diff --git a/audio/common/7.0/types.hal b/audio/common/7.0/types.hal
index 99c2e5a..bea0705 100644
--- a/audio/common/7.0/types.hal
+++ b/audio/common/7.0/types.hal
@@ -61,6 +61,8 @@
  * Audio stream type describing the intended use case of a stream.
  * See 'audioStreamType' in audio_policy_configuration.xsd for the
  * list of allowed values.
+ *
+ * An empty string is used to specify the "default" stream type.
  */
 typedef string AudioStreamType;
 
diff --git a/audio/common/all-versions/default/7.0/HidlUtils.cpp b/audio/common/all-versions/default/7.0/HidlUtils.cpp
index bb3a596..2949fac 100644
--- a/audio/common/all-versions/default/7.0/HidlUtils.cpp
+++ b/audio/common/all-versions/default/7.0/HidlUtils.cpp
@@ -335,25 +335,35 @@
     return BAD_VALUE;
 }
 
+// The "default" value of audio_stream_type_t is represented by an empty string.
 status_t HidlUtils::audioStreamTypeFromHal(audio_stream_type_t halStreamType,
                                            AudioStreamType* streamType) {
-    *streamType = audio_stream_type_to_string(halStreamType);
-    if (!streamType->empty() && !xsd::isUnknownAudioStreamType(*streamType)) {
+    if (halStreamType != AUDIO_STREAM_DEFAULT) {
+        *streamType = audio_stream_type_to_string(halStreamType);
+        if (!streamType->empty() && !xsd::isUnknownAudioStreamType(*streamType)) {
+            return NO_ERROR;
+        }
+        ALOGE("Unknown audio stream type value 0x%X", halStreamType);
+        return BAD_VALUE;
+    } else {
+        *streamType = "";
         return NO_ERROR;
     }
-    ALOGE("Unknown audio stream type value 0x%X", halStreamType);
-    return BAD_VALUE;
 }
 
 status_t HidlUtils::audioStreamTypeToHal(const AudioStreamType& streamType,
                                          audio_stream_type_t* halStreamType) {
-    if (!xsd::isUnknownAudioStreamType(streamType) &&
-        audio_stream_type_from_string(streamType.c_str(), halStreamType)) {
+    if (!streamType.empty()) {
+        if (!xsd::isUnknownAudioStreamType(streamType) &&
+            audio_stream_type_from_string(streamType.c_str(), halStreamType)) {
+            return NO_ERROR;
+        }
+        ALOGE("Unknown audio stream type \"%s\"", streamType.c_str());
+        return BAD_VALUE;
+    } else {
+        *halStreamType = AUDIO_STREAM_DEFAULT;
         return NO_ERROR;
     }
-    ALOGE("Unknown audio stream type \"%s\"", streamType.c_str());
-    *halStreamType = AUDIO_STREAM_DEFAULT;
-    return BAD_VALUE;
 }
 
 status_t HidlUtils::audioConfigFromHal(const audio_config_t& halConfig, bool isInput,
diff --git a/audio/common/all-versions/default/Android.bp b/audio/common/all-versions/default/Android.bp
index 45f0b8f..29a3d6f 100644
--- a/audio/common/all-versions/default/Android.bp
+++ b/audio/common/all-versions/default/Android.bp
@@ -114,7 +114,7 @@
     ],
 }
 
-cc_library_shared {
+cc_library {
     name: "android.hardware.audio.common@6.0-util",
     defaults: ["android.hardware.audio.common-util_default"],
     srcs: [":android.hardware.audio.common-util@2-6"],
@@ -152,6 +152,32 @@
 // Note: this isn't a VTS test, but rather a unit test
 // to verify correctness of conversion utilities.
 cc_test {
+    name: "android.hardware.audio.common@6.0-util_tests",
+    defaults: ["android.hardware.audio.common-util_default"],
+
+    srcs: ["tests/hidlutils6_tests.cpp"],
+
+    // Use static linking to allow running in presubmit on
+    // targets that don't have HAL V6.
+    static_libs: [
+        "android.hardware.audio.common@6.0",
+        "android.hardware.audio.common@6.0-util",
+    ],
+
+    cflags: [
+        "-Werror",
+        "-Wall",
+        "-DMAJOR_VERSION=6",
+        "-DMINOR_VERSION=0",
+        "-include common/all-versions/VersionMacro.h",
+    ],
+
+    test_suites: ["device-tests"],
+}
+
+// Note: this isn't a VTS test, but rather a unit test
+// to verify correctness of conversion utilities.
+cc_test {
     name: "android.hardware.audio.common@7.0-util_tests",
     defaults: ["android.hardware.audio.common-util_default"],
 
diff --git a/audio/common/all-versions/default/HidlUtils.h b/audio/common/all-versions/default/HidlUtils.h
index 22b7152..dd4ca4d 100644
--- a/audio/common/all-versions/default/HidlUtils.h
+++ b/audio/common/all-versions/default/HidlUtils.h
@@ -210,6 +210,9 @@
                *halDeviceType == AUDIO_DEVICE_IN_REMOTE_SUBMIX) {
         snprintf(halDeviceAddress, AUDIO_DEVICE_MAX_ADDRESS_LEN, "%s",
                  device.rSubmixAddress.c_str());
+    } else {
+        // Fall back to bus address for other device types, e.g. for microphones.
+        snprintf(halDeviceAddress, AUDIO_DEVICE_MAX_ADDRESS_LEN, "%s", device.busAddress.c_str());
     }
     return NO_ERROR;
 }
@@ -249,6 +252,7 @@
         device->rSubmixAddress = halDeviceAddress;
         return OK;
     }
+    // Fall back to bus address for other device types, e.g. for microphones.
     device->busAddress = halDeviceAddress;
     return NO_ERROR;
 }
diff --git a/audio/common/all-versions/default/TEST_MAPPING b/audio/common/all-versions/default/TEST_MAPPING
index 4316ccf..c965113 100644
--- a/audio/common/all-versions/default/TEST_MAPPING
+++ b/audio/common/all-versions/default/TEST_MAPPING
@@ -1,6 +1,9 @@
 {
   "presubmit": [
     {
+      "name": "android.hardware.audio.common@6.0-util_tests"
+    },
+    {
       "name": "android.hardware.audio.common@7.0-util_tests"
     }
   ]
diff --git a/audio/common/all-versions/default/tests/hidlutils6_tests.cpp b/audio/common/all-versions/default/tests/hidlutils6_tests.cpp
new file mode 100644
index 0000000..3a24e75
--- /dev/null
+++ b/audio/common/all-versions/default/tests/hidlutils6_tests.cpp
@@ -0,0 +1,108 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <gtest/gtest.h>
+
+#define LOG_TAG "HidlUtils_Test"
+#include <log/log.h>
+
+#include <HidlUtils.h>
+#include <system/audio.h>
+
+using namespace android;
+using namespace ::android::hardware::audio::common::CPP_VERSION;
+using ::android::hardware::audio::common::CPP_VERSION::implementation::HidlUtils;
+
+// Not generated automatically because DeviceAddress contains
+// an union.
+//
+// operator== must be defined in the same namespace as the data type.
+namespace android::hardware::audio::common::CPP_VERSION {
+
+inline bool operator==(const DeviceAddress& lhs, const DeviceAddress& rhs) {
+    if (lhs.device != rhs.device) return false;
+    audio_devices_t halDeviceType = static_cast<audio_devices_t>(lhs.device);
+    if (audio_is_a2dp_out_device(halDeviceType) || audio_is_a2dp_in_device(halDeviceType)) {
+        return lhs.address.mac == rhs.address.mac;
+    } else if (halDeviceType == AUDIO_DEVICE_OUT_IP || halDeviceType == AUDIO_DEVICE_IN_IP) {
+        return lhs.address.ipv4 == rhs.address.ipv4;
+    } else if (audio_is_usb_out_device(halDeviceType) || audio_is_usb_in_device(halDeviceType)) {
+        return lhs.address.alsa == rhs.address.alsa;
+    } else if (halDeviceType == AUDIO_DEVICE_OUT_REMOTE_SUBMIX ||
+               halDeviceType == AUDIO_DEVICE_IN_REMOTE_SUBMIX) {
+        return lhs.rSubmixAddress == rhs.rSubmixAddress;
+    }
+    // busAddress field can be used for types other than bus, e.g. for microphones.
+    return lhs.busAddress == rhs.busAddress;
+}
+
+}  // namespace android::hardware::audio::common::CPP_VERSION
+
+static void ConvertDeviceAddress(const DeviceAddress& device) {
+    audio_devices_t halDeviceType;
+    char halDeviceAddress[AUDIO_DEVICE_MAX_ADDRESS_LEN] = {};
+    EXPECT_EQ(NO_ERROR, HidlUtils::deviceAddressToHal(device, &halDeviceType, halDeviceAddress));
+    DeviceAddress deviceBack;
+    EXPECT_EQ(NO_ERROR,
+              HidlUtils::deviceAddressFromHal(halDeviceType, halDeviceAddress, &deviceBack));
+    EXPECT_EQ(device, deviceBack);
+}
+
+TEST(HidlUtils6, ConvertUniqueDeviceAddress) {
+    DeviceAddress speaker;
+    speaker.device = AudioDevice::OUT_SPEAKER;
+    ConvertDeviceAddress(speaker);
+
+    DeviceAddress micWithAddress;
+    micWithAddress.device = AudioDevice::IN_BUILTIN_MIC;
+    micWithAddress.busAddress = "bottom";
+    ConvertDeviceAddress(micWithAddress);
+}
+
+TEST(HidlUtils6, ConvertA2dpDeviceAddress) {
+    DeviceAddress a2dpSpeaker;
+    a2dpSpeaker.device = AudioDevice::OUT_BLUETOOTH_A2DP_SPEAKER;
+    a2dpSpeaker.address.mac = std::array<uint8_t, 6>{1, 2, 3, 4, 5, 6};
+    ConvertDeviceAddress(a2dpSpeaker);
+}
+
+TEST(HidlUtils6, ConvertIpv4DeviceAddress) {
+    DeviceAddress ipv4;
+    ipv4.device = AudioDevice::OUT_IP;
+    ipv4.address.ipv4 = std::array<uint8_t, 4>{1, 2, 3, 4};
+    ConvertDeviceAddress(ipv4);
+}
+
+TEST(HidlUtils6, ConvertUsbDeviceAddress) {
+    DeviceAddress usbHeadset;
+    usbHeadset.device = AudioDevice::OUT_USB_HEADSET;
+    usbHeadset.address.alsa = {1, 2};
+    ConvertDeviceAddress(usbHeadset);
+}
+
+TEST(HidlUtils6, ConvertBusDeviceAddress) {
+    DeviceAddress bus;
+    bus.device = AudioDevice::OUT_BUS;
+    bus.busAddress = "bus_device";
+    ConvertDeviceAddress(bus);
+}
+
+TEST(HidlUtils6, ConvertRSubmixDeviceAddress) {
+    DeviceAddress rSubmix;
+    rSubmix.device = AudioDevice::OUT_REMOTE_SUBMIX;
+    rSubmix.rSubmixAddress = AUDIO_REMOTE_SUBMIX_DEVICE_ADDRESS;
+    ConvertDeviceAddress(rSubmix);
+}
diff --git a/audio/common/all-versions/default/tests/hidlutils_tests.cpp b/audio/common/all-versions/default/tests/hidlutils_tests.cpp
index 40fc5c8..ec6bdf3 100644
--- a/audio/common/all-versions/default/tests/hidlutils_tests.cpp
+++ b/audio/common/all-versions/default/tests/hidlutils_tests.cpp
@@ -44,8 +44,8 @@
         static_cast<audio_gain_mode_t>(0xFFFFFFFFU);
 // AUDIO_SOURCE_INVALID is framework-only.
 static constexpr audio_source_t kInvalidHalSource = static_cast<audio_source_t>(-1);
-static constexpr audio_stream_type_t kInvalidHalStreamType =
-        static_cast<audio_stream_type_t>(0xFFFFFFFFU);
+// AUDIO_STREAM_DEFAULT is framework-only
+static constexpr audio_stream_type_t kInvalidHalStreamType = static_cast<audio_stream_type_t>(-2);
 static constexpr audio_usage_t kInvalidHalUsage = static_cast<audio_usage_t>(0xFFFFFFFFU);
 
 TEST(HidlUtils, ConvertInvalidChannelMask) {
@@ -476,6 +476,11 @@
     DeviceAddress speaker;
     speaker.deviceType = toString(xsd::AudioDevice::AUDIO_DEVICE_OUT_SPEAKER);
     ConvertDeviceAddress(speaker);
+
+    DeviceAddress micWithAddress;
+    micWithAddress.deviceType = toString(xsd::AudioDevice::AUDIO_DEVICE_IN_BUILTIN_MIC);
+    micWithAddress.address.id("bottom");
+    ConvertDeviceAddress(micWithAddress);
 }
 
 TEST(HidlUtils, ConvertA2dpDeviceAddress) {
@@ -660,10 +665,18 @@
     AudioStreamType invalid;
     EXPECT_EQ(BAD_VALUE, HidlUtils::audioStreamTypeFromHal(kInvalidHalStreamType, &invalid));
     audio_stream_type_t halInvalid;
-    EXPECT_EQ(BAD_VALUE, HidlUtils::audioStreamTypeToHal("", &halInvalid));
     EXPECT_EQ(BAD_VALUE, HidlUtils::audioStreamTypeToHal("random string", &halInvalid));
 }
 
+TEST(HidlUtils, ConvertDefaultStreamType) {
+    AudioStreamType streamDefault = "";
+    audio_stream_type_t halStreamDefault;
+    EXPECT_EQ(NO_ERROR, HidlUtils::audioStreamTypeToHal(streamDefault, &halStreamDefault));
+    AudioStreamType streamDefaultBack;
+    EXPECT_EQ(NO_ERROR, HidlUtils::audioStreamTypeFromHal(halStreamDefault, &streamDefaultBack));
+    EXPECT_EQ(streamDefault, streamDefaultBack);
+}
+
 TEST(HidlUtils, ConvertStreamType) {
     for (const auto enumVal : xsdc_enum_range<xsd::AudioStreamType>{}) {
         const AudioStreamType streamType = toString(enumVal);
diff --git a/audio/core/all-versions/vts/functional/4.0/AudioPrimaryHidlHalTest.cpp b/audio/core/all-versions/vts/functional/4.0/AudioPrimaryHidlHalTest.cpp
index bb7c6d3..f87e5ed 100644
--- a/audio/core/all-versions/vts/functional/4.0/AudioPrimaryHidlHalTest.cpp
+++ b/audio/core/all-versions/vts/functional/4.0/AudioPrimaryHidlHalTest.cpp
@@ -322,9 +322,9 @@
                 const SourceMetadata metadata = {
                         {{toString(usage),
                           toString(content),
-                          {} /* tags */,
+                          volume,
                           toString(xsd::AudioChannelMask::AUDIO_CHANNEL_OUT_STEREO),
-                          volume}}};
+                          {} /* tags */}}};
                 ASSERT_RESULT(okOrNotSupported, stream->updateSourceMetadata(metadata))
                         << "usage=" << toString(usage) << ", content=" << toString(content)
                         << ", volume=" << volume;
diff --git a/automotive/OWNERS b/automotive/OWNERS
index fb3e3d6..43c5f3e 100644
--- a/automotive/OWNERS
+++ b/automotive/OWNERS
@@ -1,6 +1,6 @@
 pirozzoj@google.com
 twasilczyk@google.com
-pfg@google.com
+krachuri@google.com
 gurunagarajan@google.com
 keunyoung@google.com
 felipeal@google.com
diff --git a/automotive/evs/1.1/vts/functional/VtsHalEvsV1_1TargetTest.cpp b/automotive/evs/1.1/vts/functional/VtsHalEvsV1_1TargetTest.cpp
index e56c2d1..a3dc45b 100644
--- a/automotive/evs/1.1/vts/functional/VtsHalEvsV1_1TargetTest.cpp
+++ b/automotive/evs/1.1/vts/functional/VtsHalEvsV1_1TargetTest.cpp
@@ -41,14 +41,14 @@
 #include <utils/Errors.h>
 #include <utils/StrongPointer.h>
 
+#include <android-base/logging.h>
 #include <android/hardware/automotive/evs/1.1/IEvsCamera.h>
 #include <android/hardware/automotive/evs/1.1/IEvsCameraStream.h>
-#include <android/hardware/automotive/evs/1.1/IEvsEnumerator.h>
 #include <android/hardware/automotive/evs/1.1/IEvsDisplay.h>
+#include <android/hardware/automotive/evs/1.1/IEvsEnumerator.h>
 #include <android/hardware/camera/device/3.2/ICameraDevice.h>
-#include <android-base/logging.h>
 #include <system/camera_metadata.h>
-#include <ui/DisplayConfig.h>
+#include <ui/DisplayMode.h>
 #include <ui/DisplayState.h>
 #include <ui/GraphicBuffer.h>
 #include <ui/GraphicBufferAllocator.h>
@@ -622,7 +622,7 @@
         ASSERT_GT(config.size(), 0);
         ASSERT_GT(state.size(), 0);
 
-        android::DisplayConfig* pConfig = (android::DisplayConfig*)config.data();
+        android::ui::DisplayMode* pConfig = (android::ui::DisplayMode*)config.data();
         const auto width = pConfig->resolution.getWidth();
         const auto height = pConfig->resolution.getHeight();
         LOG(INFO) << "    Resolution: " << width << "x" << height;
diff --git a/biometrics/face/1.1/default/Android.bp b/biometrics/face/1.0/default/Android.bp
similarity index 84%
rename from biometrics/face/1.1/default/Android.bp
rename to biometrics/face/1.0/default/Android.bp
index 360071f..d6ff087 100644
--- a/biometrics/face/1.1/default/Android.bp
+++ b/biometrics/face/1.0/default/Android.bp
@@ -15,10 +15,10 @@
  */
 
 cc_binary {
-    name: "android.hardware.biometrics.face@1.1-service.example",
+    name: "android.hardware.biometrics.face@1.0-service.example",
     defaults: ["hidl_defaults"],
     vendor: true,
-    init_rc: ["android.hardware.biometrics.face@1.1-service.rc"],
+    init_rc: ["android.hardware.biometrics.face@1.0-service.rc"],
     vintf_fragments: ["manifest_face_default.xml"],
     relative_install_path: "hw",
     proprietary: true,
@@ -31,6 +31,5 @@
         "libutils",
         "liblog",
         "android.hardware.biometrics.face@1.0",
-        "android.hardware.biometrics.face@1.1",
     ],
 }
diff --git a/biometrics/face/1.1/default/BiometricsFace.cpp b/biometrics/face/1.0/default/BiometricsFace.cpp
similarity index 81%
rename from biometrics/face/1.1/default/BiometricsFace.cpp
rename to biometrics/face/1.0/default/BiometricsFace.cpp
index 57b3a92..97dc469 100644
--- a/biometrics/face/1.1/default/BiometricsFace.cpp
+++ b/biometrics/face/1.0/default/BiometricsFace.cpp
@@ -110,20 +110,4 @@
     return Status::OK;
 }
 
-// Methods from ::android::hardware::biometrics::face::V1_1::IBiometricsFace follow.
-Return<Status> BiometricsFace::enroll_1_1(const hidl_vec<uint8_t>& /* hat */,
-                                          uint32_t /* timeoutSec */,
-                                          const hidl_vec<Feature>& /* disabledFeatures */,
-                                          const hidl_handle& /* windowId */) {
-    mClientCallback->onError(kDeviceId, mUserId, FaceError::UNABLE_TO_PROCESS, 0 /* vendorCode */);
-    return Status::OK;
-}
-
-Return<Status> BiometricsFace::enrollRemotely(const hidl_vec<uint8_t>& /* hat */,
-                                              uint32_t /* timeoutSec */,
-                                              const hidl_vec<Feature>& /* disabledFeatures */) {
-    mClientCallback->onError(kDeviceId, mUserId, FaceError::UNABLE_TO_PROCESS, 0 /* vendorCode */);
-    return Status::OK;
-}
-
 }  // namespace android::hardware::biometrics::face::implementation
diff --git a/biometrics/face/1.1/default/BiometricsFace.h b/biometrics/face/1.0/default/BiometricsFace.h
similarity index 81%
rename from biometrics/face/1.1/default/BiometricsFace.h
rename to biometrics/face/1.0/default/BiometricsFace.h
index 5ce5771..1d99ed2 100644
--- a/biometrics/face/1.1/default/BiometricsFace.h
+++ b/biometrics/face/1.0/default/BiometricsFace.h
@@ -16,7 +16,7 @@
 
 #pragma once
 
-#include <android/hardware/biometrics/face/1.1/IBiometricsFace.h>
+#include <android/hardware/biometrics/face/1.0/IBiometricsFace.h>
 #include <hidl/MQDescriptor.h>
 #include <hidl/Status.h>
 #include <random>
@@ -34,7 +34,7 @@
 using ::android::hardware::biometrics::face::V1_0::IBiometricsFaceClientCallback;
 using ::android::hardware::biometrics::face::V1_0::Status;
 
-class BiometricsFace : public V1_1::IBiometricsFace {
+class BiometricsFace : public V1_0::IBiometricsFace {
   public:
     BiometricsFace();
 
@@ -71,14 +71,6 @@
 
     Return<Status> resetLockout(const hidl_vec<uint8_t>& hat) override;
 
-    // Methods from ::android::hardware::biometrics::face::V1_1::IBiometricsFace follow.
-    Return<Status> enroll_1_1(const hidl_vec<uint8_t>& hat, uint32_t timeoutSec,
-                              const hidl_vec<Feature>& disabledFeatures,
-                              const hidl_handle& windowId) override;
-
-    Return<Status> enrollRemotely(const hidl_vec<uint8_t>& hat, uint32_t timeoutSec,
-                                  const hidl_vec<Feature>& disabledFeatures) override;
-
   private:
     std::mt19937 mRandom;
     int32_t mUserId;
diff --git a/biometrics/face/1.1/default/android.hardware.biometrics.face@1.1-service.rc b/biometrics/face/1.0/default/android.hardware.biometrics.face@1.0-service.rc
similarity index 75%
rename from biometrics/face/1.1/default/android.hardware.biometrics.face@1.1-service.rc
rename to biometrics/face/1.0/default/android.hardware.biometrics.face@1.0-service.rc
index 687e2d8..6c7362f 100644
--- a/biometrics/face/1.1/default/android.hardware.biometrics.face@1.1-service.rc
+++ b/biometrics/face/1.0/default/android.hardware.biometrics.face@1.0-service.rc
@@ -1,4 +1,4 @@
-service vendor.face-hal-1-1-default /vendor/bin/hw/android.hardware.biometrics.face@1.1-service.example
+service vendor.face-hal-1-0-default /vendor/bin/hw/android.hardware.biometrics.face@1.0-service.example
     # "class hal" causes a race condition on some devices due to files created
     # in /data. As a workaround, postpone startup until later in boot once
     # /data is mounted.
diff --git a/biometrics/face/1.1/default/manifest_face_default.xml b/biometrics/face/1.0/default/manifest_face_default.xml
similarity index 90%
rename from biometrics/face/1.1/default/manifest_face_default.xml
rename to biometrics/face/1.0/default/manifest_face_default.xml
index ec71d9c..380ae49 100644
--- a/biometrics/face/1.1/default/manifest_face_default.xml
+++ b/biometrics/face/1.0/default/manifest_face_default.xml
@@ -2,7 +2,7 @@
     <hal format="hidl">
         <name>android.hardware.biometrics.face</name>
         <transport>hwbinder</transport>
-        <version>1.1</version>
+        <version>1.0</version>
         <interface>
             <name>IBiometricsFace</name>
             <instance>default</instance>
diff --git a/biometrics/face/1.1/default/service.cpp b/biometrics/face/1.0/default/service.cpp
similarity index 88%
rename from biometrics/face/1.1/default/service.cpp
rename to biometrics/face/1.0/default/service.cpp
index 344bdb9..9818c95 100644
--- a/biometrics/face/1.1/default/service.cpp
+++ b/biometrics/face/1.0/default/service.cpp
@@ -14,10 +14,10 @@
  * limitations under the License.
  */
 
-#define LOG_TAG "android.hardware.biometrics.face@1.1-service"
+#define LOG_TAG "android.hardware.biometrics.face@1.0-service"
 
 #include <android/hardware/biometrics/face/1.0/types.h>
-#include <android/hardware/biometrics/face/1.1/IBiometricsFace.h>
+#include <android/hardware/biometrics/face/1.0/IBiometricsFace.h>
 #include <android/log.h>
 #include <hidl/HidlSupport.h>
 #include <hidl/HidlTransportSupport.h>
@@ -27,7 +27,7 @@
 using android::hardware::configureRpcThreadpool;
 using android::hardware::joinRpcThreadpool;
 using android::hardware::biometrics::face::implementation::BiometricsFace;
-using android::hardware::biometrics::face::V1_1::IBiometricsFace;
+using android::hardware::biometrics::face::V1_0::IBiometricsFace;
 
 int main() {
     ALOGI("BiometricsFace HAL is being started.");
diff --git a/biometrics/face/1.1/Android.bp b/biometrics/face/1.1/Android.bp
deleted file mode 100644
index 14a86f1..0000000
--- a/biometrics/face/1.1/Android.bp
+++ /dev/null
@@ -1,14 +0,0 @@
-// This file is autogenerated by hidl-gen -Landroidbp.
-
-hidl_interface {
-    name: "android.hardware.biometrics.face@1.1",
-    root: "android.hardware",
-    srcs: [
-        "IBiometricsFace.hal",
-    ],
-    interfaces: [
-        "android.hardware.biometrics.face@1.0",
-        "android.hidl.base@1.0",
-    ],
-    gen_java: true,
-}
diff --git a/biometrics/face/1.1/IBiometricsFace.hal b/biometrics/face/1.1/IBiometricsFace.hal
deleted file mode 100644
index 84e7443..0000000
--- a/biometrics/face/1.1/IBiometricsFace.hal
+++ /dev/null
@@ -1,117 +0,0 @@
-/*
- * Copyright (C) 2019 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package android.hardware.biometrics.face@1.1;
-
-import @1.0::IBiometricsFace;
-import @1.0::Status;
-import @1.0::Feature;
-
-/**
- * The HAL interface for biometric face authentication.
- */
-interface IBiometricsFace extends @1.0::IBiometricsFace {
-    /**
-     * Enrolls a user's face for a remote client, for example Android Auto.
-     *
-     * The HAL implementation is responsible for creating a secure communication
-     * channel and receiving the enrollment images from a mobile device with
-     * face authentication hardware.
-     *
-     * Note that the Hardware Authentication Token must be valid for the
-     * duration of enrollment and thus should be explicitly invalidated by a
-     * call to revokeChallenge() when enrollment is complete, to reduce the
-     * window of opportunity to re-use the challenge and HAT. For example,
-     * Settings calls generateChallenge() once to allow the user to enroll one
-     * or more faces or toggle secure settings without having to re-enter the
-     * PIN/pattern/password. Once the user completes the operation, Settings
-     * invokes revokeChallenge() to close the transaction. If the HAT is expired,
-     * the implementation must invoke onError with UNABLE_TO_PROCESS.
-     *
-     * Requirements for using this API:
-     * - Mobile devices MUST NOT delegate enrollment to another device by calling
-     * this API. This feature is intended only to allow enrollment on devices
-     * where it is impossible to enroll locally on the device.
-     * - The path MUST be protected by a secret key with rollback protection.
-     * - Synchronizing between devices MUST be accomplished by having both
-     * devices agree on a secret PIN entered by the user (similar to BT
-     * pairing procedure) and use a salted version of that PIN plus other secret
-     * to encrypt traffic.
-     * - All communication to/from the remote device MUST be encrypted and signed
-     * to prevent image injection and other man-in-the-middle type attacks.
-     * - generateChallenge() and revokeChallenge() MUST be implemented on both
-     * remote and local host (e.g. hash the result of the remote host with a
-     * local secret before responding to the API call) and any transmission of
-     * the challenge between hosts MUST be signed to prevent man-in-the-middle
-     * attacks.
-     * - In the event of a lost connection, the result of the last
-     * generateChallenge() MUST be invalidated and the process started over.
-     * - Both the remote and local host MUST honor the timeout and invalidate the
-     * challenge.
-     *
-     * This method triggers the IBiometricsFaceClientCallback#onEnrollResult()
-     * method.
-     *
-     * @param hat A valid Hardware Authentication Token, generated as a result
-     *     of a generateChallenge() challenge being wrapped by the gatekeeper
-     *     after a successful strong authentication request.
-     * @param timeoutSec A timeout in seconds, after which this enroll
-     *     attempt is cancelled. Note that the framework can continue
-     *     enrollment by calling this again with a valid HAT. This timeout is
-     *     expected to be used to limit power usage if the device becomes idle
-     *     during enrollment. The implementation is expected to send
-     *     ERROR_TIMEOUT if this happens.
-     * @param disabledFeatures A list of features to be disabled during
-     *     enrollment. Note that all features are enabled by default.
-     * @return status The status of this method call.
-     */
-    enrollRemotely(vec<uint8_t> hat, uint32_t timeoutSec, vec<Feature> disabledFeatures)
-        generates (Status status);
-
-    /**
-     * Enrolls a user's face.
-     *
-     * Note that the Hardware Authentication Token must be valid for the
-     * duration of enrollment and thus should be explicitly invalidated by a
-     * call to revokeChallenge() when enrollment is complete, to reduce the
-     * window of opportunity to re-use the challenge and HAT. For example,
-     * Settings calls generateChallenge() once to allow the user to enroll one
-     * or more faces or toggle secure settings without having to re-enter the
-     * PIN/pattern/password. Once the user completes the operation, Settings
-     * invokes revokeChallenge() to close the transaction. If the HAT is expired,
-     * the implementation must invoke onError with UNABLE_TO_PROCESS.
-     *
-     * This method triggers the IBiometricsFaceClientCallback#onEnrollResult()
-     * method.
-     *
-     * @param hat A valid Hardware Authentication Token, generated as a result
-     *     of a generateChallenge() challenge being wrapped by the gatekeeper
-     *     after a successful strong authentication request.
-     * @param timeoutSec A timeout in seconds, after which this enroll
-     *     attempt is cancelled. Note that the framework can continue
-     *     enrollment by calling this again with a valid HAT. This timeout is
-     *     expected to be used to limit power usage if the device becomes idle
-     *     during enrollment. The implementation is expected to send
-     *     ERROR_TIMEOUT if this happens.
-     * @param disabledFeatures A list of features to be disabled during
-     *     enrollment. Note that all features are enabled by default.
-     * @param windowId optional ID of a camera preview window for a
-     *     single-camera device. Must be null if not used.
-     * @return status The status of this method call.
-     */
-    enroll_1_1(vec<uint8_t> hat, uint32_t timeoutSec, vec<Feature> disabledFeatures,
-        handle windowId) generates (Status status);
-};
diff --git a/biometrics/face/1.1/vts/functional/Android.bp b/biometrics/face/1.1/vts/functional/Android.bp
deleted file mode 100644
index aa0b1fa..0000000
--- a/biometrics/face/1.1/vts/functional/Android.bp
+++ /dev/null
@@ -1,29 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-cc_test {
-    name: "VtsHalBiometricsFaceV1_1TargetTest",
-    defaults: ["VtsHalTargetTestDefaults"],
-    srcs: ["VtsHalBiometricsFaceV1_1TargetTest.cpp"],
-    static_libs: [
-        "android.hardware.biometrics.face@1.0",
-        "android.hardware.biometrics.face@1.1",
-    ],
-    test_suites: [
-        "general-tests",
-        "vts",
-    ],
-}
diff --git a/biometrics/face/1.1/vts/functional/VtsHalBiometricsFaceV1_1TargetTest.cpp b/biometrics/face/1.1/vts/functional/VtsHalBiometricsFaceV1_1TargetTest.cpp
deleted file mode 100644
index 0077c8c..0000000
--- a/biometrics/face/1.1/vts/functional/VtsHalBiometricsFaceV1_1TargetTest.cpp
+++ /dev/null
@@ -1,206 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#define LOG_TAG "biometrics_face_hidl_hal_test"
-
-#include <android/hardware/biometrics/face/1.0/IBiometricsFaceClientCallback.h>
-#include <android/hardware/biometrics/face/1.1/IBiometricsFace.h>
-
-#include <VtsHalHidlTargetCallbackBase.h>
-#include <android-base/logging.h>
-#include <gtest/gtest.h>
-#include <hidl/GtestPrinter.h>
-#include <hidl/ServiceManagement.h>
-
-#include <chrono>
-#include <cstdint>
-#include <random>
-
-using android::sp;
-using android::hardware::hidl_handle;
-using android::hardware::hidl_vec;
-using android::hardware::Return;
-using android::hardware::Void;
-using android::hardware::biometrics::face::V1_0::FaceAcquiredInfo;
-using android::hardware::biometrics::face::V1_0::FaceError;
-using android::hardware::biometrics::face::V1_0::IBiometricsFaceClientCallback;
-using android::hardware::biometrics::face::V1_0::OptionalUint64;
-using android::hardware::biometrics::face::V1_0::Status;
-using android::hardware::biometrics::face::V1_1::IBiometricsFace;
-
-namespace {
-
-// Arbitrary, nonexistent userId
-constexpr uint32_t kUserId = 9;
-constexpr uint32_t kTimeoutSec = 3;
-constexpr auto kTimeout = std::chrono::seconds(kTimeoutSec);
-constexpr char kFacedataDir[] = "/data/vendor_de/0/facedata";
-constexpr char kCallbackNameOnError[] = "onError";
-
-// Callback arguments that need to be captured for the tests.
-struct FaceCallbackArgs {
-    // The error passed to the last onError() callback.
-    FaceError error;
-
-    // The userId passed to the last callback.
-    int32_t userId;
-};
-
-// Test callback class for the BiometricsFace HAL.
-// The HAL will call these callback methods to notify about completed operations
-// or encountered errors.
-class FaceCallback : public ::testing::VtsHalHidlTargetCallbackBase<FaceCallbackArgs>,
-                     public IBiometricsFaceClientCallback {
-  public:
-    Return<void> onEnrollResult(uint64_t, uint32_t, int32_t, uint32_t) override { return Void(); }
-
-    Return<void> onAuthenticated(uint64_t, uint32_t, int32_t, const hidl_vec<uint8_t>&) override {
-        return Void();
-    }
-
-    Return<void> onAcquired(uint64_t, int32_t, FaceAcquiredInfo, int32_t) override {
-        return Void();
-    }
-
-    Return<void> onError(uint64_t, int32_t userId, FaceError error, int32_t) override {
-        FaceCallbackArgs args = {};
-        args.error = error;
-        args.userId = userId;
-        NotifyFromCallback(kCallbackNameOnError, args);
-        return Void();
-    }
-
-    Return<void> onRemoved(uint64_t, const hidl_vec<uint32_t>&, int32_t) override { return Void(); }
-
-    Return<void> onEnumerate(uint64_t, const hidl_vec<uint32_t>&, int32_t) override {
-        return Void();
-    }
-
-    Return<void> onLockoutChanged(uint64_t) override { return Void(); }
-};
-
-// Test class for the BiometricsFace HAL.
-class FaceHidlTest : public ::testing::TestWithParam<std::string> {
-  public:
-    void SetUp() override {
-        mService = IBiometricsFace::getService(GetParam());
-        ASSERT_NE(mService, nullptr);
-        mCallback = new FaceCallback();
-        mCallback->SetWaitTimeoutDefault(kTimeout);
-        Return<void> ret1 = mService->setCallback(mCallback, [](const OptionalUint64& res) {
-            ASSERT_EQ(Status::OK, res.status);
-            // Makes sure the "deviceId" represented by "res.value" is not 0.
-            // 0 would mean the HIDL is not available.
-            ASSERT_NE(0UL, res.value);
-        });
-        ASSERT_TRUE(ret1.isOk());
-        Return<Status> ret2 = mService->setActiveUser(kUserId, kFacedataDir);
-        ASSERT_EQ(Status::OK, static_cast<Status>(ret2));
-    }
-
-    void TearDown() override {}
-
-    sp<IBiometricsFace> mService;
-    sp<FaceCallback> mCallback;
-};
-
-// enroll with an invalid (all zeroes) HAT should fail.
-TEST_P(FaceHidlTest, Enroll1_1ZeroHatTest) {
-    // Filling HAT with zeros
-    hidl_vec<uint8_t> token(69);
-    for (size_t i = 0; i < 69; i++) {
-        token[i] = 0;
-    }
-
-    hidl_handle windowId = nullptr;
-    Return<Status> ret = mService->enroll_1_1(token, kTimeoutSec, {}, windowId);
-    ASSERT_EQ(Status::OK, static_cast<Status>(ret));
-
-    // onError should be called with a meaningful (nonzero) error.
-    auto res = mCallback->WaitForCallback(kCallbackNameOnError);
-    EXPECT_TRUE(res.no_timeout);
-    EXPECT_EQ(kUserId, res.args->userId);
-    EXPECT_EQ(FaceError::UNABLE_TO_PROCESS, res.args->error);
-}
-
-// enroll with an invalid HAT should fail.
-TEST_P(FaceHidlTest, Enroll1_1GarbageHatTest) {
-    // Filling HAT with pseudorandom invalid data.
-    // Using default seed to make the test reproducible.
-    std::mt19937 gen(std::mt19937::default_seed);
-    std::uniform_int_distribution<uint8_t> dist;
-    hidl_vec<uint8_t> token(69);
-    for (size_t i = 0; i < 69; ++i) {
-        token[i] = dist(gen);
-    }
-
-    hidl_handle windowId = nullptr;
-    Return<Status> ret = mService->enroll_1_1(token, kTimeoutSec, {}, windowId);
-    ASSERT_EQ(Status::OK, static_cast<Status>(ret));
-
-    // onError should be called with a meaningful (nonzero) error.
-    auto res = mCallback->WaitForCallback(kCallbackNameOnError);
-    EXPECT_TRUE(res.no_timeout);
-    EXPECT_EQ(kUserId, res.args->userId);
-    EXPECT_EQ(FaceError::UNABLE_TO_PROCESS, res.args->error);
-}
-
-// enroll with an invalid (all zeroes) HAT should fail.
-TEST_P(FaceHidlTest, EnrollRemotelyZeroHatTest) {
-    // Filling HAT with zeros
-    hidl_vec<uint8_t> token(69);
-    for (size_t i = 0; i < 69; i++) {
-        token[i] = 0;
-    }
-
-    Return<Status> ret = mService->enrollRemotely(token, kTimeoutSec, {});
-    ASSERT_EQ(Status::OK, static_cast<Status>(ret));
-
-    // onError should be called with a meaningful (nonzero) error.
-    auto res = mCallback->WaitForCallback(kCallbackNameOnError);
-    EXPECT_TRUE(res.no_timeout);
-    EXPECT_EQ(kUserId, res.args->userId);
-    EXPECT_EQ(FaceError::UNABLE_TO_PROCESS, res.args->error);
-}
-
-// enroll with an invalid HAT should fail.
-TEST_P(FaceHidlTest, EnrollRemotelyGarbageHatTest) {
-    // Filling HAT with pseudorandom invalid data.
-    // Using default seed to make the test reproducible.
-    std::mt19937 gen(std::mt19937::default_seed);
-    std::uniform_int_distribution<uint8_t> dist;
-    hidl_vec<uint8_t> token(69);
-    for (size_t i = 0; i < 69; ++i) {
-        token[i] = dist(gen);
-    }
-
-    Return<Status> ret = mService->enrollRemotely(token, kTimeoutSec, {});
-    ASSERT_EQ(Status::OK, static_cast<Status>(ret));
-
-    // onError should be called with a meaningful (nonzero) error.
-    auto res = mCallback->WaitForCallback(kCallbackNameOnError);
-    EXPECT_TRUE(res.no_timeout);
-    EXPECT_EQ(kUserId, res.args->userId);
-    EXPECT_EQ(FaceError::UNABLE_TO_PROCESS, res.args->error);
-}
-
-}  // anonymous namespace
-
-GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(FaceHidlTest);
-INSTANTIATE_TEST_SUITE_P(
-        PerInstance, FaceHidlTest,
-        testing::ValuesIn(android::hardware::getAllHalInstanceNames(IBiometricsFace::descriptor)),
-        android::hardware::PrintInstanceNameToString);
diff --git a/biometrics/face/aidl/android/hardware/biometrics/face/ISessionCallback.aidl b/biometrics/face/aidl/android/hardware/biometrics/face/ISessionCallback.aidl
index 354f4a7..2e3cd95 100644
--- a/biometrics/face/aidl/android/hardware/biometrics/face/ISessionCallback.aidl
+++ b/biometrics/face/aidl/android/hardware/biometrics/face/ISessionCallback.aidl
@@ -17,10 +17,10 @@
 package android.hardware.biometrics.face;
 
 import android.hardware.biometrics.face.AcquiredInfo;
-import android.hardware.biometrics.face.Feature;
 import android.hardware.biometrics.face.AuthenticationFrame;
 import android.hardware.biometrics.face.EnrollmentFrame;
 import android.hardware.biometrics.face.Error;
+import android.hardware.biometrics.face.Feature;
 import android.hardware.biometrics.face.SessionState;
 import android.hardware.keymaster.HardwareAuthToken;
 
@@ -100,9 +100,8 @@
     /**
      * This method must only be used to notify the framework during SessionState::AUTHENTICATING.
      *
-     * Used to notify the framework upon successful authentication. Note that the authentication
-     * lifecycle ends when either 1) a face is accepted, or 2) an error occurred. The
-     * authentication lifecycle does NOT end when a face is rejected.
+     * Used to notify the framework about a successful authentication. This ends the authentication
+     * lifecycle.
      *
      * @param enrollmentId Face that was accepted.
      * @param hat If the sensor is configured as SensorStrength::STRONG, a non-null attestation that
@@ -115,9 +114,8 @@
     /**
      * This method must only be used to notify the framework during SessionState::AUTHENTICATING.
      *
-     * Used to notify the framework upon rejected attempts. Note that the authentication
-     * lifecycle ends when either 1) a face is accepted, or 2) an occurred. The
-     * authentication lifecycle does NOT end when a face is rejected.
+     * Used to notify the framework about a failed authentication. This ends the authentication
+     * lifecycle.
      */
     void onAuthenticationFailed();
 
diff --git a/biometrics/face/aidl/default/Session.cpp b/biometrics/face/aidl/default/Session.cpp
index 63d1721..bd5a062 100644
--- a/biometrics/face/aidl/default/Session.cpp
+++ b/biometrics/face/aidl/default/Session.cpp
@@ -15,6 +15,7 @@
  */
 
 #include <aidl/android/hardware/biometrics/common/BnCancellationSignal.h>
+#include <android-base/logging.h>
 
 #include "Session.h"
 
@@ -37,6 +38,7 @@
 Session::Session(std::shared_ptr<ISessionCallback> cb) : cb_(std::move(cb)) {}
 
 ndk::ScopedAStatus Session::generateChallenge(int32_t /*cookie*/, int32_t /*timeoutSec*/) {
+    LOG(INFO) << "generateChallenge";
     if (cb_) {
         cb_->onStateChanged(0, SessionState::GENERATING_CHALLENGE);
         cb_->onChallengeGenerated(0);
@@ -46,6 +48,7 @@
 }
 
 ndk::ScopedAStatus Session::revokeChallenge(int32_t /*cookie*/, int64_t challenge) {
+    LOG(INFO) << "revokeChallenge";
     if (cb_) {
         cb_->onStateChanged(0, SessionState::REVOKING_CHALLENGE);
         cb_->onChallengeRevoked(challenge);
@@ -59,11 +62,13 @@
         EnrollmentType /*enrollmentType*/, const std::vector<Feature>& /*features*/,
         const NativeHandle& /*previewSurface*/,
         std::shared_ptr<biometrics::common::ICancellationSignal>* /*return_val*/) {
+    LOG(INFO) << "enroll";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::authenticate(int32_t /*cookie*/, int64_t /*keystoreOperationId*/,
                                          std::shared_ptr<common::ICancellationSignal>* return_val) {
+    LOG(INFO) << "authenticate";
     if (cb_) {
         cb_->onStateChanged(0, SessionState::AUTHENTICATING);
     }
@@ -73,10 +78,12 @@
 
 ndk::ScopedAStatus Session::detectInteraction(
         int32_t /*cookie*/, std::shared_ptr<common::ICancellationSignal>* /*return_val*/) {
+    LOG(INFO) << "detectInteraction";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::enumerateEnrollments(int32_t /*cookie*/) {
+    LOG(INFO) << "enumerateEnrollments";
     if (cb_) {
         cb_->onStateChanged(0, SessionState::ENUMERATING_ENROLLMENTS);
         cb_->onEnrollmentsEnumerated(std::vector<int32_t>());
@@ -87,6 +94,7 @@
 
 ndk::ScopedAStatus Session::removeEnrollments(int32_t /*cookie*/,
                                               const std::vector<int32_t>& /*enrollmentIds*/) {
+    LOG(INFO) << "removeEnrollments";
     if (cb_) {
         cb_->onStateChanged(0, SessionState::REMOVING_ENROLLMENTS);
         cb_->onEnrollmentsRemoved(std::vector<int32_t>());
@@ -96,6 +104,7 @@
 }
 
 ndk::ScopedAStatus Session::getFeatures(int32_t /*cookie*/, int32_t /*enrollmentId*/) {
+    LOG(INFO) << "getFeatures";
     return ndk::ScopedAStatus::ok();
 }
 
@@ -103,10 +112,12 @@
                                        const keymaster::HardwareAuthToken& /*hat*/,
                                        int32_t /*enrollmentId*/, Feature /*feature*/,
                                        bool /*enabled*/) {
+    LOG(INFO) << "setFeature";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::getAuthenticatorId(int32_t /*cookie*/) {
+    LOG(INFO) << "getAuthenticatorId";
     if (cb_) {
         cb_->onStateChanged(0, SessionState::GETTING_AUTHENTICATOR_ID);
         cb_->onAuthenticatorIdRetrieved(0 /* authenticatorId */);
@@ -116,11 +127,13 @@
 }
 
 ndk::ScopedAStatus Session::invalidateAuthenticatorId(int32_t /*cookie*/) {
+    LOG(INFO) << "invalidateAuthenticatorId";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::resetLockout(int32_t /*cookie*/,
                                          const keymaster::HardwareAuthToken& /*hat*/) {
+    LOG(INFO) << "resetLockout";
     if (cb_) {
         cb_->onStateChanged(0, SessionState::RESETTING_LOCKOUT);
         cb_->onLockoutCleared();
diff --git a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SensorLocation.aidl b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SensorLocation.aidl
new file mode 100644
index 0000000..a6e8b4d
--- /dev/null
+++ b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SensorLocation.aidl
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.biometrics.fingerprint;
+@VintfStability
+parcelable SensorLocation {
+  int displayId;
+  int sensorLocationX;
+  int sensorLocationY;
+  int sensorRadius;
+}
diff --git a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SensorProps.aidl b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SensorProps.aidl
index c3daacd..53ac6dd 100644
--- a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SensorProps.aidl
+++ b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SensorProps.aidl
@@ -35,10 +35,7 @@
 parcelable SensorProps {
   android.hardware.biometrics.common.CommonProps commonProps;
   android.hardware.biometrics.fingerprint.FingerprintSensorType sensorType;
+  android.hardware.biometrics.fingerprint.SensorLocation[] sensorLocations;
   boolean supportsNavigationGestures;
-  int sensorLocationX;
-  int sensorLocationY;
-  int sensorRadius;
-  int displayId;
   boolean supportsDetectInteraction;
 }
diff --git a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SensorLocation.aidl b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SensorLocation.aidl
new file mode 100644
index 0000000..62a2e8c
--- /dev/null
+++ b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SensorLocation.aidl
@@ -0,0 +1,54 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.biometrics.fingerprint;
+
+@VintfStability
+parcelable SensorLocation {
+    /**
+     * The display to which the following measurements are relative to. This must correspond to the
+     * android.hardware.DisplayManager#getDisplay Android API.
+     *
+     * A few examples:
+     *   1) A capacitive rear fingerprint sensor would specify the display to which it is behind.
+     *   2) An under-display fingerprint sensor would specify the display on which the sensor is
+     *      located.
+     *   3) A foldable device would specify multiple locations and have a SensorLocation entry
+     *      for each display from which the sensor is accessible from.
+     */
+    int displayId;
+
+    /**
+     * The location of the center of the sensor if applicable. For example, sensors of
+     * FingerprintSensorType::UNDER_DISPLAY_* would report this value as the distance in pixels,
+     * measured from the left edge of the screen.
+     */
+    int sensorLocationX;
+
+    /**
+     * The location of the center of the sensor if applicable. For example, sensors of
+     * FingerprintSensorType::UNDER_DISPLAY_* would report this value as the distance in pixels,
+     * measured from the top edge of the screen.
+     */
+    int sensorLocationY;
+
+    /**
+     * The radius of the sensor if applicable. For example, sensors of
+     * FingerprintSensorType::UNDER_DISPLAY_* would report this value as the radius of the sensor,
+     * in pixels.
+     */
+    int sensorRadius;
+}
\ No newline at end of file
diff --git a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SensorProps.aidl b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SensorProps.aidl
index afed175..5222f3e 100644
--- a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SensorProps.aidl
+++ b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SensorProps.aidl
@@ -18,6 +18,7 @@
 
 import android.hardware.biometrics.common.CommonProps;
 import android.hardware.biometrics.fingerprint.FingerprintSensorType;
+import android.hardware.biometrics.fingerprint.SensorLocation;
 
 @VintfStability
 parcelable SensorProps {
@@ -32,39 +33,18 @@
     FingerprintSensorType sensorType;
 
     /**
+     * A list of display-specific locations from where the sensor is usable from. See SensorLocation
+     * for more details.
+     */
+    SensorLocation[] sensorLocations;
+
+    /**
      * Must be set to true for sensors that support "swipe" gestures via
      * android.view.KeyEvent#KEYCODE_SYSTEM_NAVIGATION_*.
      */
     boolean supportsNavigationGestures;
 
     /**
-     * The location of the center of the sensor if applicable. For example, sensors of
-     * FingerprintSensorType::UNDER_DISPLAY_* would report this value as the distance in pixels,
-     * measured from the left edge of the screen.
-     */
-    int sensorLocationX;
-
-    /**
-     * The location of the center of the sensor if applicable. For example, sensors of
-     * FingerprintSensorType::UNDER_DISPLAY_* would report this value as the distance in pixels,
-     * measured from the top edge of the screen.
-     */
-    int sensorLocationY;
-
-    /**
-     * The radius of the sensor if applicable. For example, sensors of
-     * FingerprintSensorType::UNDER_DISPLAY_* would report this value as the radius of the sensor,
-     * in pixels.
-     */
-    int sensorRadius;
-
-    /**
-     * For sensors of FingerprintSensorType::UNDER_DISPLAY_*, this must correspond to the
-     * android.hardware.DisplayManager#getDisplay Android API.
-     */
-    int displayId;
-
-    /**
      * Specifies whether or not the implementation supports ISession#detectInteraction.
      */
     boolean supportsDetectInteraction;
diff --git a/biometrics/fingerprint/aidl/default/Android.bp b/biometrics/fingerprint/aidl/default/Android.bp
index c8cb663..24087cf 100644
--- a/biometrics/fingerprint/aidl/default/Android.bp
+++ b/biometrics/fingerprint/aidl/default/Android.bp
@@ -1,18 +1,32 @@
 cc_binary {
     name: "android.hardware.biometrics.fingerprint-service.example",
+    vendor: true,
     relative_install_path: "hw",
     init_rc: ["fingerprint-default.rc"],
     vintf_fragments: ["fingerprint-default.xml"],
-    vendor: true,
+    local_include_dirs: ["include"],
+    srcs: [
+        "main.cpp",
+        "Fingerprint.cpp",
+        "Session.cpp",
+    ],
     shared_libs: [
         "libbase",
         "libbinder_ndk",
         "android.hardware.biometrics.fingerprint-V1-ndk_platform",
         "android.hardware.biometrics.common-V1-ndk_platform",
     ],
+}
+
+cc_test_host {
+    name: "android.hardware.biometrics.fingerprint.WorkerThreadTest",
+    local_include_dirs: ["include"],
     srcs: [
-        "main.cpp",
-        "Fingerprint.cpp",
-        "Session.cpp",
+        "tests/WorkerThreadTest.cpp",
+        "WorkerThread.cpp",
     ],
+    shared_libs: [
+        "libcutils",
+    ],
+    test_suites: ["general-tests"],
 }
diff --git a/biometrics/fingerprint/aidl/default/Fingerprint.cpp b/biometrics/fingerprint/aidl/default/Fingerprint.cpp
index 6eb35d9..fa3171f 100644
--- a/biometrics/fingerprint/aidl/default/Fingerprint.cpp
+++ b/biometrics/fingerprint/aidl/default/Fingerprint.cpp
@@ -18,46 +18,44 @@
 #include "Session.h"
 
 namespace aidl::android::hardware::biometrics::fingerprint {
+namespace {
 
-const int kSensorId = 1;
-const common::SensorStrength kSensorStrength = common::SensorStrength::STRONG;
-const int kMaxEnrollmentsPerUser = 5;
-const FingerprintSensorType kSensorType = FingerprintSensorType::REAR;
-const bool kSupportsNavigationGestures = true;
-const std::string kHwDeviceName = "fingerprintSensor";
-const std::string kHardwareVersion = "vendor/model/revision";
-const std::string kFirmwareVersion = "1.01";
-const std::string kSerialNumber = "00000001";
+constexpr int SENSOR_ID = 1;
+constexpr common::SensorStrength SENSOR_STRENGTH = common::SensorStrength::STRONG;
+constexpr int MAX_ENROLLMENTS_PER_USER = 5;
+constexpr FingerprintSensorType SENSOR_TYPE = FingerprintSensorType::REAR;
+constexpr bool SUPPORTS_NAVIGATION_GESTURES = true;
+constexpr char HW_DEVICE_NAME[] = "fingerprintSensor";
+constexpr char HW_VERSION[] = "vendor/model/revision";
+constexpr char FW_VERSION[] = "1.01";
+constexpr char SERIAL_NUMBER[] = "00000001";
 
-ndk::ScopedAStatus Fingerprint::getSensorProps(std::vector<SensorProps>* return_val) {
-    *return_val = std::vector<SensorProps>();
+}  // namespace
 
-    std::vector<common::HardwareInfo> hardwareInfos = std::vector<common::HardwareInfo>();
-    common::HardwareInfo sensorInfo = {kHwDeviceName,
-            kHardwareVersion,
-            kFirmwareVersion,
-            kSerialNumber
-    };
-    hardwareInfos.push_back(sensorInfo);
-    common::CommonProps commonProps = {kSensorId,
-            kSensorStrength,
-            kMaxEnrollmentsPerUser,
-            hardwareInfos};
-    SensorProps props = {commonProps,
-            kSensorType,
-            kSupportsNavigationGestures,
-            0 /* sensorLocationX */,
-            0 /* sensorLocationY */,
-            0 /* sensorRadius */,
-            0 /* displayId */};
-    return_val->push_back(props);
+Fingerprint::Fingerprint() {}
+
+ndk::ScopedAStatus Fingerprint::getSensorProps(std::vector<SensorProps>* out) {
+    std::vector<common::HardwareInfo> hardwareInfos = {
+            {HW_DEVICE_NAME, HW_VERSION, FW_VERSION, SERIAL_NUMBER}};
+
+    common::CommonProps commonProps = {SENSOR_ID, SENSOR_STRENGTH, MAX_ENROLLMENTS_PER_USER,
+                                       hardwareInfos};
+
+    SensorLocation sensorLocation = {0 /* displayId */, 0 /* sensorLocationX */,
+                                     0 /* sensorLocationY */, 0 /* sensorRadius */};
+
+    *out = {{commonProps,
+             SENSOR_TYPE,
+             {sensorLocation},
+             SUPPORTS_NAVIGATION_GESTURES,
+             false /* supportsDetectInteraction */}};
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Fingerprint::createSession(int32_t /*sensorId*/, int32_t /*userId*/,
                                               const std::shared_ptr<ISessionCallback>& cb,
-                                              std::shared_ptr<ISession>* return_val) {
-    *return_val = SharedRefBase::make<Session>(cb);
+                                              std::shared_ptr<ISession>* out) {
+    *out = SharedRefBase::make<Session>(cb);
     return ndk::ScopedAStatus::ok();
 }
 }  // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/Session.cpp b/biometrics/fingerprint/aidl/default/Session.cpp
index bf08203..52dddb6 100644
--- a/biometrics/fingerprint/aidl/default/Session.cpp
+++ b/biometrics/fingerprint/aidl/default/Session.cpp
@@ -15,6 +15,7 @@
  */
 
 #include <aidl/android/hardware/biometrics/common/BnCancellationSignal.h>
+#include <android-base/logging.h>
 
 #include "Session.h"
 
@@ -25,79 +26,92 @@
     ndk::ScopedAStatus cancel() override { return ndk::ScopedAStatus::ok(); }
 };
 
-Session::Session(std::shared_ptr<ISessionCallback> cb) : cb_(std::move(cb)) {}
+Session::Session(std::shared_ptr<ISessionCallback> cb) : mCb(std::move(cb)) {}
 
 ndk::ScopedAStatus Session::generateChallenge(int32_t /*cookie*/, int32_t /*timeoutSec*/) {
+    LOG(INFO) << "generateChallenge";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::revokeChallenge(int32_t /*cookie*/, int64_t /*challenge*/) {
+    LOG(INFO) << "revokeChallenge";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::enroll(int32_t /*cookie*/, const keymaster::HardwareAuthToken& /*hat*/,
-                                   std::shared_ptr<common::ICancellationSignal>* /*return_val*/) {
+                                   std::shared_ptr<common::ICancellationSignal>* /*out*/) {
+    LOG(INFO) << "enroll";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::authenticate(int32_t /*cookie*/, int64_t /*keystoreOperationId*/,
-                                         std::shared_ptr<common::ICancellationSignal>* return_val) {
-    if (cb_) {
-        cb_->onStateChanged(0, SessionState::AUTHENTICATING);
+                                         std::shared_ptr<common::ICancellationSignal>* out) {
+    LOG(INFO) << "authenticate";
+    if (mCb) {
+        mCb->onStateChanged(0, SessionState::AUTHENTICATING);
     }
-    *return_val = SharedRefBase::make<CancellationSignal>();
+    *out = SharedRefBase::make<CancellationSignal>();
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::detectInteraction(
-        int32_t /*cookie*/, std::shared_ptr<common::ICancellationSignal>* /*return_val*/) {
+        int32_t /*cookie*/, std::shared_ptr<common::ICancellationSignal>* /*out*/) {
+    LOG(INFO) << "detectInteraction";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::enumerateEnrollments(int32_t /*cookie*/) {
-    if (cb_) {
-        cb_->onStateChanged(0, SessionState::ENUMERATING_ENROLLMENTS);
-        cb_->onEnrollmentsEnumerated(std::vector<int32_t>());
+    LOG(INFO) << "enumerateEnrollments";
+    if (mCb) {
+        mCb->onStateChanged(0, SessionState::ENUMERATING_ENROLLMENTS);
+        mCb->onEnrollmentsEnumerated(std::vector<int32_t>());
     }
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::removeEnrollments(int32_t /*cookie*/,
                                               const std::vector<int32_t>& /*enrollmentIds*/) {
-    if (cb_) {
-        cb_->onStateChanged(0, SessionState::REMOVING_ENROLLMENTS);
-        cb_->onEnrollmentsRemoved(std::vector<int32_t>());
+    LOG(INFO) << "removeEnrollments";
+    if (mCb) {
+        mCb->onStateChanged(0, SessionState::REMOVING_ENROLLMENTS);
+        mCb->onEnrollmentsRemoved(std::vector<int32_t>());
     }
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::getAuthenticatorId(int32_t /*cookie*/) {
-    if (cb_) {
-        cb_->onStateChanged(0, SessionState::GETTING_AUTHENTICATOR_ID);
-        cb_->onAuthenticatorIdRetrieved(0 /* authenticatorId */);
+    LOG(INFO) << "getAuthenticatorId";
+    if (mCb) {
+        mCb->onStateChanged(0, SessionState::GETTING_AUTHENTICATOR_ID);
+        mCb->onAuthenticatorIdRetrieved(0 /* authenticatorId */);
     }
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::invalidateAuthenticatorId(int32_t /*cookie*/) {
+    LOG(INFO) << "invalidateAuthenticatorId";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::resetLockout(int32_t /*cookie*/,
                                          const keymaster::HardwareAuthToken& /*hat*/) {
+    LOG(INFO) << "resetLockout";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::onPointerDown(int32_t /*pointerId*/, int32_t /*x*/, int32_t /*y*/,
                                           float /*minor*/, float /*major*/) {
+    LOG(INFO) << "onPointerDown";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::onPointerUp(int32_t /*pointerId*/) {
+    LOG(INFO) << "onPointerUp";
     return ndk::ScopedAStatus::ok();
 }
 
 ndk::ScopedAStatus Session::onUiReady() {
+    LOG(INFO) << "onUiReady";
     return ndk::ScopedAStatus::ok();
 }
 }  // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/WorkerThread.cpp b/biometrics/fingerprint/aidl/default/WorkerThread.cpp
new file mode 100644
index 0000000..512efb8
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/WorkerThread.cpp
@@ -0,0 +1,68 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "WorkerThread.h"
+
+namespace aidl::android::hardware::biometrics::fingerprint {
+
+// It's important that mThread is initialized after everything else because it runs a member
+// function that may use any member of this class.
+WorkerThread::WorkerThread(size_t maxQueueSize)
+    : mMaxSize(maxQueueSize),
+      mIsDestructing(false),
+      mQueue(),
+      mQueueMutex(),
+      mQueueCond(),
+      mThread(&WorkerThread::threadFunc, this) {}
+
+WorkerThread::~WorkerThread() {
+    // This is a signal for threadFunc to terminate as soon as possible, and a hint for schedule
+    // that it doesn't need to do any work.
+    mIsDestructing = true;
+    mQueueCond.notify_all();
+    mThread.join();
+}
+
+bool WorkerThread::schedule(Task&& task) {
+    if (mIsDestructing) {
+        return false;
+    }
+
+    std::unique_lock<std::mutex> lock(mQueueMutex);
+    if (mQueue.size() >= mMaxSize) {
+        return false;
+    }
+    mQueue.push_back(std::move(task));
+    lock.unlock();
+    mQueueCond.notify_one();
+    return true;
+}
+
+void WorkerThread::threadFunc() {
+    while (!mIsDestructing) {
+        std::unique_lock<std::mutex> lock(mQueueMutex);
+        mQueueCond.wait(lock, [this] { return !mQueue.empty() || mIsDestructing; });
+        if (mIsDestructing) {
+            return;
+        }
+        Task task = std::move(mQueue.front());
+        mQueue.pop_front();
+        lock.unlock();
+        task();
+    }
+}
+
+}  // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/Fingerprint.h b/biometrics/fingerprint/aidl/default/include/Fingerprint.h
similarity index 91%
rename from biometrics/fingerprint/aidl/default/Fingerprint.h
rename to biometrics/fingerprint/aidl/default/include/Fingerprint.h
index 4e952ba..867e5fa 100644
--- a/biometrics/fingerprint/aidl/default/Fingerprint.h
+++ b/biometrics/fingerprint/aidl/default/include/Fingerprint.h
@@ -20,13 +20,15 @@
 
 namespace aidl::android::hardware::biometrics::fingerprint {
 
-class Fingerprint : public BnFingerprint {
+class Fingerprint final : public BnFingerprint {
   public:
-    ndk::ScopedAStatus getSensorProps(std::vector<SensorProps>* _aidl_return) override;
+    Fingerprint();
+
+    ndk::ScopedAStatus getSensorProps(std::vector<SensorProps>* out) override;
 
     ndk::ScopedAStatus createSession(int32_t sensorId, int32_t userId,
                                      const std::shared_ptr<ISessionCallback>& cb,
-                                     std::shared_ptr<ISession>* _aidl_return) override;
+                                     std::shared_ptr<ISession>* out) override;
 };
 
 }  // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/Session.h b/biometrics/fingerprint/aidl/default/include/Session.h
similarity index 89%
rename from biometrics/fingerprint/aidl/default/Session.h
rename to biometrics/fingerprint/aidl/default/include/Session.h
index ed3ae3f..b9befef 100644
--- a/biometrics/fingerprint/aidl/default/Session.h
+++ b/biometrics/fingerprint/aidl/default/include/Session.h
@@ -33,14 +33,13 @@
     ndk::ScopedAStatus revokeChallenge(int32_t cookie, int64_t challenge) override;
 
     ndk::ScopedAStatus enroll(int32_t cookie, const keymaster::HardwareAuthToken& hat,
-                              std::shared_ptr<common::ICancellationSignal>* return_val) override;
+                              std::shared_ptr<common::ICancellationSignal>* out) override;
 
-    ndk::ScopedAStatus authenticate(
-            int32_t cookie, int64_t keystoreOperationId,
-            std::shared_ptr<common::ICancellationSignal>* return_val) override;
+    ndk::ScopedAStatus authenticate(int32_t cookie, int64_t keystoreOperationId,
+                                    std::shared_ptr<common::ICancellationSignal>* out) override;
 
     ndk::ScopedAStatus detectInteraction(
-            int32_t cookie, std::shared_ptr<common::ICancellationSignal>* return_val) override;
+            int32_t cookie, std::shared_ptr<common::ICancellationSignal>* out) override;
 
     ndk::ScopedAStatus enumerateEnrollments(int32_t cookie) override;
 
@@ -62,7 +61,7 @@
     ndk::ScopedAStatus onUiReady() override;
 
   private:
-    std::shared_ptr<ISessionCallback> cb_;
+    std::shared_ptr<ISessionCallback> mCb;
 };
 
 }  // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/include/WorkerThread.h b/biometrics/fingerprint/aidl/default/include/WorkerThread.h
new file mode 100644
index 0000000..49104c8
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/include/WorkerThread.h
@@ -0,0 +1,74 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include <mutex>
+#include <optional>
+#include <queue>
+#include <thread>
+
+namespace aidl::android::hardware::biometrics::fingerprint {
+
+using Task = std::function<void()>;
+
+// A class that encapsulates a worker thread and a task queue, and provides a convenient interface
+// for a Session to schedule its tasks for asynchronous execution.
+class WorkerThread final {
+  public:
+    // Internally creates a queue that cannot exceed maxQueueSize elements and a new thread that
+    // polls the queue for tasks until this instance is destructed.
+    explicit WorkerThread(size_t maxQueueSize);
+
+    // Unblocks the internal queue and calls join on the internal thread allowing it to gracefully
+    // exit.
+    ~WorkerThread();
+
+    // Disallow copying this class.
+    WorkerThread(const WorkerThread&) = delete;
+    WorkerThread& operator=(const WorkerThread&) = delete;
+
+    // Also disable moving this class to simplify implementation.
+    WorkerThread(WorkerThread&&) = delete;
+    WorkerThread& operator=(WorkerThread&&) = delete;
+
+    // If the internal queue is not full, pushes a task at the end of the queue and returns true.
+    // Otherwise, returns false. If the queue is busy, blocks until it becomes available.
+    bool schedule(Task&& task);
+
+  private:
+    // The function that runs on the internal thread. Sequentially runs the available tasks from
+    // the queue. If the queue is empty, waits until a new task is added. If the worker is being
+    // destructed, finishes its current task and gracefully exits.
+    void threadFunc();
+
+    // The maximum size that the queue is allowed to expand to.
+    size_t mMaxSize;
+
+    // Whether the destructor was called. If true, tells threadFunc to exit as soon as possible, and
+    // tells schedule to avoid doing any work.
+    std::atomic<bool> mIsDestructing;
+
+    // Queue that's guarded by mQueueMutex and mQueueCond.
+    std::deque<Task> mQueue;
+    std::mutex mQueueMutex;
+    std::condition_variable mQueueCond;
+
+    // The internal thread that works on the tasks from the queue.
+    std::thread mThread;
+};
+
+}  // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/tests/WorkerThreadTest.cpp b/biometrics/fingerprint/aidl/default/tests/WorkerThreadTest.cpp
new file mode 100644
index 0000000..ba901ad
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/tests/WorkerThreadTest.cpp
@@ -0,0 +1,105 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <algorithm>
+#include <chrono>
+#include <future>
+#include <thread>
+
+#include <gtest/gtest.h>
+
+#include "WorkerThread.h"
+
+namespace {
+
+using aidl::android::hardware::biometrics::fingerprint::WorkerThread;
+using namespace std::chrono_literals;
+
+TEST(WorkerThreadTest, ScheduleReturnsTrueWhenQueueHasSpace) {
+    WorkerThread worker(1 /*maxQueueSize*/);
+    for (int i = 0; i < 100; ++i) {
+        EXPECT_TRUE(worker.schedule([] {}));
+        // Allow enough time for the previous task to be processed.
+        std::this_thread::sleep_for(2ms);
+    }
+}
+
+TEST(WorkerThreadTest, ScheduleReturnsFalseWhenQueueIsFull) {
+    WorkerThread worker(2 /*maxQueueSize*/);
+    // Add a long-running task.
+    worker.schedule([] { std::this_thread::sleep_for(1s); });
+
+    // Allow enough time for the worker to start working on the previous task.
+    std::this_thread::sleep_for(2ms);
+
+    // Fill the worker's queue to the maximum.
+    worker.schedule([] {});
+    worker.schedule([] {});
+
+    EXPECT_FALSE(worker.schedule([] {}));
+}
+
+TEST(WorkerThreadTest, TasksExecuteInOrder) {
+    constexpr int NUM_TASKS = 10000;
+    WorkerThread worker(NUM_TASKS);
+
+    std::vector<int> results;
+    for (int i = 0; i < NUM_TASKS; ++i) {
+        worker.schedule([&results, i] {
+            // Delay tasks differently to provoke races.
+            std::this_thread::sleep_for(std::chrono::nanoseconds(100 - i % 100));
+            // Unguarded write to results to provoke races.
+            results.push_back(i);
+        });
+    }
+
+    std::promise<void> promise;
+    auto future = promise.get_future();
+
+    // Schedule a special task to signal when all of the tasks are finished.
+    worker.schedule([&promise] { promise.set_value(); });
+    auto status = future.wait_for(1s);
+    ASSERT_EQ(status, std::future_status::ready);
+
+    ASSERT_EQ(results.size(), NUM_TASKS);
+    EXPECT_TRUE(std::is_sorted(results.begin(), results.end()));
+}
+
+TEST(WorkerThreadTest, ExecutionStopsAfterWorkerIsDestroyed) {
+    std::promise<void> promise1;
+    std::promise<void> promise2;
+    auto future1 = promise1.get_future();
+    auto future2 = promise2.get_future();
+
+    {
+        WorkerThread worker(2 /*maxQueueSize*/);
+        worker.schedule([&promise1] {
+            promise1.set_value();
+            std::this_thread::sleep_for(200ms);
+        });
+        worker.schedule([&promise2] { promise2.set_value(); });
+
+        // Make sure the first task is executing.
+        auto status1 = future1.wait_for(1s);
+        ASSERT_EQ(status1, std::future_status::ready);
+    }
+
+    // The second task should never execute.
+    auto status2 = future2.wait_for(1s);
+    EXPECT_EQ(status2, std::future_status::timeout);
+}
+
+}  // namespace
diff --git a/bluetooth/audio/2.0/default/Android.bp b/bluetooth/audio/2.0/default/Android.bp
index 0db0028..8ed631e 100644
--- a/bluetooth/audio/2.0/default/Android.bp
+++ b/bluetooth/audio/2.0/default/Android.bp
@@ -23,24 +23,3 @@
         "libutils",
     ],
 }
-
-cc_library_shared {
-    name: "libbluetooth_audio_session",
-    defaults: ["hidl_defaults"],
-    vendor: true,
-    srcs: [
-        "session/BluetoothAudioSession.cpp",
-        "session/BluetoothAudioSupportedCodecsDB.cpp",
-    ],
-    export_include_dirs: ["session/"],
-    header_libs: ["libhardware_headers"],
-    shared_libs: [
-        "android.hardware.bluetooth.audio@2.0",
-        "libbase",
-        "libcutils",
-        "libfmq",
-        "libhidlbase",
-        "liblog",
-        "libutils",
-    ],
-}
diff --git a/bluetooth/audio/2.1/default/A2dpOffloadAudioProvider.cpp b/bluetooth/audio/2.1/default/A2dpOffloadAudioProvider.cpp
index b4a61b6..3fe1a4d 100644
--- a/bluetooth/audio/2.1/default/A2dpOffloadAudioProvider.cpp
+++ b/bluetooth/audio/2.1/default/A2dpOffloadAudioProvider.cpp
@@ -22,8 +22,8 @@
 #include <fmq/MessageQueue.h>
 #include <hidl/MQDescriptor.h>
 
-#include "BluetoothAudioSessionReport.h"
-#include "BluetoothAudioSupportedCodecsDB.h"
+#include "BluetoothAudioSessionReport_2_1.h"
+#include "BluetoothAudioSupportedCodecsDB_2_1.h"
 
 namespace android {
 namespace hardware {
@@ -32,7 +32,7 @@
 namespace V2_1 {
 namespace implementation {
 
-using ::android::bluetooth::audio::BluetoothAudioSessionReport;
+using ::android::bluetooth::audio::BluetoothAudioSessionReport_2_1;
 using ::android::hardware::kSynchronizedReadWrite;
 using ::android::hardware::MessageQueue;
 using ::android::hardware::Void;
@@ -81,8 +81,8 @@
 
 Return<void> A2dpOffloadAudioProvider::onSessionReady(
     startSession_cb _hidl_cb) {
-  BluetoothAudioSessionReport::OnSessionStarted(session_type_, stack_iface_,
-                                                nullptr, audio_config_);
+  BluetoothAudioSessionReport_2_1::OnSessionStarted(session_type_, stack_iface_,
+                                                    nullptr, audio_config_);
   _hidl_cb(BluetoothAudioStatus::SUCCESS, DataMQ::Descriptor());
   return Void();
 }
diff --git a/bluetooth/audio/2.1/default/A2dpSoftwareAudioProvider.cpp b/bluetooth/audio/2.1/default/A2dpSoftwareAudioProvider.cpp
index a67c341..a37176b 100644
--- a/bluetooth/audio/2.1/default/A2dpSoftwareAudioProvider.cpp
+++ b/bluetooth/audio/2.1/default/A2dpSoftwareAudioProvider.cpp
@@ -20,8 +20,8 @@
 
 #include <android-base/logging.h>
 
-#include "BluetoothAudioSessionReport.h"
-#include "BluetoothAudioSupportedCodecsDB.h"
+#include "BluetoothAudioSessionReport_2_1.h"
+#include "BluetoothAudioSupportedCodecsDB_2_1.h"
 
 namespace android {
 namespace hardware {
@@ -30,7 +30,7 @@
 namespace V2_1 {
 namespace implementation {
 
-using ::android::bluetooth::audio::BluetoothAudioSessionReport;
+using ::android::bluetooth::audio::BluetoothAudioSessionReport_2_1;
 using ::android::hardware::Void;
 using ::android::hardware::bluetooth::audio::V2_0::AudioConfiguration;
 
@@ -96,7 +96,7 @@
 Return<void> A2dpSoftwareAudioProvider::onSessionReady(
     startSession_cb _hidl_cb) {
   if (mDataMQ && mDataMQ->isValid()) {
-    BluetoothAudioSessionReport::OnSessionStarted(
+    BluetoothAudioSessionReport_2_1::OnSessionStarted(
         session_type_, stack_iface_, mDataMQ->getDesc(), audio_config_);
     _hidl_cb(BluetoothAudioStatus::SUCCESS, *mDataMQ->getDesc());
   } else {
diff --git a/bluetooth/audio/2.1/default/Android.bp b/bluetooth/audio/2.1/default/Android.bp
index 5381fec..c05aa3f 100644
--- a/bluetooth/audio/2.1/default/Android.bp
+++ b/bluetooth/audio/2.1/default/Android.bp
@@ -16,29 +16,7 @@
         "android.hardware.bluetooth.audio@2.0",
         "android.hardware.bluetooth.audio@2.1",
         "libbase",
-        "libbluetooth_audio_session_2_1",
-        "libcutils",
-        "libfmq",
-        "libhidlbase",
-        "liblog",
-        "libutils",
-    ],
-}
-
-cc_library_shared {
-    name: "libbluetooth_audio_session_2_1",
-    defaults: ["hidl_defaults"],
-    vendor: true,
-    srcs: [
-        "session/BluetoothAudioSession.cpp",
-        "session/BluetoothAudioSupportedCodecsDB.cpp",
-    ],
-    export_include_dirs: ["session/"],
-    header_libs: ["libhardware_headers"],
-    shared_libs: [
-        "android.hardware.bluetooth.audio@2.0",
-        "android.hardware.bluetooth.audio@2.1",
-        "libbase",
+        "libbluetooth_audio_session",
         "libcutils",
         "libfmq",
         "libhidlbase",
diff --git a/bluetooth/audio/2.1/default/BluetoothAudioProvider.cpp b/bluetooth/audio/2.1/default/BluetoothAudioProvider.cpp
index 73fe06c..38889ae 100644
--- a/bluetooth/audio/2.1/default/BluetoothAudioProvider.cpp
+++ b/bluetooth/audio/2.1/default/BluetoothAudioProvider.cpp
@@ -20,8 +20,8 @@
 
 #include <android-base/logging.h>
 
-#include "BluetoothAudioSessionReport.h"
-#include "BluetoothAudioSupportedCodecsDB.h"
+#include "BluetoothAudioSessionReport_2_1.h"
+#include "BluetoothAudioSupportedCodecsDB_2_1.h"
 
 namespace android {
 namespace hardware {
@@ -30,7 +30,7 @@
 namespace V2_1 {
 namespace implementation {
 
-using ::android::bluetooth::audio::BluetoothAudioSessionReport;
+using ::android::bluetooth::audio::BluetoothAudioSessionReport_2_1;
 using ::android::hardware::kSynchronizedReadWrite;
 using ::android::hardware::MessageQueue;
 using ::android::hardware::Void;
@@ -105,8 +105,8 @@
    * HAL server should start the streaming on data path.
    */
   if (stack_iface_) {
-    BluetoothAudioSessionReport::ReportControlStatus(session_type_, true,
-                                                     status);
+    BluetoothAudioSessionReport_2_1::ReportControlStatus(session_type_, true,
+                                                         status);
   } else {
     LOG(WARNING) << __func__ << " - SessionType=" << toString(session_type_)
                  << ", status=" << toString(status) << " has NO session";
@@ -125,8 +125,8 @@
    * HAL server should suspend the streaming on data path.
    */
   if (stack_iface_) {
-    BluetoothAudioSessionReport::ReportControlStatus(session_type_, false,
-                                                     status);
+    BluetoothAudioSessionReport_2_1::ReportControlStatus(session_type_, false,
+                                                         status);
   } else {
     LOG(WARNING) << __func__ << " - SessionType=" << toString(session_type_)
                  << ", status=" << toString(status) << " has NO session";
@@ -139,7 +139,7 @@
   LOG(INFO) << __func__ << " - SessionType=" << toString(session_type_);
 
   if (stack_iface_) {
-    BluetoothAudioSessionReport::OnSessionEnded(session_type_);
+    BluetoothAudioSessionReport_2_1::OnSessionEnded(session_type_);
     stack_iface_->unlinkToDeath(death_recipient_);
   } else {
     LOG(INFO) << __func__ << " - SessionType=" << toString(session_type_)
diff --git a/bluetooth/audio/2.1/default/BluetoothAudioProvidersFactory.cpp b/bluetooth/audio/2.1/default/BluetoothAudioProvidersFactory.cpp
index adf2717..e1b1ac6 100644
--- a/bluetooth/audio/2.1/default/BluetoothAudioProvidersFactory.cpp
+++ b/bluetooth/audio/2.1/default/BluetoothAudioProvidersFactory.cpp
@@ -20,7 +20,7 @@
 
 #include <android-base/logging.h>
 
-#include "BluetoothAudioSupportedCodecsDB.h"
+#include "BluetoothAudioSupportedCodecsDB_2_1.h"
 
 namespace android {
 namespace hardware {
diff --git a/bluetooth/audio/2.1/default/HearingAidAudioProvider.cpp b/bluetooth/audio/2.1/default/HearingAidAudioProvider.cpp
index aded7e1..712bd4f 100644
--- a/bluetooth/audio/2.1/default/HearingAidAudioProvider.cpp
+++ b/bluetooth/audio/2.1/default/HearingAidAudioProvider.cpp
@@ -20,8 +20,8 @@
 
 #include <android-base/logging.h>
 
-#include "BluetoothAudioSessionReport.h"
-#include "BluetoothAudioSupportedCodecsDB.h"
+#include "BluetoothAudioSessionReport_2_1.h"
+#include "BluetoothAudioSupportedCodecsDB_2_1.h"
 
 namespace android {
 namespace hardware {
@@ -30,7 +30,7 @@
 namespace V2_1 {
 namespace implementation {
 
-using ::android::bluetooth::audio::BluetoothAudioSessionReport;
+using ::android::bluetooth::audio::BluetoothAudioSessionReport_2_1;
 using ::android::hardware::Void;
 using ::android::hardware::bluetooth::audio::V2_0::AudioConfiguration;
 
@@ -95,7 +95,7 @@
 
 Return<void> HearingAidAudioProvider::onSessionReady(startSession_cb _hidl_cb) {
   if (mDataMQ && mDataMQ->isValid()) {
-    BluetoothAudioSessionReport::OnSessionStarted(
+    BluetoothAudioSessionReport_2_1::OnSessionStarted(
         session_type_, stack_iface_, mDataMQ->getDesc(), audio_config_);
     _hidl_cb(BluetoothAudioStatus::SUCCESS, *mDataMQ->getDesc());
   } else {
diff --git a/bluetooth/audio/2.1/default/LeAudioAudioProvider.cpp b/bluetooth/audio/2.1/default/LeAudioAudioProvider.cpp
index 9c2b4fe..2ebf6c5 100644
--- a/bluetooth/audio/2.1/default/LeAudioAudioProvider.cpp
+++ b/bluetooth/audio/2.1/default/LeAudioAudioProvider.cpp
@@ -21,8 +21,8 @@
 
 #include <android-base/logging.h>
 
-#include "BluetoothAudioSessionReport.h"
-#include "BluetoothAudioSupportedCodecsDB.h"
+#include "BluetoothAudioSessionReport_2_1.h"
+#include "BluetoothAudioSupportedCodecsDB_2_1.h"
 
 namespace android {
 namespace hardware {
@@ -31,7 +31,7 @@
 namespace V2_1 {
 namespace implementation {
 
-using ::android::bluetooth::audio::BluetoothAudioSessionReport;
+using ::android::bluetooth::audio::BluetoothAudioSessionReport_2_1;
 using ::android::hardware::Void;
 using ::android::hardware::bluetooth::audio::V2_0::BitsPerSample;
 using ::android::hardware::bluetooth::audio::V2_0::ChannelMode;
@@ -179,7 +179,7 @@
 
 Return<void> LeAudioAudioProvider::onSessionReady(startSession_cb _hidl_cb) {
   if (mDataMQ && mDataMQ->isValid()) {
-    BluetoothAudioSessionReport::OnSessionStarted(
+    BluetoothAudioSessionReport_2_1::OnSessionStarted(
         session_type_, stack_iface_, mDataMQ->getDesc(), audio_config_);
     _hidl_cb(BluetoothAudioStatus::SUCCESS, *mDataMQ->getDesc());
   } else {
diff --git a/bluetooth/audio/2.1/default/session/BluetoothAudioSession.cpp b/bluetooth/audio/2.1/default/session/BluetoothAudioSession.cpp
deleted file mode 100644
index ea2c54a..0000000
--- a/bluetooth/audio/2.1/default/session/BluetoothAudioSession.cpp
+++ /dev/null
@@ -1,467 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#define LOG_TAG "BTAudioProviderSession"
-
-#include "BluetoothAudioSession.h"
-
-#include <android-base/logging.h>
-#include <android-base/stringprintf.h>
-
-namespace android {
-namespace bluetooth {
-namespace audio {
-
-using ::android::hardware::audio::common::V5_0::AudioContentType;
-using ::android::hardware::audio::common::V5_0::AudioUsage;
-using ::android::hardware::audio::common::V5_0::PlaybackTrackMetadata;
-using ::android::hardware::audio::common::V5_0::SourceMetadata;
-using ::android::hardware::bluetooth::audio::V2_0::CodecType;
-using ::android::hardware::bluetooth::audio::V2_0::TimeSpec;
-
-const CodecConfiguration BluetoothAudioSession::kInvalidCodecConfiguration = {
-    .codecType = CodecType::UNKNOWN,
-    .encodedAudioBitrate = 0x00000000,
-    .peerMtu = 0xffff,
-    .isScmstEnabled = false,
-    .config = {}};
-AudioConfiguration BluetoothAudioSession::invalidSoftwareAudioConfiguration =
-    {};
-AudioConfiguration BluetoothAudioSession::invalidOffloadAudioConfiguration = {};
-
-static constexpr int kFmqSendTimeoutMs = 1000;  // 1000 ms timeout for sending
-static constexpr int kFmqReceiveTimeoutMs =
-    1000;                               // 1000 ms timeout for receiving
-static constexpr int kWritePollMs = 1;  // polled non-blocking interval
-static constexpr int kReadPollMs = 1;   // polled non-blocking interval
-
-static inline timespec timespec_convert_from_hal(const TimeSpec& TS) {
-  return {.tv_sec = static_cast<long>(TS.tvSec),
-          .tv_nsec = static_cast<long>(TS.tvNSec)};
-}
-
-BluetoothAudioSession::BluetoothAudioSession(const SessionType& session_type)
-    : session_type_(session_type), stack_iface_(nullptr), mDataMQ(nullptr) {
-  invalidSoftwareAudioConfiguration.pcmConfig(kInvalidPcmParameters);
-  invalidOffloadAudioConfiguration.codecConfig(kInvalidCodecConfiguration);
-}
-
-// The report function is used to report that the Bluetooth stack has started
-// this session without any failure, and will invoke session_changed_cb_ to
-// notify those registered bluetooth_audio outputs
-void BluetoothAudioSession::OnSessionStarted(
-    const sp<IBluetoothAudioPort> stack_iface, const DataMQ::Descriptor* dataMQ,
-    const AudioConfiguration& audio_config) {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (stack_iface == nullptr) {
-    LOG(ERROR) << __func__ << " - SessionType=" << toString(session_type_)
-               << ", IBluetoothAudioPort Invalid";
-  } else if (!UpdateAudioConfig(audio_config)) {
-    LOG(ERROR) << __func__ << " - SessionType=" << toString(session_type_)
-               << ", AudioConfiguration=" << toString(audio_config)
-               << " Invalid";
-  } else if (!UpdateDataPath(dataMQ)) {
-    LOG(ERROR) << __func__ << " - SessionType=" << toString(session_type_)
-               << " DataMQ Invalid";
-    audio_config_ =
-        (session_type_ == SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH
-             ? kInvalidOffloadAudioConfiguration
-             : kInvalidSoftwareAudioConfiguration);
-  } else {
-    stack_iface_ = stack_iface;
-    LOG(INFO) << __func__ << " - SessionType=" << toString(session_type_)
-              << ", AudioConfiguration=" << toString(audio_config);
-    ReportSessionStatus();
-  }
-}
-
-// The report function is used to report that the Bluetooth stack has ended the
-// session, and will invoke session_changed_cb_ to notify registered
-// bluetooth_audio outputs
-void BluetoothAudioSession::OnSessionEnded() {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  bool toggled = IsSessionReady();
-  LOG(INFO) << __func__ << " - SessionType=" << toString(session_type_);
-  audio_config_ = (session_type_ == SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH
-                       ? kInvalidOffloadAudioConfiguration
-                       : kInvalidSoftwareAudioConfiguration);
-  stack_iface_ = nullptr;
-  UpdateDataPath(nullptr);
-  if (toggled) {
-    ReportSessionStatus();
-  }
-}
-
-// invoking the registered session_changed_cb_
-void BluetoothAudioSession::ReportSessionStatus() {
-  // This is locked already by OnSessionStarted / OnSessionEnded
-  if (observers_.empty()) {
-    LOG(INFO) << __func__ << " - SessionType=" << toString(session_type_)
-              << " has NO port state observer";
-    return;
-  }
-  for (auto& observer : observers_) {
-    uint16_t cookie = observer.first;
-    std::shared_ptr<struct PortStatusCallbacks> cb = observer.second;
-    LOG(INFO) << __func__ << " - SessionType=" << toString(session_type_)
-              << " notify to bluetooth_audio=0x"
-              << android::base::StringPrintf("%04x", cookie);
-    cb->session_changed_cb_(cookie);
-  }
-}
-
-// The report function is used to report that the Bluetooth stack has notified
-// the result of startStream or suspendStream, and will invoke
-// control_result_cb_ to notify registered bluetooth_audio outputs
-void BluetoothAudioSession::ReportControlStatus(
-    bool start_resp, const BluetoothAudioStatus& status) {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (observers_.empty()) {
-    LOG(WARNING) << __func__ << " - SessionType=" << toString(session_type_)
-                 << " has NO port state observer";
-    return;
-  }
-  for (auto& observer : observers_) {
-    uint16_t cookie = observer.first;
-    std::shared_ptr<struct PortStatusCallbacks> cb = observer.second;
-    LOG(INFO) << __func__ << " - status=" << toString(status)
-              << " for SessionType=" << toString(session_type_)
-              << ", bluetooth_audio=0x"
-              << android::base::StringPrintf("%04x", cookie)
-              << (start_resp ? " started" : " suspended");
-    cb->control_result_cb_(cookie, start_resp, status);
-  }
-}
-
-// The function helps to check if this session is ready or not
-// @return: true if the Bluetooth stack has started the specified session
-bool BluetoothAudioSession::IsSessionReady() {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  bool dataMQ_valid =
-      (session_type_ == SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH ||
-       (mDataMQ != nullptr && mDataMQ->isValid()));
-  return stack_iface_ != nullptr && dataMQ_valid;
-}
-
-bool BluetoothAudioSession::UpdateDataPath(const DataMQ::Descriptor* dataMQ) {
-  if (dataMQ == nullptr) {
-    // usecase of reset by nullptr
-    mDataMQ = nullptr;
-    return true;
-  }
-  std::unique_ptr<DataMQ> tempDataMQ;
-  tempDataMQ.reset(new DataMQ(*dataMQ));
-  if (!tempDataMQ || !tempDataMQ->isValid()) {
-    mDataMQ = nullptr;
-    return false;
-  }
-  mDataMQ = std::move(tempDataMQ);
-  return true;
-}
-
-bool BluetoothAudioSession::UpdateAudioConfig(
-    const AudioConfiguration& audio_config) {
-  bool is_software_session =
-      (session_type_ == SessionType::A2DP_SOFTWARE_ENCODING_DATAPATH ||
-       session_type_ == SessionType::HEARING_AID_SOFTWARE_ENCODING_DATAPATH ||
-       session_type_ == SessionType::LE_AUDIO_SOFTWARE_ENCODING_DATAPATH ||
-       session_type_ == SessionType::LE_AUDIO_SOFTWARE_DECODED_DATAPATH);
-  bool is_offload_session =
-      (session_type_ == SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH);
-  auto audio_config_discriminator = audio_config.getDiscriminator();
-  bool is_software_audio_config =
-      (is_software_session &&
-       audio_config_discriminator ==
-           AudioConfiguration::hidl_discriminator::pcmConfig);
-  bool is_offload_audio_config =
-      (is_offload_session &&
-       audio_config_discriminator ==
-           AudioConfiguration::hidl_discriminator::codecConfig);
-  if (!is_software_audio_config && !is_offload_audio_config) {
-    return false;
-  }
-  audio_config_ = audio_config;
-  return true;
-}
-
-// The control function helps the bluetooth_audio module to register
-// PortStatusCallbacks
-// @return: cookie - the assigned number to this bluetooth_audio output
-uint16_t BluetoothAudioSession::RegisterStatusCback(
-    const PortStatusCallbacks& cbacks) {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  uint16_t cookie = ObserversCookieGetInitValue(session_type_);
-  uint16_t cookie_upper_bound = ObserversCookieGetUpperBound(session_type_);
-
-  while (cookie < cookie_upper_bound) {
-    if (observers_.find(cookie) == observers_.end()) {
-      break;
-    }
-    ++cookie;
-  }
-  if (cookie >= cookie_upper_bound) {
-    LOG(ERROR) << __func__ << " - SessionType=" << toString(session_type_)
-               << " has " << observers_.size()
-               << " observers already (No Resource)";
-    return kObserversCookieUndefined;
-  }
-  std::shared_ptr<struct PortStatusCallbacks> cb =
-      std::make_shared<struct PortStatusCallbacks>();
-  *cb = cbacks;
-  observers_[cookie] = cb;
-  return cookie;
-}
-
-// The control function helps the bluetooth_audio module to unregister
-// PortStatusCallbacks
-// @param: cookie - indicates which bluetooth_audio output is
-void BluetoothAudioSession::UnregisterStatusCback(uint16_t cookie) {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (observers_.erase(cookie) != 1) {
-    LOG(WARNING) << __func__ << " - SessionType=" << toString(session_type_)
-                 << " no such provider=0x"
-                 << android::base::StringPrintf("%04x", cookie);
-  }
-}
-
-// The control function is for the bluetooth_audio module to get the current
-// AudioConfiguration
-const AudioConfiguration& BluetoothAudioSession::GetAudioConfig() {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (IsSessionReady()) {
-    return audio_config_;
-  } else if (session_type_ == SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH) {
-    return kInvalidOffloadAudioConfiguration;
-  } else {
-    return kInvalidSoftwareAudioConfiguration;
-  }
-}
-
-// Those control functions are for the bluetooth_audio module to start, suspend,
-// stop stream, to check position, and to update metadata.
-bool BluetoothAudioSession::StartStream() {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (!IsSessionReady()) {
-    LOG(DEBUG) << __func__ << " - SessionType=" << toString(session_type_)
-               << " has NO session";
-    return false;
-  }
-  auto hal_retval = stack_iface_->startStream();
-  if (!hal_retval.isOk()) {
-    LOG(WARNING) << __func__ << " - IBluetoothAudioPort SessionType="
-                 << toString(session_type_) << " failed";
-    return false;
-  }
-  return true;
-}
-
-bool BluetoothAudioSession::SuspendStream() {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (!IsSessionReady()) {
-    LOG(DEBUG) << __func__ << " - SessionType=" << toString(session_type_)
-               << " has NO session";
-    return false;
-  }
-  auto hal_retval = stack_iface_->suspendStream();
-  if (!hal_retval.isOk()) {
-    LOG(WARNING) << __func__ << " - IBluetoothAudioPort SessionType="
-                 << toString(session_type_) << " failed";
-    return false;
-  }
-  return true;
-}
-
-void BluetoothAudioSession::StopStream() {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (!IsSessionReady()) {
-    return;
-  }
-  auto hal_retval = stack_iface_->stopStream();
-  if (!hal_retval.isOk()) {
-    LOG(WARNING) << __func__ << " - IBluetoothAudioPort SessionType="
-                 << toString(session_type_) << " failed";
-  }
-}
-
-bool BluetoothAudioSession::GetPresentationPosition(
-    uint64_t* remote_delay_report_ns, uint64_t* total_bytes_readed,
-    timespec* data_position) {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (!IsSessionReady()) {
-    LOG(DEBUG) << __func__ << " - SessionType=" << toString(session_type_)
-               << " has NO session";
-    return false;
-  }
-  bool retval = false;
-  auto hal_retval = stack_iface_->getPresentationPosition(
-      [&retval, &remote_delay_report_ns, &total_bytes_readed, &data_position](
-          BluetoothAudioStatus status,
-          const uint64_t& remoteDeviceAudioDelayNanos,
-          uint64_t transmittedOctets,
-          const TimeSpec& transmittedOctetsTimeStamp) {
-        if (status == BluetoothAudioStatus::SUCCESS) {
-          if (remote_delay_report_ns)
-            *remote_delay_report_ns = remoteDeviceAudioDelayNanos;
-          if (total_bytes_readed) *total_bytes_readed = transmittedOctets;
-          if (data_position)
-            *data_position =
-                timespec_convert_from_hal(transmittedOctetsTimeStamp);
-          retval = true;
-        }
-      });
-  if (!hal_retval.isOk()) {
-    LOG(WARNING) << __func__ << " - IBluetoothAudioPort SessionType="
-                 << toString(session_type_) << " failed";
-    return false;
-  }
-  return retval;
-}
-
-void BluetoothAudioSession::UpdateTracksMetadata(
-    const struct source_metadata* source_metadata) {
-  std::lock_guard<std::recursive_mutex> guard(mutex_);
-  if (!IsSessionReady()) {
-    LOG(DEBUG) << __func__ << " - SessionType=" << toString(session_type_)
-               << " has NO session";
-    return;
-  }
-
-  ssize_t track_count = source_metadata->track_count;
-  LOG(INFO) << __func__ << " - SessionType=" << toString(session_type_) << ", "
-            << track_count << " track(s)";
-  if (session_type_ == SessionType::A2DP_SOFTWARE_ENCODING_DATAPATH ||
-      session_type_ == SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH) {
-    return;
-  }
-
-  struct playback_track_metadata* track = source_metadata->tracks;
-  SourceMetadata sourceMetadata;
-  PlaybackTrackMetadata* halMetadata;
-
-  sourceMetadata.tracks.resize(track_count);
-  halMetadata = sourceMetadata.tracks.data();
-  while (track_count && track) {
-    halMetadata->usage = static_cast<AudioUsage>(track->usage);
-    halMetadata->contentType =
-        static_cast<AudioContentType>(track->content_type);
-    halMetadata->gain = track->gain;
-    LOG(VERBOSE) << __func__ << " - SessionType=" << toString(session_type_)
-                 << ", usage=" << toString(halMetadata->usage)
-                 << ", content=" << toString(halMetadata->contentType)
-                 << ", gain=" << halMetadata->gain;
-    --track_count;
-    ++track;
-    ++halMetadata;
-  }
-  auto hal_retval = stack_iface_->updateMetadata(sourceMetadata);
-  if (!hal_retval.isOk()) {
-    LOG(WARNING) << __func__ << " - IBluetoothAudioPort SessionType="
-                 << toString(session_type_) << " failed";
-  }
-}
-
-// The control function writes stream to FMQ
-size_t BluetoothAudioSession::OutWritePcmData(const void* buffer,
-                                              size_t bytes) {
-  if (buffer == nullptr || !bytes) return 0;
-  size_t totalWritten = 0;
-  int ms_timeout = kFmqSendTimeoutMs;
-  do {
-    std::unique_lock<std::recursive_mutex> lock(mutex_);
-    if (!IsSessionReady()) break;
-    size_t availableToWrite = mDataMQ->availableToWrite();
-    if (availableToWrite) {
-      if (availableToWrite > (bytes - totalWritten)) {
-        availableToWrite = bytes - totalWritten;
-      }
-
-      if (!mDataMQ->write(static_cast<const uint8_t*>(buffer) + totalWritten,
-                          availableToWrite)) {
-        ALOGE("FMQ datapath writing %zu/%zu failed", totalWritten, bytes);
-        return totalWritten;
-      }
-      totalWritten += availableToWrite;
-    } else if (ms_timeout >= kWritePollMs) {
-      lock.unlock();
-      usleep(kWritePollMs * 1000);
-      ms_timeout -= kWritePollMs;
-    } else {
-      ALOGD("out data %zu/%zu overflow %d ms", totalWritten, bytes,
-            (kFmqSendTimeoutMs - ms_timeout));
-      return totalWritten;
-    }
-  } while (totalWritten < bytes);
-  return totalWritten;
-}
-
-// The control function reads stream from FMQ
-size_t BluetoothAudioSession::InReadPcmData(void* buffer, size_t bytes) {
-  if (buffer == nullptr || !bytes) return 0;
-  size_t totalRead = 0;
-  int ms_timeout = kFmqReceiveTimeoutMs;
-  do {
-    std::unique_lock<std::recursive_mutex> lock(mutex_);
-    if (!IsSessionReady()) break;
-    size_t availableToRead = mDataMQ->availableToRead();
-    if (availableToRead) {
-      if (availableToRead > (bytes - totalRead)) {
-        availableToRead = bytes - totalRead;
-      }
-      if (!mDataMQ->read(static_cast<uint8_t*>(buffer) + totalRead,
-                         availableToRead)) {
-        ALOGE("FMQ datapath reading %zu/%zu failed", totalRead, bytes);
-        return totalRead;
-      }
-      totalRead += availableToRead;
-    } else if (ms_timeout >= kReadPollMs) {
-      lock.unlock();
-      usleep(kReadPollMs * 1000);
-      ms_timeout -= kReadPollMs;
-      continue;
-    } else {
-      ALOGD("in data %zu/%zu overflow %d ms", totalRead, bytes,
-            (kFmqReceiveTimeoutMs - ms_timeout));
-      return totalRead;
-    }
-  } while (totalRead < bytes);
-  return totalRead;
-}
-
-std::unique_ptr<BluetoothAudioSessionInstance>
-    BluetoothAudioSessionInstance::instance_ptr =
-        std::unique_ptr<BluetoothAudioSessionInstance>(
-            new BluetoothAudioSessionInstance());
-
-// API to fetch the session
-std::shared_ptr<BluetoothAudioSession>
-BluetoothAudioSessionInstance::GetSessionInstance(
-    const SessionType& session_type) {
-  std::lock_guard<std::mutex> guard(instance_ptr->mutex_);
-  if (!instance_ptr->sessions_map_.empty()) {
-    auto entry = instance_ptr->sessions_map_.find(session_type);
-    if (entry != instance_ptr->sessions_map_.end()) {
-      return entry->second;
-    }
-  }
-  std::shared_ptr<BluetoothAudioSession> session_ptr =
-      std::make_shared<BluetoothAudioSession>(session_type);
-  instance_ptr->sessions_map_[session_type] = session_ptr;
-  return session_ptr;
-}
-
-}  // namespace audio
-}  // namespace bluetooth
-}  // namespace android
diff --git a/bluetooth/audio/2.1/default/session/BluetoothAudioSession.h b/bluetooth/audio/2.1/default/session/BluetoothAudioSession.h
deleted file mode 100644
index 7bc12e6..0000000
--- a/bluetooth/audio/2.1/default/session/BluetoothAudioSession.h
+++ /dev/null
@@ -1,190 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#pragma once
-
-#include <mutex>
-#include <unordered_map>
-
-#include <android/hardware/bluetooth/audio/2.0/IBluetoothAudioPort.h>
-#include <android/hardware/bluetooth/audio/2.1/types.h>
-#include <fmq/MessageQueue.h>
-#include <hardware/audio.h>
-#include <hidl/MQDescriptor.h>
-
-namespace android {
-namespace bluetooth {
-namespace audio {
-
-using ::android::sp;
-using ::android::hardware::kSynchronizedReadWrite;
-using ::android::hardware::MessageQueue;
-using ::android::hardware::bluetooth::audio::V2_0::BitsPerSample;
-using ::android::hardware::bluetooth::audio::V2_0::ChannelMode;
-using ::android::hardware::bluetooth::audio::V2_0::CodecConfiguration;
-using ::android::hardware::bluetooth::audio::V2_0::IBluetoothAudioPort;
-using ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration;
-using ::android::hardware::bluetooth::audio::V2_1::PcmParameters;
-using ::android::hardware::bluetooth::audio::V2_1::SampleRate;
-using ::android::hardware::bluetooth::audio::V2_1::SessionType;
-
-using BluetoothAudioStatus =
-    ::android::hardware::bluetooth::audio::V2_0::Status;
-
-using DataMQ = MessageQueue<uint8_t, kSynchronizedReadWrite>;
-
-static constexpr uint16_t kObserversCookieSize = 0x0010;  // 0x0000 ~ 0x000f
-constexpr uint16_t kObserversCookieUndefined =
-    (static_cast<uint16_t>(SessionType::UNKNOWN) << 8 & 0xff00);
-inline SessionType ObserversCookieGetSessionType(uint16_t cookie) {
-  return static_cast<SessionType>(cookie >> 8 & 0x00ff);
-}
-inline uint16_t ObserversCookieGetInitValue(SessionType session_type) {
-  return (static_cast<uint16_t>(session_type) << 8 & 0xff00);
-}
-inline uint16_t ObserversCookieGetUpperBound(SessionType session_type) {
-  return (static_cast<uint16_t>(session_type) << 8 & 0xff00) +
-         kObserversCookieSize;
-}
-
-// This presents the callbacks of started / suspended and session changed,
-// and the bluetooth_audio module uses to receive the status notification
-struct PortStatusCallbacks {
-  // control_result_cb_ - when the Bluetooth stack reports results of
-  // streamStarted or streamSuspended, the BluetoothAudioProvider will invoke
-  // this callback to report to the bluetooth_audio module.
-  // @param: cookie - indicates which bluetooth_audio output should handle
-  // @param: start_resp - this report is for startStream or not
-  // @param: status - the result of startStream
-  std::function<void(uint16_t cookie, bool start_resp,
-                     const BluetoothAudioStatus& status)>
-      control_result_cb_;
-  // session_changed_cb_ - when the Bluetooth stack start / end session, the
-  // BluetoothAudioProvider will invoke this callback to notify to the
-  // bluetooth_audio module.
-  // @param: cookie - indicates which bluetooth_audio output should handle
-  std::function<void(uint16_t cookie)> session_changed_cb_;
-};
-
-class BluetoothAudioSession {
- private:
-  // using recursive_mutex to allow hwbinder to re-enter again.
-  std::recursive_mutex mutex_;
-  SessionType session_type_;
-
-  // audio control path to use for both software and offloading
-  sp<IBluetoothAudioPort> stack_iface_;
-  // Audio path (FMQ) for software encoding/decoded data
-  std::unique_ptr<DataMQ> mDataMQ;
-  // audio data configuration for both software and offloading
-  AudioConfiguration audio_config_;
-
-  static AudioConfiguration invalidSoftwareAudioConfiguration;
-  static AudioConfiguration invalidOffloadAudioConfiguration;
-
-  // saving those registered bluetooth_audio's callbacks
-  std::unordered_map<uint16_t, std::shared_ptr<struct PortStatusCallbacks>>
-      observers_;
-
-  bool UpdateDataPath(const DataMQ::Descriptor* dataMQ);
-  bool UpdateAudioConfig(const AudioConfiguration& audio_config);
-  // invoking the registered session_changed_cb_
-  void ReportSessionStatus();
-
- public:
-  BluetoothAudioSession(const SessionType& session_type);
-
-  // The function helps to check if this session is ready or not
-  // @return: true if the Bluetooth stack has started the specified session
-  bool IsSessionReady();
-
-  // The report function is used to report that the Bluetooth stack has started
-  // this session without any failure, and will invoke session_changed_cb_ to
-  // notify those registered bluetooth_audio outputs
-  void OnSessionStarted(const sp<IBluetoothAudioPort> stack_iface,
-                        const DataMQ::Descriptor* dataMQ,
-                        const AudioConfiguration& audio_config);
-
-  // The report function is used to report that the Bluetooth stack has ended
-  // the session, and will invoke session_changed_cb_ to notify registered
-  // bluetooth_audio outputs
-  void OnSessionEnded();
-
-  // The report function is used to report that the Bluetooth stack has notified
-  // the result of startStream or suspendStream, and will invoke
-  // control_result_cb_ to notify registered bluetooth_audio outputs
-  void ReportControlStatus(bool start_resp, const BluetoothAudioStatus& status);
-
-  // The control function helps the bluetooth_audio module to register
-  // PortStatusCallbacks
-  // @return: cookie - the assigned number to this bluetooth_audio output
-  uint16_t RegisterStatusCback(const PortStatusCallbacks& cbacks);
-
-  // The control function helps the bluetooth_audio module to unregister
-  // PortStatusCallbacks
-  // @param: cookie - indicates which bluetooth_audio output is
-  void UnregisterStatusCback(uint16_t cookie);
-
-  // The control function is for the bluetooth_audio module to get the current
-  // AudioConfiguration
-  const AudioConfiguration& GetAudioConfig();
-
-  // Those control functions are for the bluetooth_audio module to start,
-  // suspend, stop stream, to check position, and to update metadata.
-  bool StartStream();
-  bool SuspendStream();
-  void StopStream();
-  bool GetPresentationPosition(uint64_t* remote_delay_report_ns,
-                               uint64_t* total_bytes_readed,
-                               timespec* data_position);
-  void UpdateTracksMetadata(const struct source_metadata* source_metadata);
-
-  // The control function writes stream to FMQ
-  size_t OutWritePcmData(const void* buffer, size_t bytes);
-  // The control function read stream from FMQ
-  size_t InReadPcmData(void* buffer, size_t bytes);
-
-  static constexpr PcmParameters kInvalidPcmParameters = {
-      .sampleRate = SampleRate::RATE_UNKNOWN,
-      .channelMode = ChannelMode::UNKNOWN,
-      .bitsPerSample = BitsPerSample::BITS_UNKNOWN,
-      .dataIntervalUs = 0,
-  };
-  // can't be constexpr because of non-literal type
-  static const CodecConfiguration kInvalidCodecConfiguration;
-
-  static constexpr AudioConfiguration& kInvalidSoftwareAudioConfiguration =
-      invalidSoftwareAudioConfiguration;
-  static constexpr AudioConfiguration& kInvalidOffloadAudioConfiguration =
-      invalidOffloadAudioConfiguration;
-};
-
-class BluetoothAudioSessionInstance {
- public:
-  // The API is to fetch the specified session
-  static std::shared_ptr<BluetoothAudioSession> GetSessionInstance(
-      const SessionType& session_type);
-
- private:
-  static std::unique_ptr<BluetoothAudioSessionInstance> instance_ptr;
-  std::mutex mutex_;
-  std::unordered_map<SessionType, std::shared_ptr<BluetoothAudioSession>>
-      sessions_map_;
-};
-
-}  // namespace audio
-}  // namespace bluetooth
-}  // namespace android
diff --git a/bluetooth/audio/2.1/default/session/BluetoothAudioSessionControl.h b/bluetooth/audio/2.1/default/session/BluetoothAudioSessionControl.h
deleted file mode 100644
index 017a611..0000000
--- a/bluetooth/audio/2.1/default/session/BluetoothAudioSessionControl.h
+++ /dev/null
@@ -1,154 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#pragma once
-
-#include "BluetoothAudioSession.h"
-
-namespace android {
-namespace bluetooth {
-namespace audio {
-
-class BluetoothAudioSessionControl {
- public:
-  // The control API helps to check if session is ready or not
-  // @return: true if the Bluetooth stack has started th specified session
-  static bool IsSessionReady(const SessionType& session_type) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->IsSessionReady();
-    }
-    return false;
-  }
-
-  // The control API helps the bluetooth_audio module to register
-  // PortStatusCallbacks
-  // @return: cookie - the assigned number to this bluetooth_audio output
-  static uint16_t RegisterControlResultCback(
-      const SessionType& session_type, const PortStatusCallbacks& cbacks) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->RegisterStatusCback(cbacks);
-    }
-    return kObserversCookieUndefined;
-  }
-
-  // The control API helps the bluetooth_audio module to unregister
-  // PortStatusCallbacks
-  // @param: cookie - indicates which bluetooth_audio output is
-  static void UnregisterControlResultCback(const SessionType& session_type,
-                                           uint16_t cookie) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      session_ptr->UnregisterStatusCback(cookie);
-    }
-  }
-
-  // The control API for the bluetooth_audio module to get current
-  // AudioConfiguration
-  static const AudioConfiguration& GetAudioConfig(
-      const SessionType& session_type) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->GetAudioConfig();
-    } else if (session_type == SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH) {
-      return BluetoothAudioSession::kInvalidOffloadAudioConfiguration;
-    } else {
-      return BluetoothAudioSession::kInvalidSoftwareAudioConfiguration;
-    }
-  }
-
-  // Those control APIs for the bluetooth_audio module to start / suspend / stop
-  // stream, to check position, and to update metadata.
-  static bool StartStream(const SessionType& session_type) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->StartStream();
-    }
-    return false;
-  }
-
-  static bool SuspendStream(const SessionType& session_type) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->SuspendStream();
-    }
-    return false;
-  }
-
-  static void StopStream(const SessionType& session_type) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      session_ptr->StopStream();
-    }
-  }
-
-  static bool GetPresentationPosition(const SessionType& session_type,
-                                      uint64_t* remote_delay_report_ns,
-                                      uint64_t* total_bytes_readed,
-                                      timespec* data_position) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->GetPresentationPosition(
-          remote_delay_report_ns, total_bytes_readed, data_position);
-    }
-    return false;
-  }
-
-  static void UpdateTracksMetadata(
-      const SessionType& session_type,
-      const struct source_metadata* source_metadata) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      session_ptr->UpdateTracksMetadata(source_metadata);
-    }
-  }
-
-  // The control API writes stream to FMQ
-  static size_t OutWritePcmData(const SessionType& session_type,
-                                const void* buffer, size_t bytes) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->OutWritePcmData(buffer, bytes);
-    }
-    return 0;
-  }
-
-  // The control API reads stream from FMQ
-  static size_t InReadPcmData(const SessionType& session_type, void* buffer,
-                              size_t bytes) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      return session_ptr->InReadPcmData(buffer, bytes);
-    }
-    return 0;
-  }
-};
-
-}  // namespace audio
-}  // namespace bluetooth
-}  // namespace android
diff --git a/bluetooth/audio/2.1/default/session/BluetoothAudioSessionReport.h b/bluetooth/audio/2.1/default/session/BluetoothAudioSessionReport.h
deleted file mode 100644
index 267bf8f..0000000
--- a/bluetooth/audio/2.1/default/session/BluetoothAudioSessionReport.h
+++ /dev/null
@@ -1,63 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#pragma once
-
-#include "BluetoothAudioSession.h"
-
-namespace android {
-namespace bluetooth {
-namespace audio {
-
-class BluetoothAudioSessionReport {
- public:
-  // The API reports the Bluetooth stack has started the session, and will
-  // inform registered bluetooth_audio session
-  static void OnSessionStarted(const SessionType& session_type,
-                               const sp<IBluetoothAudioPort> host_iface,
-                               const DataMQ::Descriptor* dataMQ,
-                               const AudioConfiguration& audio_config) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      session_ptr->OnSessionStarted(host_iface, dataMQ, audio_config);
-    }
-  }
-  // The API reports the Bluetooth stack has ended the session, and will
-  // inform registered bluetooth_audio outputs
-  static void OnSessionEnded(const SessionType& session_type) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      session_ptr->OnSessionEnded();
-    }
-  }
-  // The API reports the Bluetooth stack has replied the result of startStream
-  // or suspendStream, and will inform registered bluetooth_audio outputs
-  static void ReportControlStatus(const SessionType& session_type,
-                                  const bool& start_resp,
-                                  const BluetoothAudioStatus& status) {
-    std::shared_ptr<BluetoothAudioSession> session_ptr =
-        BluetoothAudioSessionInstance::GetSessionInstance(session_type);
-    if (session_ptr != nullptr) {
-      session_ptr->ReportControlStatus(start_resp, status);
-    }
-  }
-};
-
-}  // namespace audio
-}  // namespace bluetooth
-}  // namespace android
diff --git a/bluetooth/audio/2.1/default/session/BluetoothAudioSupportedCodecsDB.cpp b/bluetooth/audio/2.1/default/session/BluetoothAudioSupportedCodecsDB.cpp
deleted file mode 100644
index 0937f44..0000000
--- a/bluetooth/audio/2.1/default/session/BluetoothAudioSupportedCodecsDB.cpp
+++ /dev/null
@@ -1,489 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#define LOG_TAG "BTAudioProviderSessionCodecsDB"
-
-#include "BluetoothAudioSupportedCodecsDB.h"
-
-#include <android-base/logging.h>
-
-namespace android {
-namespace bluetooth {
-namespace audio {
-
-using ::android::hardware::bluetooth::audio::V2_0::AacObjectType;
-using ::android::hardware::bluetooth::audio::V2_0::AacParameters;
-using ::android::hardware::bluetooth::audio::V2_0::AacVariableBitRate;
-using ::android::hardware::bluetooth::audio::V2_0::AptxParameters;
-using ::android::hardware::bluetooth::audio::V2_0::BitsPerSample;
-using ::android::hardware::bluetooth::audio::V2_0::ChannelMode;
-using ::android::hardware::bluetooth::audio::V2_0::CodecType;
-using ::android::hardware::bluetooth::audio::V2_0::LdacChannelMode;
-using ::android::hardware::bluetooth::audio::V2_0::LdacParameters;
-using ::android::hardware::bluetooth::audio::V2_0::LdacQualityIndex;
-using ::android::hardware::bluetooth::audio::V2_0::SbcAllocMethod;
-using ::android::hardware::bluetooth::audio::V2_0::SbcBlockLength;
-using ::android::hardware::bluetooth::audio::V2_0::SbcChannelMode;
-using ::android::hardware::bluetooth::audio::V2_0::SbcNumSubbands;
-using ::android::hardware::bluetooth::audio::V2_0::SbcParameters;
-using ::android::hardware::bluetooth::audio::V2_1::SampleRate;
-
-// Default Supported PCM Parameters
-static const ::android::hardware::bluetooth::audio::V2_0::PcmParameters
-    kDefaultSoftwarePcmCapabilities = {
-        .sampleRate = static_cast<
-            android::hardware::bluetooth::audio::V2_0::SampleRate>(
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_44100 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_48000 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_88200 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_96000 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_16000),
-        .channelMode =
-            static_cast<ChannelMode>(ChannelMode::MONO | ChannelMode::STEREO),
-        .bitsPerSample = static_cast<BitsPerSample>(BitsPerSample::BITS_16 |
-                                                    BitsPerSample::BITS_24 |
-                                                    BitsPerSample::BITS_32)};
-
-static const PcmParameters kDefaultSoftwarePcmCapabilities_2_1 = {
-    .sampleRate = static_cast<SampleRate>(
-        SampleRate::RATE_48000 | SampleRate::RATE_44100 |
-        SampleRate::RATE_32000 | SampleRate::RATE_24000 |
-        SampleRate::RATE_16000 | SampleRate::RATE_8000),
-    .channelMode =
-        static_cast<ChannelMode>(ChannelMode::MONO | ChannelMode::STEREO),
-    .bitsPerSample = static_cast<BitsPerSample>(BitsPerSample::BITS_16)};
-
-// Default Supported Codecs
-// SBC: mSampleRate:(44100), mBitsPerSample:(16), mChannelMode:(MONO|STEREO)
-//      all blocks | subbands 8 | Loudness
-static const SbcParameters kDefaultOffloadSbcCapability = {
-    .sampleRate =
-        android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_44100,
-    .channelMode = static_cast<SbcChannelMode>(SbcChannelMode::MONO |
-                                               SbcChannelMode::JOINT_STEREO),
-    .blockLength = static_cast<SbcBlockLength>(
-        SbcBlockLength::BLOCKS_4 | SbcBlockLength::BLOCKS_8 |
-        SbcBlockLength::BLOCKS_12 | SbcBlockLength::BLOCKS_16),
-    .numSubbands = SbcNumSubbands::SUBBAND_8,
-    .allocMethod = SbcAllocMethod::ALLOC_MD_L,
-    .bitsPerSample = BitsPerSample::BITS_16,
-    .minBitpool = 2,
-    .maxBitpool = 53};
-
-// AAC: mSampleRate:(44100), mBitsPerSample:(16), mChannelMode:(STEREO)
-static const AacParameters kDefaultOffloadAacCapability = {
-    .objectType = AacObjectType::MPEG2_LC,
-    .sampleRate =
-        android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_44100,
-    .channelMode = ChannelMode::STEREO,
-    .variableBitRateEnabled = AacVariableBitRate::ENABLED,
-    .bitsPerSample = BitsPerSample::BITS_16};
-
-// LDAC: mSampleRate:(44100|48000|88200|96000), mBitsPerSample:(16|24|32),
-//       mChannelMode:(DUAL|STEREO)
-static const LdacParameters kDefaultOffloadLdacCapability = {
-    .sampleRate =
-        static_cast<android::hardware::bluetooth::audio::V2_0::SampleRate>(
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_44100 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_48000 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_88200 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_96000),
-    .channelMode = static_cast<LdacChannelMode>(LdacChannelMode::DUAL |
-                                                LdacChannelMode::STEREO),
-    .qualityIndex = LdacQualityIndex::QUALITY_HIGH,
-    .bitsPerSample = static_cast<BitsPerSample>(BitsPerSample::BITS_16 |
-                                                BitsPerSample::BITS_24 |
-                                                BitsPerSample::BITS_32)};
-
-// aptX: mSampleRate:(44100|48000), mBitsPerSample:(16), mChannelMode:(STEREO)
-static const AptxParameters kDefaultOffloadAptxCapability = {
-    .sampleRate =
-        static_cast<android::hardware::bluetooth::audio::V2_0::SampleRate>(
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_44100 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_48000),
-    .channelMode = ChannelMode::STEREO,
-    .bitsPerSample = BitsPerSample::BITS_16,
-};
-
-// aptX HD: mSampleRate:(44100|48000), mBitsPerSample:(24),
-//          mChannelMode:(STEREO)
-static const AptxParameters kDefaultOffloadAptxHdCapability = {
-    .sampleRate =
-        static_cast<android::hardware::bluetooth::audio::V2_0::SampleRate>(
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_44100 |
-            android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_48000),
-    .channelMode = ChannelMode::STEREO,
-    .bitsPerSample = BitsPerSample::BITS_24,
-};
-
-const std::vector<CodecCapabilities> kDefaultOffloadA2dpCodecCapabilities = {
-    {.codecType = CodecType::SBC, .capabilities = {}},
-    {.codecType = CodecType::AAC, .capabilities = {}},
-    {.codecType = CodecType::LDAC, .capabilities = {}},
-    {.codecType = CodecType::APTX, .capabilities = {}},
-    {.codecType = CodecType::APTX_HD, .capabilities = {}}};
-
-static bool IsSingleBit(uint32_t bitmasks, uint32_t bitfield) {
-  bool single = false;
-  uint32_t test_bit = 0x00000001;
-  while (test_bit <= bitmasks && test_bit <= bitfield) {
-    if (bitfield & test_bit && bitmasks & test_bit) {
-      if (single) return false;
-      single = true;
-    }
-    if (test_bit == 0x80000000) break;
-    test_bit <<= 1;
-  }
-  return single;
-}
-
-static bool IsOffloadSbcConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific);
-static bool IsOffloadAacConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific);
-static bool IsOffloadLdacConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific);
-static bool IsOffloadAptxConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific);
-static bool IsOffloadAptxHdConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific);
-
-static bool IsOffloadSbcConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific) {
-  if (codec_specific.getDiscriminator() !=
-      CodecConfiguration::CodecSpecific::hidl_discriminator::sbcConfig) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  }
-  const SbcParameters sbc_data = codec_specific.sbcConfig();
-  if (!IsSingleBit(static_cast<uint32_t>(sbc_data.sampleRate), 0xff) ||
-      !IsSingleBit(static_cast<uint32_t>(sbc_data.channelMode), 0x0f) ||
-      !IsSingleBit(static_cast<uint32_t>(sbc_data.blockLength), 0xf0) ||
-      !IsSingleBit(static_cast<uint32_t>(sbc_data.numSubbands), 0x0c) ||
-      !IsSingleBit(static_cast<uint32_t>(sbc_data.allocMethod), 0x03) ||
-      !IsSingleBit(static_cast<uint32_t>(sbc_data.bitsPerSample), 0x07) ||
-      sbc_data.minBitpool > sbc_data.maxBitpool) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  } else if ((sbc_data.sampleRate & kDefaultOffloadSbcCapability.sampleRate) &&
-             (sbc_data.channelMode &
-              kDefaultOffloadSbcCapability.channelMode) &&
-             (sbc_data.blockLength &
-              kDefaultOffloadSbcCapability.blockLength) &&
-             (sbc_data.numSubbands &
-              kDefaultOffloadSbcCapability.numSubbands) &&
-             (sbc_data.allocMethod &
-              kDefaultOffloadSbcCapability.allocMethod) &&
-             (sbc_data.bitsPerSample &
-              kDefaultOffloadSbcCapability.bitsPerSample) &&
-             (kDefaultOffloadSbcCapability.minBitpool <= sbc_data.minBitpool &&
-              sbc_data.maxBitpool <= kDefaultOffloadSbcCapability.maxBitpool)) {
-    return true;
-  }
-  LOG(WARNING) << __func__
-               << ": Unsupported CodecSpecific=" << toString(codec_specific);
-  return false;
-}
-
-static bool IsOffloadAacConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific) {
-  if (codec_specific.getDiscriminator() !=
-      CodecConfiguration::CodecSpecific::hidl_discriminator::aacConfig) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  }
-  const AacParameters aac_data = codec_specific.aacConfig();
-  if (!IsSingleBit(static_cast<uint32_t>(aac_data.objectType), 0xf0) ||
-      !IsSingleBit(static_cast<uint32_t>(aac_data.sampleRate), 0xff) ||
-      !IsSingleBit(static_cast<uint32_t>(aac_data.channelMode), 0x03) ||
-      !IsSingleBit(static_cast<uint32_t>(aac_data.bitsPerSample), 0x07)) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  } else if ((aac_data.objectType & kDefaultOffloadAacCapability.objectType) &&
-             (aac_data.sampleRate & kDefaultOffloadAacCapability.sampleRate) &&
-             (aac_data.channelMode &
-              kDefaultOffloadAacCapability.channelMode) &&
-             (aac_data.variableBitRateEnabled == AacVariableBitRate::DISABLED ||
-              kDefaultOffloadAacCapability.variableBitRateEnabled ==
-                  AacVariableBitRate::ENABLED) &&
-             (aac_data.bitsPerSample &
-              kDefaultOffloadAacCapability.bitsPerSample)) {
-    return true;
-  }
-  LOG(WARNING) << __func__
-               << ": Unsupported CodecSpecific=" << toString(codec_specific);
-  return false;
-}
-
-static bool IsOffloadLdacConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific) {
-  if (codec_specific.getDiscriminator() !=
-      CodecConfiguration::CodecSpecific::hidl_discriminator::ldacConfig) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  }
-  const LdacParameters ldac_data = codec_specific.ldacConfig();
-  if (!IsSingleBit(static_cast<uint32_t>(ldac_data.sampleRate), 0xff) ||
-      !IsSingleBit(static_cast<uint32_t>(ldac_data.channelMode), 0x07) ||
-      (ldac_data.qualityIndex > LdacQualityIndex::QUALITY_LOW &&
-       ldac_data.qualityIndex != LdacQualityIndex::QUALITY_ABR) ||
-      !IsSingleBit(static_cast<uint32_t>(ldac_data.bitsPerSample), 0x07)) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  } else if ((ldac_data.sampleRate &
-              kDefaultOffloadLdacCapability.sampleRate) &&
-             (ldac_data.channelMode &
-              kDefaultOffloadLdacCapability.channelMode) &&
-             (ldac_data.bitsPerSample &
-              kDefaultOffloadLdacCapability.bitsPerSample)) {
-    return true;
-  }
-  LOG(WARNING) << __func__
-               << ": Unsupported CodecSpecific=" << toString(codec_specific);
-  return false;
-}
-
-static bool IsOffloadAptxConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific) {
-  if (codec_specific.getDiscriminator() !=
-      CodecConfiguration::CodecSpecific::hidl_discriminator::aptxConfig) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  }
-  const AptxParameters aptx_data = codec_specific.aptxConfig();
-  if (!IsSingleBit(static_cast<uint32_t>(aptx_data.sampleRate), 0xff) ||
-      !IsSingleBit(static_cast<uint32_t>(aptx_data.channelMode), 0x03) ||
-      !IsSingleBit(static_cast<uint32_t>(aptx_data.bitsPerSample), 0x07)) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  } else if ((aptx_data.sampleRate &
-              kDefaultOffloadAptxCapability.sampleRate) &&
-             (aptx_data.channelMode &
-              kDefaultOffloadAptxCapability.channelMode) &&
-             (aptx_data.bitsPerSample &
-              kDefaultOffloadAptxCapability.bitsPerSample)) {
-    return true;
-  }
-  LOG(WARNING) << __func__
-               << ": Unsupported CodecSpecific=" << toString(codec_specific);
-  return false;
-}
-
-static bool IsOffloadAptxHdConfigurationValid(
-    const CodecConfiguration::CodecSpecific& codec_specific) {
-  if (codec_specific.getDiscriminator() !=
-      CodecConfiguration::CodecSpecific::hidl_discriminator::aptxConfig) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  }
-  const AptxParameters aptx_data = codec_specific.aptxConfig();
-  if (!IsSingleBit(static_cast<uint32_t>(aptx_data.sampleRate), 0xff) ||
-      !IsSingleBit(static_cast<uint32_t>(aptx_data.channelMode), 0x03) ||
-      !IsSingleBit(static_cast<uint32_t>(aptx_data.bitsPerSample), 0x07)) {
-    LOG(WARNING) << __func__
-                 << ": Invalid CodecSpecific=" << toString(codec_specific);
-    return false;
-  } else if ((aptx_data.sampleRate &
-              kDefaultOffloadAptxHdCapability.sampleRate) &&
-             (aptx_data.channelMode &
-              kDefaultOffloadAptxHdCapability.channelMode) &&
-             (aptx_data.bitsPerSample &
-              kDefaultOffloadAptxHdCapability.bitsPerSample)) {
-    return true;
-  }
-  LOG(WARNING) << __func__
-               << ": Unsupported CodecSpecific=" << toString(codec_specific);
-  return false;
-}
-
-std::vector<::android::hardware::bluetooth::audio::V2_0::PcmParameters>
-GetSoftwarePcmCapabilities() {
-  return std::vector<
-      ::android::hardware::bluetooth::audio::V2_0::PcmParameters>(
-      1, kDefaultSoftwarePcmCapabilities);
-}
-
-std::vector<PcmParameters> GetSoftwarePcmCapabilities_2_1() {
-  return std::vector<PcmParameters>(1, kDefaultSoftwarePcmCapabilities_2_1);
-}
-
-std::vector<CodecCapabilities> GetOffloadCodecCapabilities(
-    const ::android::hardware::bluetooth::audio::V2_0::SessionType&
-        session_type) {
-  return GetOffloadCodecCapabilities(static_cast<SessionType>(session_type));
-}
-
-std::vector<CodecCapabilities> GetOffloadCodecCapabilities(
-    const SessionType& session_type) {
-  if (session_type != SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH) {
-    return std::vector<CodecCapabilities>(0);
-  }
-  std::vector<CodecCapabilities> offload_a2dp_codec_capabilities =
-      kDefaultOffloadA2dpCodecCapabilities;
-  for (auto& codec_capability : offload_a2dp_codec_capabilities) {
-    switch (codec_capability.codecType) {
-      case CodecType::SBC:
-        codec_capability.capabilities.sbcCapabilities(
-            kDefaultOffloadSbcCapability);
-        break;
-      case CodecType::AAC:
-        codec_capability.capabilities.aacCapabilities(
-            kDefaultOffloadAacCapability);
-        break;
-      case CodecType::LDAC:
-        codec_capability.capabilities.ldacCapabilities(
-            kDefaultOffloadLdacCapability);
-        break;
-      case CodecType::APTX:
-        codec_capability.capabilities.aptxCapabilities(
-            kDefaultOffloadAptxCapability);
-        break;
-      case CodecType::APTX_HD:
-        codec_capability.capabilities.aptxCapabilities(
-            kDefaultOffloadAptxHdCapability);
-        break;
-      case CodecType::UNKNOWN:
-        codec_capability = {};
-        break;
-    }
-  }
-  return offload_a2dp_codec_capabilities;
-}
-
-bool IsSoftwarePcmConfigurationValid(
-    const ::android::hardware::bluetooth::audio::V2_0::PcmParameters&
-        pcm_config) {
-  if ((pcm_config.sampleRate !=
-           android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_44100 &&
-       pcm_config.sampleRate !=
-           android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_48000 &&
-       pcm_config.sampleRate !=
-           android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_88200 &&
-       pcm_config.sampleRate !=
-           android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_96000 &&
-       pcm_config.sampleRate !=
-           android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_16000 &&
-       pcm_config.sampleRate !=
-           android::hardware::bluetooth::audio::V2_0::SampleRate::RATE_24000) ||
-      (pcm_config.bitsPerSample != BitsPerSample::BITS_16 &&
-       pcm_config.bitsPerSample != BitsPerSample::BITS_24 &&
-       pcm_config.bitsPerSample != BitsPerSample::BITS_32) ||
-      (pcm_config.channelMode != ChannelMode::MONO &&
-       pcm_config.channelMode != ChannelMode::STEREO)) {
-    LOG(WARNING) << __func__
-                 << ": Invalid PCM Configuration=" << toString(pcm_config);
-    return false;
-  } else if (pcm_config.sampleRate &
-                 kDefaultSoftwarePcmCapabilities.sampleRate &&
-             pcm_config.bitsPerSample &
-                 kDefaultSoftwarePcmCapabilities.bitsPerSample &&
-             pcm_config.channelMode &
-                 kDefaultSoftwarePcmCapabilities.channelMode) {
-    return true;
-  }
-  LOG(WARNING) << __func__
-               << ": Unsupported PCM Configuration=" << toString(pcm_config);
-  return false;
-}
-
-bool IsSoftwarePcmConfigurationValid_2_1(const PcmParameters& pcm_config) {
-  if ((pcm_config.sampleRate != SampleRate::RATE_96000 &&
-       pcm_config.sampleRate != SampleRate::RATE_88200 &&
-       pcm_config.sampleRate != SampleRate::RATE_48000 &&
-       pcm_config.sampleRate != SampleRate::RATE_44100 &&
-       pcm_config.sampleRate != SampleRate::RATE_32000 &&
-       pcm_config.sampleRate != SampleRate::RATE_24000 &&
-       pcm_config.sampleRate != SampleRate::RATE_16000 &&
-       pcm_config.sampleRate != SampleRate::RATE_8000) ||
-      (pcm_config.bitsPerSample != BitsPerSample::BITS_16 &&
-       pcm_config.bitsPerSample != BitsPerSample::BITS_24 &&
-       pcm_config.bitsPerSample != BitsPerSample::BITS_32) ||
-      (pcm_config.channelMode != ChannelMode::MONO &&
-       pcm_config.channelMode != ChannelMode::STEREO)) {
-    LOG(WARNING) << __func__
-                 << ": Invalid PCM Configuration=" << toString(pcm_config);
-    return false;
-  } else if (pcm_config.sampleRate &
-                 kDefaultSoftwarePcmCapabilities_2_1.sampleRate &&
-             pcm_config.bitsPerSample &
-                 kDefaultSoftwarePcmCapabilities_2_1.bitsPerSample &&
-             pcm_config.channelMode &
-                 kDefaultSoftwarePcmCapabilities_2_1.channelMode &&
-             pcm_config.dataIntervalUs != 0) {
-    return true;
-  }
-  LOG(WARNING) << __func__
-               << ": Unsupported PCM Configuration=" << toString(pcm_config);
-  return false;
-}
-
-bool IsOffloadCodecConfigurationValid(const SessionType& session_type,
-                                      const CodecConfiguration& codec_config) {
-  if (session_type != SessionType::A2DP_HARDWARE_OFFLOAD_DATAPATH) {
-    LOG(ERROR) << __func__
-               << ": Invalid SessionType=" << toString(session_type);
-    return false;
-  } else if (codec_config.encodedAudioBitrate < 0x00000001 ||
-             0x00ffffff < codec_config.encodedAudioBitrate) {
-    LOG(ERROR) << __func__ << ": Unsupported Codec Configuration="
-               << toString(codec_config);
-    return false;
-  }
-  const CodecConfiguration::CodecSpecific& codec_specific = codec_config.config;
-  switch (codec_config.codecType) {
-    case CodecType::SBC:
-      if (IsOffloadSbcConfigurationValid(codec_specific)) {
-        return true;
-      }
-      return false;
-    case CodecType::AAC:
-      if (IsOffloadAacConfigurationValid(codec_specific)) {
-        return true;
-      }
-      return false;
-    case CodecType::LDAC:
-      if (IsOffloadLdacConfigurationValid(codec_specific)) {
-        return true;
-      }
-      return false;
-    case CodecType::APTX:
-      if (IsOffloadAptxConfigurationValid(codec_specific)) {
-        return true;
-      }
-      return false;
-    case CodecType::APTX_HD:
-      if (IsOffloadAptxHdConfigurationValid(codec_specific)) {
-        return true;
-      }
-      return false;
-    case CodecType::UNKNOWN:
-      return false;
-  }
-  return false;
-}
-
-}  // namespace audio
-}  // namespace bluetooth
-}  // namespace android
diff --git a/bluetooth/audio/2.1/default/session/BluetoothAudioSupportedCodecsDB.h b/bluetooth/audio/2.1/default/session/BluetoothAudioSupportedCodecsDB.h
deleted file mode 100644
index 9b2f680..0000000
--- a/bluetooth/audio/2.1/default/session/BluetoothAudioSupportedCodecsDB.h
+++ /dev/null
@@ -1,49 +0,0 @@
-/*
- * Copyright 2020 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#pragma once
-
-#include <android/hardware/bluetooth/audio/2.0/types.h>
-#include <android/hardware/bluetooth/audio/2.1/types.h>
-
-namespace android {
-namespace bluetooth {
-namespace audio {
-
-using ::android::hardware::bluetooth::audio::V2_0::CodecCapabilities;
-using ::android::hardware::bluetooth::audio::V2_0::CodecConfiguration;
-using ::android::hardware::bluetooth::audio::V2_1::PcmParameters;
-using ::android::hardware::bluetooth::audio::V2_1::SessionType;
-
-std::vector<::android::hardware::bluetooth::audio::V2_0::PcmParameters>
-GetSoftwarePcmCapabilities();
-std::vector<PcmParameters> GetSoftwarePcmCapabilities_2_1();
-std::vector<CodecCapabilities> GetOffloadCodecCapabilities(
-    const SessionType& session_type);
-std::vector<CodecCapabilities> GetOffloadCodecCapabilities(
-    const ::android::hardware::bluetooth::audio::V2_0::SessionType&
-        session_type);
-
-bool IsSoftwarePcmConfigurationValid_2_1(const PcmParameters& pcm_config);
-bool IsSoftwarePcmConfigurationValid(
-    const ::android::hardware::bluetooth::audio::V2_0::PcmParameters&
-        pcm_config);
-bool IsOffloadCodecConfigurationValid(const SessionType& session_type,
-                                      const CodecConfiguration& codec_config);
-
-}  // namespace audio
-}  // namespace bluetooth
-}  // namespace android
diff --git a/bluetooth/audio/2.1/vts/functional/VtsHalBluetoothAudioV2_1TargetTest.cpp b/bluetooth/audio/2.1/vts/functional/VtsHalBluetoothAudioV2_1TargetTest.cpp
index 95903d1..57fa07b 100644
--- a/bluetooth/audio/2.1/vts/functional/VtsHalBluetoothAudioV2_1TargetTest.cpp
+++ b/bluetooth/audio/2.1/vts/functional/VtsHalBluetoothAudioV2_1TargetTest.cpp
@@ -1032,7 +1032,7 @@
  * stopped with different PCM config
  */
 TEST_P(BluetoothAudioProviderLeAudioOutputSoftwareHidlTest,
-       StartAndEndLeAudioOutputSessionWithPossiblePcmConfig) {
+       DISABLED_StartAndEndLeAudioOutputSessionWithPossiblePcmConfig) {
   bool is_codec_config_valid;
   std::unique_ptr<DataMQ> tempDataMQ;
   auto hidl_cb = [&is_codec_config_valid, &tempDataMQ](
@@ -1126,7 +1126,7 @@
  * stopped with different PCM config
  */
 TEST_P(BluetoothAudioProviderLeAudioInputSoftwareHidlTest,
-       StartAndEndLeAudioInputSessionWithPossiblePcmConfig) {
+       DISABLED_StartAndEndLeAudioInputSessionWithPossiblePcmConfig) {
   bool is_codec_config_valid;
   std::unique_ptr<DataMQ> tempDataMQ;
   auto hidl_cb = [&is_codec_config_valid, &tempDataMQ](
diff --git a/bluetooth/audio/utils/Android.bp b/bluetooth/audio/utils/Android.bp
new file mode 100644
index 0000000..35476d2
--- /dev/null
+++ b/bluetooth/audio/utils/Android.bp
@@ -0,0 +1,23 @@
+cc_library_shared {
+    name: "libbluetooth_audio_session",
+    defaults: ["hidl_defaults"],
+    vendor: true,
+    srcs: [
+        "session/BluetoothAudioSession.cpp",
+        "session/BluetoothAudioSession_2_1.cpp",
+        "session/BluetoothAudioSupportedCodecsDB.cpp",
+        "session/BluetoothAudioSupportedCodecsDB_2_1.cpp",
+    ],
+    export_include_dirs: ["session/"],
+    header_libs: ["libhardware_headers"],
+    shared_libs: [
+        "android.hardware.bluetooth.audio@2.0",
+        "android.hardware.bluetooth.audio@2.1",
+        "libbase",
+        "libcutils",
+        "libfmq",
+        "libhidlbase",
+        "liblog",
+        "libutils",
+    ],
+}
diff --git a/bluetooth/audio/2.0/default/session/BluetoothAudioSession.cpp b/bluetooth/audio/utils/session/BluetoothAudioSession.cpp
similarity index 100%
rename from bluetooth/audio/2.0/default/session/BluetoothAudioSession.cpp
rename to bluetooth/audio/utils/session/BluetoothAudioSession.cpp
diff --git a/bluetooth/audio/2.0/default/session/BluetoothAudioSession.h b/bluetooth/audio/utils/session/BluetoothAudioSession.h
similarity index 100%
rename from bluetooth/audio/2.0/default/session/BluetoothAudioSession.h
rename to bluetooth/audio/utils/session/BluetoothAudioSession.h
diff --git a/bluetooth/audio/2.0/default/session/BluetoothAudioSessionControl.h b/bluetooth/audio/utils/session/BluetoothAudioSessionControl.h
similarity index 100%
rename from bluetooth/audio/2.0/default/session/BluetoothAudioSessionControl.h
rename to bluetooth/audio/utils/session/BluetoothAudioSessionControl.h
diff --git a/bluetooth/audio/utils/session/BluetoothAudioSessionControl_2_1.h b/bluetooth/audio/utils/session/BluetoothAudioSessionControl_2_1.h
new file mode 100644
index 0000000..86af468
--- /dev/null
+++ b/bluetooth/audio/utils/session/BluetoothAudioSessionControl_2_1.h
@@ -0,0 +1,148 @@
+/*
+ * Copyright 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include "BluetoothAudioSession_2_1.h"
+
+namespace android {
+namespace bluetooth {
+namespace audio {
+
+class BluetoothAudioSessionControl_2_1 {
+  using SessionType_2_1 =
+      ::android::hardware::bluetooth::audio::V2_1::SessionType;
+
+ public:
+  // The control API helps to check if session is ready or not
+  // @return: true if the Bluetooth stack has started th specified session
+  static bool IsSessionReady(const SessionType_2_1& session_type) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      return session_ptr->GetAudioSession()->IsSessionReady();
+    }
+    return false;
+  }
+
+  // The control API helps the bluetooth_audio module to register
+  // PortStatusCallbacks
+  // @return: cookie - the assigned number to this bluetooth_audio output
+  static uint16_t RegisterControlResultCback(
+      const SessionType_2_1& session_type, const PortStatusCallbacks& cbacks) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      return session_ptr->GetAudioSession()->RegisterStatusCback(cbacks);
+    }
+    return kObserversCookieUndefined;
+  }
+
+  // The control API helps the bluetooth_audio module to unregister
+  // PortStatusCallbacks
+  // @param: cookie - indicates which bluetooth_audio output is
+  static void UnregisterControlResultCback(const SessionType_2_1& session_type,
+                                           uint16_t cookie) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      session_ptr->GetAudioSession()->UnregisterStatusCback(cookie);
+    }
+  }
+
+  // The control API for the bluetooth_audio module to get current
+  // AudioConfiguration
+  static const AudioConfiguration& GetAudioConfig(
+      const SessionType_2_1& session_type) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      // TODO: map 2.1 to 2.0 audio config inside GetAudioConfig?
+      return session_ptr->GetAudioSession()->GetAudioConfig();
+    } else if (session_type ==
+               SessionType_2_1::A2DP_HARDWARE_OFFLOAD_DATAPATH) {
+      return BluetoothAudioSession::kInvalidOffloadAudioConfiguration;
+    } else {
+      return BluetoothAudioSession::kInvalidSoftwareAudioConfiguration;
+    }
+  }
+
+  // Those control APIs for the bluetooth_audio module to start / suspend / stop
+  // stream, to check position, and to update metadata.
+  static bool StartStream(const SessionType_2_1& session_type) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      return session_ptr->GetAudioSession()->StartStream();
+    }
+    return false;
+  }
+
+  static bool SuspendStream(const SessionType_2_1& session_type) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      return session_ptr->GetAudioSession()->SuspendStream();
+    }
+    return false;
+  }
+
+  static void StopStream(const SessionType_2_1& session_type) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      session_ptr->GetAudioSession()->StopStream();
+    }
+  }
+
+  static bool GetPresentationPosition(const SessionType_2_1& session_type,
+                                      uint64_t* remote_delay_report_ns,
+                                      uint64_t* total_bytes_readed,
+                                      timespec* data_position) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      return session_ptr->GetAudioSession()->GetPresentationPosition(
+          remote_delay_report_ns, total_bytes_readed, data_position);
+    }
+    return false;
+  }
+
+  static void UpdateTracksMetadata(
+      const SessionType_2_1& session_type,
+      const struct source_metadata* source_metadata) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      session_ptr->GetAudioSession()->UpdateTracksMetadata(source_metadata);
+    }
+  }
+
+  // The control API writes stream to FMQ
+  static size_t OutWritePcmData(const SessionType_2_1& session_type,
+                                const void* buffer, size_t bytes) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      return session_ptr->GetAudioSession()->OutWritePcmData(buffer, bytes);
+    }
+    return 0;
+  }
+};
+
+}  // namespace audio
+}  // namespace bluetooth
+}  // namespace android
diff --git a/bluetooth/audio/2.0/default/session/BluetoothAudioSessionReport.h b/bluetooth/audio/utils/session/BluetoothAudioSessionReport.h
similarity index 100%
rename from bluetooth/audio/2.0/default/session/BluetoothAudioSessionReport.h
rename to bluetooth/audio/utils/session/BluetoothAudioSessionReport.h
diff --git a/bluetooth/audio/utils/session/BluetoothAudioSessionReport_2_1.h b/bluetooth/audio/utils/session/BluetoothAudioSessionReport_2_1.h
new file mode 100644
index 0000000..ab30536
--- /dev/null
+++ b/bluetooth/audio/utils/session/BluetoothAudioSessionReport_2_1.h
@@ -0,0 +1,69 @@
+/*
+ * Copyright 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include "BluetoothAudioSession_2_1.h"
+
+namespace android {
+namespace bluetooth {
+namespace audio {
+
+class BluetoothAudioSessionReport_2_1 {
+ public:
+  // The API reports the Bluetooth stack has started the session, and will
+  // inform registered bluetooth_audio outputs
+  static void OnSessionStarted(
+      const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+          session_type,
+      const sp<IBluetoothAudioPort> host_iface,
+      const DataMQ::Descriptor* dataMQ,
+      const ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration&
+          audio_config) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      session_ptr->OnSessionStarted(host_iface, dataMQ, audio_config);
+    }
+  }
+  // The API reports the Bluetooth stack has ended the session, and will
+  // inform registered bluetooth_audio outputs
+  static void OnSessionEnded(
+      const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+          session_type) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      session_ptr->GetAudioSession()->OnSessionEnded();
+    }
+  }
+  // The API reports the Bluetooth stack has replied the result of startStream
+  // or suspendStream, and will inform registered bluetooth_audio outputs
+  static void ReportControlStatus(
+      const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+          session_type,
+      const bool& start_resp, const BluetoothAudioStatus& status) {
+    std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+        BluetoothAudioSessionInstance_2_1::GetSessionInstance(session_type);
+    if (session_ptr != nullptr) {
+      session_ptr->GetAudioSession()->ReportControlStatus(start_resp, status);
+    }
+  }
+};
+
+}  // namespace audio
+}  // namespace bluetooth
+}  // namespace android
diff --git a/bluetooth/audio/utils/session/BluetoothAudioSession_2_1.cpp b/bluetooth/audio/utils/session/BluetoothAudioSession_2_1.cpp
new file mode 100644
index 0000000..9e1baf4
--- /dev/null
+++ b/bluetooth/audio/utils/session/BluetoothAudioSession_2_1.cpp
@@ -0,0 +1,117 @@
+/*
+ * Copyright 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "BTAudioProviderSession_2_1"
+
+#include "BluetoothAudioSession_2_1.h"
+
+#include <android-base/logging.h>
+#include <android-base/stringprintf.h>
+
+namespace android {
+namespace bluetooth {
+namespace audio {
+using SessionType_2_1 =
+    ::android::hardware::bluetooth::audio::V2_1::SessionType;
+using SessionType_2_0 =
+    ::android::hardware::bluetooth::audio::V2_0::SessionType;
+
+namespace {
+bool is_2_0_session_type(
+    const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+        session_type) {
+  if (session_type == SessionType_2_1::A2DP_SOFTWARE_ENCODING_DATAPATH ||
+      session_type == SessionType_2_1::A2DP_HARDWARE_OFFLOAD_DATAPATH ||
+      session_type == SessionType_2_1::HEARING_AID_SOFTWARE_ENCODING_DATAPATH) {
+    return true;
+  } else {
+    return false;
+  }
+}
+}  // namespace
+
+BluetoothAudioSession_2_1::BluetoothAudioSession_2_1(
+    const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+        session_type)
+    : audio_session(BluetoothAudioSessionInstance::GetSessionInstance(
+          static_cast<SessionType_2_0>(session_type))) {
+  if (is_2_0_session_type(session_type)) {
+    session_type_2_1_ = (SessionType_2_1::UNKNOWN);
+  } else {
+    session_type_2_1_ = (session_type);
+  }
+}
+
+std::shared_ptr<BluetoothAudioSession>
+BluetoothAudioSession_2_1::GetAudioSession() {
+  return audio_session;
+}
+
+// The report function is used to report that the Bluetooth stack has started
+// this session without any failure, and will invoke session_changed_cb_ to
+// notify those registered bluetooth_audio outputs
+void BluetoothAudioSession_2_1::OnSessionStarted(
+    const sp<IBluetoothAudioPort> stack_iface, const DataMQ::Descriptor* dataMQ,
+    const ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration&
+        audio_config) {
+  if (session_type_2_1_ == SessionType_2_1::UNKNOWN) {
+    ::android::hardware::bluetooth::audio::V2_0::AudioConfiguration config;
+    if (audio_config.getDiscriminator() ==
+        ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration::
+            hidl_discriminator::codecConfig) {
+      config.codecConfig(audio_config.codecConfig());
+    } else {
+      auto& tmpPcm = audio_config.pcmConfig();
+      config.pcmConfig(
+          ::android::hardware::bluetooth::audio::V2_0::PcmParameters{
+              .sampleRate = static_cast<SampleRate>(tmpPcm.sampleRate),
+              .channelMode = tmpPcm.channelMode,
+              .bitsPerSample = tmpPcm.bitsPerSample
+              /*dataIntervalUs is not passed to 2.0 */
+          });
+    }
+
+    audio_session->OnSessionStarted(stack_iface, dataMQ, config);
+  } else {
+    LOG(FATAL) << " Not implemented yet!!";
+  }
+}
+
+std::unique_ptr<BluetoothAudioSessionInstance_2_1>
+    BluetoothAudioSessionInstance_2_1::instance_ptr =
+        std::unique_ptr<BluetoothAudioSessionInstance_2_1>(
+            new BluetoothAudioSessionInstance_2_1());
+
+// API to fetch the session of A2DP / Hearing Aid
+std::shared_ptr<BluetoothAudioSession_2_1>
+BluetoothAudioSessionInstance_2_1::GetSessionInstance(
+    const SessionType_2_1& session_type) {
+  std::lock_guard<std::mutex> guard(instance_ptr->mutex_);
+  if (!instance_ptr->sessions_map_.empty()) {
+    auto entry = instance_ptr->sessions_map_.find(session_type);
+    if (entry != instance_ptr->sessions_map_.end()) {
+      return entry->second;
+    }
+  }
+  std::shared_ptr<BluetoothAudioSession_2_1> session_ptr =
+      std::make_shared<BluetoothAudioSession_2_1>(session_type);
+  instance_ptr->sessions_map_[session_type] = session_ptr;
+  return session_ptr;
+}
+
+}  // namespace audio
+}  // namespace bluetooth
+}  // namespace android
diff --git a/bluetooth/audio/utils/session/BluetoothAudioSession_2_1.h b/bluetooth/audio/utils/session/BluetoothAudioSession_2_1.h
new file mode 100644
index 0000000..0e9c12b
--- /dev/null
+++ b/bluetooth/audio/utils/session/BluetoothAudioSession_2_1.h
@@ -0,0 +1,82 @@
+/*
+ * Copyright 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include <android/hardware/bluetooth/audio/2.1/types.h>
+#include "BluetoothAudioSession.h"
+
+#include <mutex>
+#include <unordered_map>
+
+namespace android {
+namespace bluetooth {
+namespace audio {
+
+class BluetoothAudioSession_2_1 {
+ private:
+  std::shared_ptr<BluetoothAudioSession> audio_session;
+
+  ::android::hardware::bluetooth::audio::V2_1::SessionType session_type_2_1_;
+
+  // audio data configuration for both software and offloading
+  ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration
+      audio_config_2_1_;
+
+  bool UpdateAudioConfig(
+      const ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration&
+          audio_config);
+
+ public:
+  BluetoothAudioSession_2_1(
+      const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+          session_type);
+
+  std::shared_ptr<BluetoothAudioSession> GetAudioSession();
+
+  // The report function is used to report that the Bluetooth stack has started
+  // this session without any failure, and will invoke session_changed_cb_ to
+  // notify those registered bluetooth_audio outputs
+  void OnSessionStarted(
+      const sp<IBluetoothAudioPort> stack_iface,
+      const DataMQ::Descriptor* dataMQ,
+      const ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration&
+          audio_config);
+
+  // The control function is for the bluetooth_audio module to get the current
+  // AudioConfiguration
+  const ::android::hardware::bluetooth::audio::V2_1::AudioConfiguration&
+  GetAudioConfig();
+};
+
+class BluetoothAudioSessionInstance_2_1 {
+ public:
+  // The API is to fetch the specified session of A2DP / Hearing Aid
+  static std::shared_ptr<BluetoothAudioSession_2_1> GetSessionInstance(
+      const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+          session_type);
+
+ private:
+  static std::unique_ptr<BluetoothAudioSessionInstance_2_1> instance_ptr;
+  std::mutex mutex_;
+  std::unordered_map<::android::hardware::bluetooth::audio::V2_1::SessionType,
+                     std::shared_ptr<BluetoothAudioSession_2_1>>
+      sessions_map_;
+};
+
+}  // namespace audio
+}  // namespace bluetooth
+}  // namespace android
diff --git a/bluetooth/audio/2.0/default/session/BluetoothAudioSupportedCodecsDB.cpp b/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB.cpp
similarity index 100%
rename from bluetooth/audio/2.0/default/session/BluetoothAudioSupportedCodecsDB.cpp
rename to bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB.cpp
diff --git a/bluetooth/audio/2.0/default/session/BluetoothAudioSupportedCodecsDB.h b/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB.h
similarity index 100%
rename from bluetooth/audio/2.0/default/session/BluetoothAudioSupportedCodecsDB.h
rename to bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB.h
diff --git a/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB_2_1.cpp b/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB_2_1.cpp
new file mode 100644
index 0000000..8b0b0f7
--- /dev/null
+++ b/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB_2_1.cpp
@@ -0,0 +1,127 @@
+/*
+ * Copyright 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "BTAudioProviderSessionCodecsDB_2_1"
+
+#include "BluetoothAudioSupportedCodecsDB_2_1.h"
+
+#include <android-base/logging.h>
+
+namespace android {
+namespace bluetooth {
+namespace audio {
+
+using ::android::hardware::bluetooth::audio::V2_0::BitsPerSample;
+using ::android::hardware::bluetooth::audio::V2_0::ChannelMode;
+
+using SampleRate_2_0 = ::android::hardware::bluetooth::audio::V2_0::SampleRate;
+using SampleRate_2_1 = ::android::hardware::bluetooth::audio::V2_1::SampleRate;
+
+using SessionType_2_1 =
+    ::android::hardware::bluetooth::audio::V2_1::SessionType;
+using SessionType_2_0 =
+    ::android::hardware::bluetooth::audio::V2_0::SessionType;
+
+namespace {
+bool is_2_0_session_type(
+    const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+        session_type) {
+  if (session_type == SessionType_2_1::A2DP_SOFTWARE_ENCODING_DATAPATH ||
+      session_type == SessionType_2_1::A2DP_HARDWARE_OFFLOAD_DATAPATH ||
+      session_type == SessionType_2_1::HEARING_AID_SOFTWARE_ENCODING_DATAPATH) {
+    return true;
+  } else {
+    return false;
+  }
+}
+}  // namespace
+
+static const ::android::hardware::bluetooth::audio::V2_1::PcmParameters
+    kDefaultSoftwarePcmCapabilities_2_1 = {
+        .sampleRate = static_cast<SampleRate_2_1>(
+            SampleRate_2_1::RATE_44100 | SampleRate_2_1::RATE_48000 |
+            SampleRate_2_1::RATE_88200 | SampleRate_2_1::RATE_96000 |
+            SampleRate_2_1::RATE_16000 | SampleRate_2_1::RATE_24000),
+        .channelMode =
+            static_cast<ChannelMode>(ChannelMode::MONO | ChannelMode::STEREO),
+        .bitsPerSample = static_cast<BitsPerSample>(BitsPerSample::BITS_16 |
+                                                    BitsPerSample::BITS_24 |
+                                                    BitsPerSample::BITS_32)};
+
+std::vector<::android::hardware::bluetooth::audio::V2_1::PcmParameters>
+GetSoftwarePcmCapabilities_2_1() {
+  return std::vector<
+      ::android::hardware::bluetooth::audio::V2_1::PcmParameters>(
+      1, kDefaultSoftwarePcmCapabilities_2_1);
+}
+
+std::vector<CodecCapabilities> GetOffloadCodecCapabilities(
+    const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+        session_type) {
+  if (is_2_0_session_type(session_type)) {
+    return GetOffloadCodecCapabilities(
+        static_cast<SessionType_2_0>(session_type));
+  }
+  return std::vector<CodecCapabilities>(0);
+}
+
+bool IsSoftwarePcmConfigurationValid_2_1(
+    const ::android::hardware::bluetooth::audio::V2_1::PcmParameters&
+        pcm_config) {
+  if ((pcm_config.sampleRate != SampleRate_2_1::RATE_44100 &&
+       pcm_config.sampleRate != SampleRate_2_1::RATE_48000 &&
+       pcm_config.sampleRate != SampleRate_2_1::RATE_88200 &&
+       pcm_config.sampleRate != SampleRate_2_1::RATE_96000 &&
+       pcm_config.sampleRate != SampleRate_2_1::RATE_16000 &&
+       pcm_config.sampleRate != SampleRate_2_1::RATE_24000) ||
+      (pcm_config.bitsPerSample != BitsPerSample::BITS_16 &&
+       pcm_config.bitsPerSample != BitsPerSample::BITS_24 &&
+       pcm_config.bitsPerSample != BitsPerSample::BITS_32) ||
+      (pcm_config.channelMode != ChannelMode::MONO &&
+       pcm_config.channelMode != ChannelMode::STEREO)) {
+    LOG(WARNING) << __func__
+                 << ": Invalid PCM Configuration=" << toString(pcm_config);
+    return false;
+  } else if (pcm_config.sampleRate &
+                 kDefaultSoftwarePcmCapabilities_2_1.sampleRate &&
+             pcm_config.bitsPerSample &
+                 kDefaultSoftwarePcmCapabilities_2_1.bitsPerSample &&
+             pcm_config.channelMode &
+                 kDefaultSoftwarePcmCapabilities_2_1.channelMode &&
+             pcm_config.dataIntervalUs != 0) {
+    return true;
+  }
+  LOG(WARNING) << __func__
+               << ": Unsupported PCM Configuration=" << toString(pcm_config);
+  return false;
+}
+
+bool IsOffloadCodecConfigurationValid(
+    const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+        session_type,
+    const ::android::hardware::bluetooth::audio::V2_0::CodecConfiguration&
+        codec_config) {
+  if (is_2_0_session_type(session_type)) {
+    return IsOffloadCodecConfigurationValid(
+        static_cast<SessionType_2_0>(session_type), codec_config);
+  }
+
+  return false;
+}
+
+}  // namespace audio
+}  // namespace bluetooth
+}  // namespace android
diff --git a/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB_2_1.h b/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB_2_1.h
new file mode 100644
index 0000000..746d9c0
--- /dev/null
+++ b/bluetooth/audio/utils/session/BluetoothAudioSupportedCodecsDB_2_1.h
@@ -0,0 +1,46 @@
+/*
+ * Copyright 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include "BluetoothAudioSupportedCodecsDB.h"
+
+#include <android/hardware/bluetooth/audio/2.1/types.h>
+
+namespace android {
+namespace bluetooth {
+namespace audio {
+
+std::vector<::android::hardware::bluetooth::audio::V2_1::PcmParameters>
+GetSoftwarePcmCapabilities_2_1();
+std::vector<::android::hardware::bluetooth::audio::V2_0::CodecCapabilities>
+GetOffloadCodecCapabilities(
+    const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+        session_type);
+
+bool IsSoftwarePcmConfigurationValid_2_1(
+    const ::android::hardware::bluetooth::audio::V2_1::PcmParameters&
+        pcm_config);
+
+bool IsOffloadCodecConfigurationValid(
+    const ::android::hardware::bluetooth::audio::V2_1::SessionType&
+        session_type,
+    const ::android::hardware::bluetooth::audio::V2_0::CodecConfiguration&
+        codec_config);
+
+}  // namespace audio
+}  // namespace bluetooth
+}  // namespace android
diff --git a/camera/metadata/3.6/Android.bp b/camera/metadata/3.6/Android.bp
new file mode 100644
index 0000000..d9f3fb8
--- /dev/null
+++ b/camera/metadata/3.6/Android.bp
@@ -0,0 +1,16 @@
+// This file is autogenerated by hidl-gen -Landroidbp.
+
+hidl_interface {
+    name: "android.hardware.camera.metadata@3.6",
+    root: "android.hardware",
+    srcs: [
+        "types.hal",
+    ],
+    interfaces: [
+        "android.hardware.camera.metadata@3.2",
+        "android.hardware.camera.metadata@3.3",
+        "android.hardware.camera.metadata@3.4",
+        "android.hardware.camera.metadata@3.5",
+    ],
+    gen_java: true,
+}
diff --git a/camera/metadata/3.6/types.hal b/camera/metadata/3.6/types.hal
new file mode 100644
index 0000000..fb95736
--- /dev/null
+++ b/camera/metadata/3.6/types.hal
@@ -0,0 +1,51 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*
+ * Autogenerated from camera metadata definitions in
+ * /system/media/camera/docs/metadata_definitions.xml
+ * *** DO NOT EDIT BY HAND ***
+ */
+
+package android.hardware.camera.metadata@3.6;
+
+import android.hardware.camera.metadata@3.2;
+import android.hardware.camera.metadata@3.3;
+import android.hardware.camera.metadata@3.4;
+import android.hardware.camera.metadata@3.5;
+
+// No new metadata sections added in this revision
+
+/**
+ * Main enumeration for defining camera metadata tags added in this revision
+ *
+ * <p>Partial documentation is included for each tag; for complete documentation, reference
+ * '/system/media/camera/docs/docs.html' in the corresponding Android source tree.</p>
+ */
+enum CameraMetadataTag : @3.5::CameraMetadataTag {
+    /** android.scaler.defaultSecureImageSize [static, int32[], public]
+     *
+     * <p>Default YUV/PRIVATE size to use for requesting secure image buffers.</p>
+     */
+    ANDROID_SCALER_DEFAULT_SECURE_IMAGE_SIZE = android.hardware.camera.metadata@3.5::CameraMetadataTag:ANDROID_SCALER_END_3_5,
+
+    ANDROID_SCALER_END_3_6,
+
+};
+
+/*
+ * Enumeration definitions for the various entries that need them
+ */
diff --git a/cas/1.0/vts/functional/VtsHalCasV1_0TargetTest.cpp b/cas/1.0/vts/functional/VtsHalCasV1_0TargetTest.cpp
index df0c859..a1d5930 100644
--- a/cas/1.0/vts/functional/VtsHalCasV1_0TargetTest.cpp
+++ b/cas/1.0/vts/functional/VtsHalCasV1_0TargetTest.cpp
@@ -256,12 +256,19 @@
 
 ::testing::AssertionResult MediaCasHidlTest::createCasPlugin(int32_t caSystemId) {
     auto status = mService->isSystemIdSupported(caSystemId);
+    bool skipDescrambler = false;
     if (!status.isOk() || !status) {
         return ::testing::AssertionFailure();
     }
     status = mService->isDescramblerSupported(caSystemId);
     if (!status.isOk() || !status) {
-        return ::testing::AssertionFailure();
+        if (mIsTestDescrambler) {
+            return ::testing::AssertionFailure();
+        } else {
+            ALOGI("Skip Descrambler test since it's not required in cas@1.2.");
+            mDescramblerBase = nullptr;
+            skipDescrambler = true;
+        }
     }
 
     mCasListener = new MediaCasListener();
@@ -274,16 +281,15 @@
         return ::testing::AssertionFailure();
     }
 
+    if (skipDescrambler) {
+        return ::testing::AssertionSuccess();
+    }
+
     auto descramblerStatus = mService->createDescrambler(caSystemId);
     if (!descramblerStatus.isOk()) {
-        if (mIsTestDescrambler) {
-            return ::testing::AssertionFailure();
-        } else {
-            ALOGI("Skip Descrambler test since it's not required in cas@1.2.");
-            return ::testing::AssertionSuccess();
-        }
+        return ::testing::AssertionFailure();
     }
-    mIsTestDescrambler = true;
+
     mDescramblerBase = descramblerStatus;
     return ::testing::AssertionResult(mDescramblerBase != nullptr);
 }
@@ -506,7 +512,7 @@
     returnStatus = mMediaCas->setSessionPrivateData(streamSessionId, hidlPvtData);
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         returnStatus = mDescramblerBase->setMediaCasSession(sessionId);
         EXPECT_TRUE(returnStatus.isOk());
         EXPECT_EQ(Status::OK, returnStatus);
@@ -556,7 +562,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         EXPECT_FALSE(mDescramblerBase->requiresSecureDecoderComponent("video/avc"));
 
         sp<IDescrambler> descrambler;
@@ -606,7 +612,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         returnStatus = mDescramblerBase->setMediaCasSession(sessionId);
         EXPECT_TRUE(returnStatus.isOk());
         EXPECT_EQ(Status::ERROR_CAS_SESSION_NOT_OPENED, returnStatus);
@@ -672,7 +678,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::ERROR_CAS_UNKNOWN, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         /*
          * Test MediaDescrambler error codes
          */
@@ -720,7 +726,7 @@
     std::vector<uint8_t> sessionId;
     ASSERT_TRUE(openCasSession(&sessionId));
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         returnStatus = mDescramblerBase->setMediaCasSession(sessionId);
         EXPECT_TRUE(returnStatus.isOk());
         EXPECT_EQ(Status::OK, returnStatus);
@@ -732,7 +738,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         sp<IDescrambler> descrambler = IDescrambler::castFrom(mDescramblerBase);
         ASSERT_NE(nullptr, descrambler.get());
 
diff --git a/cas/1.1/vts/functional/VtsHalCasV1_1TargetTest.cpp b/cas/1.1/vts/functional/VtsHalCasV1_1TargetTest.cpp
index 6797506..42d70cf 100644
--- a/cas/1.1/vts/functional/VtsHalCasV1_1TargetTest.cpp
+++ b/cas/1.1/vts/functional/VtsHalCasV1_1TargetTest.cpp
@@ -297,12 +297,19 @@
 
 ::testing::AssertionResult MediaCasHidlTest::createCasPlugin(int32_t caSystemId) {
     auto status = mService->isSystemIdSupported(caSystemId);
+    bool skipDescrambler = false;
     if (!status.isOk() || !status) {
         return ::testing::AssertionFailure();
     }
     status = mService->isDescramblerSupported(caSystemId);
     if (!status.isOk() || !status) {
-        return ::testing::AssertionFailure();
+        if (mIsTestDescrambler) {
+            return ::testing::AssertionFailure();
+        } else {
+            ALOGI("Skip Descrambler test since it's not required in cas@1.2.");
+            mDescramblerBase = nullptr;
+            skipDescrambler = true;
+        }
     }
 
     mCasListener = new MediaCasListener();
@@ -315,16 +322,14 @@
         return ::testing::AssertionFailure();
     }
 
+    if (skipDescrambler) {
+        return ::testing::AssertionSuccess();
+    }
+
     auto descramblerStatus = mService->createDescrambler(caSystemId);
     if (!descramblerStatus.isOk()) {
-        if (mIsTestDescrambler) {
-            return ::testing::AssertionFailure();
-        } else {
-            ALOGI("Skip Descrambler test since it's not required in cas@1.2.");
-            return ::testing::AssertionSuccess();
-        }
+        return ::testing::AssertionFailure();
     }
-    mIsTestDescrambler = true;
 
     mDescramblerBase = descramblerStatus;
     return ::testing::AssertionResult(mDescramblerBase != nullptr);
@@ -481,7 +486,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         returnStatus = mDescramblerBase->setMediaCasSession(sessionId);
         EXPECT_TRUE(returnStatus.isOk());
         EXPECT_EQ(Status::OK, returnStatus);
@@ -533,7 +538,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         EXPECT_FALSE(mDescramblerBase->requiresSecureDecoderComponent("video/avc"));
 
         sp<IDescrambler> descrambler;
diff --git a/cas/1.2/vts/functional/VtsHalCasV1_2TargetTest.cpp b/cas/1.2/vts/functional/VtsHalCasV1_2TargetTest.cpp
index 333dea6..0d75f5b 100644
--- a/cas/1.2/vts/functional/VtsHalCasV1_2TargetTest.cpp
+++ b/cas/1.2/vts/functional/VtsHalCasV1_2TargetTest.cpp
@@ -311,7 +311,6 @@
     sp<ICas> mMediaCas;
     sp<IDescramblerBase> mDescramblerBase;
     sp<MediaCasListener> mCasListener;
-    bool mIsTestDescrambler = false;
     typedef struct _OobInputTestParams {
         const SubSample* subSamples;
         uint32_t numSubSamples;
@@ -336,12 +335,15 @@
 
 ::testing::AssertionResult MediaCasHidlTest::createCasPlugin(int32_t caSystemId) {
     auto status = mService->isSystemIdSupported(caSystemId);
+    bool skipDescrambler = false;
     if (!status.isOk() || !status) {
         return ::testing::AssertionFailure();
     }
     status = mService->isDescramblerSupported(caSystemId);
     if (!status.isOk() || !status) {
-        return ::testing::AssertionFailure();
+        ALOGI("Skip Descrambler test since it's not required in cas@1.2.");
+        mDescramblerBase = nullptr;
+        skipDescrambler = true;
     }
 
     mCasListener = new MediaCasListener();
@@ -354,12 +356,14 @@
         return ::testing::AssertionFailure();
     }
 
-    auto descramblerStatus = mService->createDescrambler(caSystemId);
-    if (!descramblerStatus.isOk()) {
-        ALOGI("Skip Descrambler test since it's not required in cas@1.2.");
+    if (skipDescrambler) {
         return ::testing::AssertionSuccess();
     }
-    mIsTestDescrambler = true;
+
+    auto descramblerStatus = mService->createDescrambler(caSystemId);
+    if (!descramblerStatus.isOk()) {
+        return ::testing::AssertionFailure();
+    }
 
     mDescramblerBase = descramblerStatus;
     return ::testing::AssertionResult(mDescramblerBase != nullptr);
@@ -516,7 +520,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         returnStatus = mDescramblerBase->setMediaCasSession(sessionId);
         EXPECT_TRUE(returnStatus.isOk());
         EXPECT_EQ(Status::OK, returnStatus);
@@ -571,7 +575,7 @@
     EXPECT_TRUE(returnStatus.isOk());
     EXPECT_EQ(Status::OK, returnStatus);
 
-    if (mIsTestDescrambler) {
+    if (mDescramblerBase != nullptr) {
         EXPECT_FALSE(mDescramblerBase->requiresSecureDecoderComponent("video/avc"));
 
         sp<IDescrambler> descrambler;
diff --git a/compatibility_matrices/compatibility_matrix.current.xml b/compatibility_matrices/compatibility_matrix.current.xml
index 8e44be0..6562f22 100644
--- a/compatibility_matrices/compatibility_matrix.current.xml
+++ b/compatibility_matrices/compatibility_matrix.current.xml
@@ -9,7 +9,6 @@
     </hal>
     <hal format="hidl" optional="false">
         <name>android.hardware.audio</name>
-        <!-- TODO(b/142480271): remove 6.0 when implemented on reference device. -->
         <version>6.0</version>
         <version>7.0</version>
         <interface>
@@ -19,7 +18,6 @@
     </hal>
     <hal format="hidl" optional="false">
         <name>android.hardware.audio.effect</name>
-        <!-- TODO(b/142480271): remove 6.0 when implemented on reference device. -->
         <version>6.0</version>
         <version>7.0</version>
         <interface>
@@ -97,7 +95,7 @@
     </hal>
     <hal format="hidl" optional="true">
         <name>android.hardware.biometrics.face</name>
-        <version>1.0-1</version>
+        <version>1.0</version>
         <interface>
             <name>IBiometricsFace</name>
             <instance>default</instance>
@@ -191,7 +189,7 @@
     </hal>
     <hal format="hidl" optional="true">
         <name>android.hardware.contexthub</name>
-        <version>1.0-2</version>
+        <version>1.2</version>
         <interface>
             <name>IContexthub</name>
             <instance>default</instance>
@@ -345,6 +343,13 @@
         </interface>
     </hal>
     <hal format="aidl" optional="true">
+        <name>android.hardware.security.keymint</name>
+        <interface>
+            <name>IRemotelyProvisionedComponent</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="aidl" optional="true">
         <name>android.hardware.light</name>
         <version>1</version>
         <interface>
@@ -397,6 +402,13 @@
             <regex-instance>.*</regex-instance>
         </interface>
     </hal>
+    <hal format="aidl" optional="true">
+        <name>android.hardware.neuralnetworks</name>
+        <interface>
+            <name>IDevice</name>
+            <regex-instance>.*</regex-instance>
+        </interface>
+    </hal>
     <hal format="hidl" optional="true">
         <name>android.hardware.nfc</name>
         <version>1.2</version>
@@ -549,7 +561,7 @@
     </hal>
     <hal format="hidl" optional="true">
         <name>android.hardware.tv.cec</name>
-        <version>1.0</version>
+        <version>1.0-1</version>
         <interface>
             <name>IHdmiCec</name>
             <instance>default</instance>
@@ -573,7 +585,7 @@
     </hal>
     <hal format="hidl" optional="true">
         <name>android.hardware.usb</name>
-        <version>1.0-2</version>
+        <version>1.0-3</version>
         <interface>
             <name>IUsb</name>
             <instance>default</instance>
diff --git a/contexthub/1.0/vts/functional/VtsHalContexthubV1_0TargetTest.cpp b/contexthub/1.0/vts/functional/VtsHalContexthubV1_0TargetTest.cpp
index 8a90173..356ad97 100644
--- a/contexthub/1.0/vts/functional/VtsHalContexthubV1_0TargetTest.cpp
+++ b/contexthub/1.0/vts/functional/VtsHalContexthubV1_0TargetTest.cpp
@@ -52,40 +52,17 @@
 using ::android::hardware::contexthub::vts_utils::ContexthubHidlTestBase;
 using ::android::hardware::contexthub::vts_utils::getHalAndHubIdList;
 using ::android::hardware::contexthub::vts_utils::getHubsSync;
+using ::android::hardware::contexthub::vts_utils::kNonExistentAppId;
+using ::android::hardware::contexthub::vts_utils::waitForCallback;
 
 namespace {
 
-// App ID with vendor "GoogT" (Google Testing), app identifier 0x555555. This
-// app ID is reserved and must never appear in the list of loaded apps.
-constexpr uint64_t kNonExistentAppId = 0x476f6f6754555555;
-
 const std::vector<std::tuple<std::string, std::string>> kTestParameters =
         getHalAndHubIdList<IContexthub>();
 
 class ContexthubHidlTest : public ContexthubHidlTestBase<IContexthub> {};
 
-// Wait for a callback to occur (signaled by the given future) up to the
-// provided timeout. If the future is invalid or the callback does not come
-// within the given time, returns false.
-template <class ReturnType>
-bool waitForCallback(std::future<ReturnType> future, ReturnType* result,
-                     std::chrono::milliseconds timeout = std::chrono::seconds(5)) {
-    auto expiration = std::chrono::system_clock::now() + timeout;
-
-    EXPECT_NE(result, nullptr);
-    EXPECT_TRUE(future.valid());
-    if (result != nullptr && future.valid()) {
-        std::future_status status = future.wait_until(expiration);
-        EXPECT_NE(status, std::future_status::timeout) << "Timed out waiting for callback";
-
-        if (status == std::future_status::ready) {
-            *result = future.get();
-            return true;
-        }
-    }
-
-    return false;
-}
+class ContexthubCallbackV1_0 : public ContexthubCallbackBase<IContexthubCallback> {};
 
 // Ensures that the metadata reported in getHubs() is sane
 TEST_P(ContexthubHidlTest, TestGetHubs) {
@@ -110,7 +87,7 @@
 
 TEST_P(ContexthubHidlTest, TestRegisterCallback) {
     ALOGD("TestRegisterCallback called, hubId %" PRIu32, getHubId());
-    ASSERT_OK(registerCallback(new ContexthubCallbackBase()));
+    ASSERT_OK(registerCallback(new ContexthubCallbackV1_0()));
 }
 
 TEST_P(ContexthubHidlTest, TestRegisterNullCallback) {
@@ -119,7 +96,7 @@
 }
 
 // Helper callback that puts the async appInfo callback data into a promise
-class QueryAppsCallback : public ContexthubCallbackBase {
+class QueryAppsCallback : public ContexthubCallbackV1_0 {
   public:
     virtual Return<void> handleAppsInfo(const hidl_vec<HubAppInfo>& appInfo) override {
         ALOGD("Got app info callback with %zu apps", appInfo.size());
@@ -150,7 +127,7 @@
 
 // Helper callback that puts the TransactionResult for the expectedTxnId into a
 // promise
-class TxnResultCallback : public ContexthubCallbackBase {
+class TxnResultCallback : public ContexthubCallbackV1_0 {
   public:
     virtual Return<void> handleTxnResult(uint32_t txnId, TransactionResult result) override {
         ALOGD("Got transaction result callback for txnId %" PRIu32 " (expecting %" PRIu32
diff --git a/contexthub/1.1/vts/functional/VtsHalContexthubV1_1TargetTest.cpp b/contexthub/1.1/vts/functional/VtsHalContexthubV1_1TargetTest.cpp
index 5f1dad9..acf4be0 100644
--- a/contexthub/1.1/vts/functional/VtsHalContexthubV1_1TargetTest.cpp
+++ b/contexthub/1.1/vts/functional/VtsHalContexthubV1_1TargetTest.cpp
@@ -31,6 +31,7 @@
 
 #include <cinttypes>
 
+using ::android::hardware::contexthub::V1_0::IContexthubCallback;
 using ::android::hardware::contexthub::V1_1::IContexthub;
 using ::android::hardware::contexthub::V1_1::Setting;
 using ::android::hardware::contexthub::V1_1::SettingValue;
@@ -45,10 +46,12 @@
 
 class ContexthubHidlTest : public ContexthubHidlTestBase<IContexthub> {};
 
+class ContexthubCallbackV1_0 : public ContexthubCallbackBase<IContexthubCallback> {};
+
 TEST_P(ContexthubHidlTest, TestOnSettingChanged) {
     // In VTS, we only test that sending the values doesn't cause things to blow up - other test
     // suites verify the expected E2E behavior in CHRE
-    ASSERT_OK(registerCallback(new ContexthubCallbackBase()));
+    ASSERT_OK(registerCallback(new ContexthubCallbackV1_0()));
     hubApi->onSettingChanged(Setting::LOCATION, SettingValue::DISABLED);
     hubApi->onSettingChanged(Setting::LOCATION, SettingValue::ENABLED);
     ASSERT_OK(registerCallback(nullptr));
diff --git a/contexthub/1.2/IContexthub.hal b/contexthub/1.2/IContexthub.hal
index 3488b74..4bb9361 100644
--- a/contexthub/1.2/IContexthub.hal
+++ b/contexthub/1.2/IContexthub.hal
@@ -16,6 +16,7 @@
 
 package android.hardware.contexthub@1.2;
 
+import @1.0::ContextHub;
 import @1.0::Result;
 import @1.1::IContexthub;
 import @1.1::SettingValue;
@@ -23,6 +24,17 @@
 
 interface IContexthub extends @1.1::IContexthub {
     /**
+     * Enumerate all available context hubs on the system.
+     *
+     * @return hubs                 list of hubs on this system.
+     * @return supportedPermissions list of Android permissions all hubs
+     *                              support for nanoapps to enforce host
+     *                              endpoints are granted in order to
+     *                              communicate with them.
+     */
+    getHubs_1_2() generates (vec<ContextHub> hubs, vec<string> supportedPermissions);
+
+    /**
      * Register a callback for the HAL implementation to send asynchronous
      * messages to the service from a context hub. There can be a maximum of
      * one callback registered with the HAL. A call to this function when a
diff --git a/contexthub/1.2/IContexthubCallback.hal b/contexthub/1.2/IContexthubCallback.hal
index 0236160..1a40512 100644
--- a/contexthub/1.2/IContexthubCallback.hal
+++ b/contexthub/1.2/IContexthubCallback.hal
@@ -24,10 +24,18 @@
      * implementation to allow the HAL to send asynchronous messages back
      * to the service and registered clients of the ContextHub service.
      *
-     * @param msg message that should be delivered to host app clients
-     *
+     * @param msg             message that should be delivered to host app
+     *                        clients
+     * @param msgContentPerms list of Android permissions that cover the
+     *                        contents of the message being sent from the app.
+     *                        This is different from the permissions stored
+     *                        inside of ContextHubMsg in that these must be a
+     *                        subset of those permissions and are meant to
+     *                        assist in properly attributing the message
+     *                        contents when delivering to a ContextHub service
+     *                        client.
      */
-    handleClientMsg_1_2(ContextHubMsg msg);
+    handleClientMsg_1_2(ContextHubMsg msg, vec<string> msgContentPerms);
 
     /**
      * This callback is passed by the Contexthub service to the HAL
diff --git a/contexthub/1.2/default/Contexthub.cpp b/contexthub/1.2/default/Contexthub.cpp
index db0c5bc..601eccd 100644
--- a/contexthub/1.2/default/Contexthub.cpp
+++ b/contexthub/1.2/default/Contexthub.cpp
@@ -23,10 +23,36 @@
 namespace V1_2 {
 namespace implementation {
 
+using ::android::hardware::hidl_string;
 using ::android::hardware::contexthub::V1_0::Result;
 using ::android::hardware::contexthub::V1_X::implementation::IContextHubCallbackWrapperV1_0;
 using ::android::hardware::contexthub::V1_X::implementation::IContextHubCallbackWrapperV1_2;
 
+Return<void> Contexthub::getHubs_1_2(getHubs_1_2_cb _hidl_cb) {
+    ::android::hardware::contexthub::V1_0::ContextHub hub = {};
+    hub.name = "Mock Context Hub";
+    hub.vendor = "AOSP";
+    hub.toolchain = "n/a";
+    hub.platformVersion = 1;
+    hub.toolchainVersion = 1;
+    hub.hubId = kMockHubId;
+    hub.peakMips = 1;
+    hub.peakPowerDrawMw = 1;
+    hub.maxSupportedMsgLen = 4096;
+    hub.chrePlatformId = UINT64_C(0x476f6f6754000000);
+    hub.chreApiMajorVersion = 1;
+    hub.chreApiMinorVersion = 4;
+
+    // Report a single mock hub
+    std::vector<::android::hardware::contexthub::V1_0::ContextHub> hubs;
+    hubs.push_back(hub);
+
+    std::vector<hidl_string> hubPermissionList;
+
+    _hidl_cb(hubs, hubPermissionList);
+    return Void();
+}
+
 Return<Result> Contexthub::registerCallback(uint32_t hubId,
                                             const sp<V1_0::IContexthubCallback>& cb) {
     if (hubId == kMockHubId) {
diff --git a/contexthub/1.2/default/Contexthub.h b/contexthub/1.2/default/Contexthub.h
index 8b89824..32b862d 100644
--- a/contexthub/1.2/default/Contexthub.h
+++ b/contexthub/1.2/default/Contexthub.h
@@ -35,6 +35,7 @@
     using Result = ::android::hardware::contexthub::V1_0::Result;
     using SettingValue = ::android::hardware::contexthub::V1_1::SettingValue;
     using SettingV1_1 = ::android::hardware::contexthub::V1_1::Setting;
+    using getHubs_1_2_cb = ::android::hardware::contexthub::V1_2::IContexthub::getHubs_1_2_cb;
 
   public:
     // Methods from V1_0::IContexthub
@@ -47,6 +48,8 @@
     Return<void> onSettingChanged(SettingV1_1 setting, SettingValue newValue) override;
 
     // Methods from V1_2::IContexthub
+    Return<void> getHubs_1_2(getHubs_1_2_cb _hidl_cb) override;
+
     Return<void> onSettingChanged_1_2(Setting setting, SettingValue newValue) override;
 
     Return<Result> registerCallback_1_2(uint32_t hubId,
diff --git a/contexthub/1.2/vts/functional/VtsHalContexthubV1_2TargetTest.cpp b/contexthub/1.2/vts/functional/VtsHalContexthubV1_2TargetTest.cpp
index 782edae..c50d43c 100644
--- a/contexthub/1.2/vts/functional/VtsHalContexthubV1_2TargetTest.cpp
+++ b/contexthub/1.2/vts/functional/VtsHalContexthubV1_2TargetTest.cpp
@@ -32,45 +32,202 @@
 
 #include <cinttypes>
 
+using ::android::sp;
+using ::android::hardware::hidl_string;
+using ::android::hardware::hidl_vec;
+using ::android::hardware::Return;
+using ::android::hardware::Void;
+using ::android::hardware::contexthub::V1_0::ContextHub;
+using ::android::hardware::contexthub::V1_0::Result;
+using ::android::hardware::contexthub::V1_0::TransactionResult;
 using ::android::hardware::contexthub::V1_1::SettingValue;
+using ::android::hardware::contexthub::V1_2::ContextHubMsg;
+using ::android::hardware::contexthub::V1_2::HubAppInfo;
 using ::android::hardware::contexthub::V1_2::IContexthub;
+using ::android::hardware::contexthub::V1_2::IContexthubCallback;
 using ::android::hardware::contexthub::V1_2::Setting;
+using ::android::hardware::contexthub::vts_utils::asBaseType;
 using ::android::hardware::contexthub::vts_utils::ContexthubCallbackBase;
 using ::android::hardware::contexthub::vts_utils::ContexthubHidlTestBase;
 using ::android::hardware::contexthub::vts_utils::getHalAndHubIdList;
+using ::android::hardware::contexthub::vts_utils::kNonExistentAppId;
+using ::android::hardware::contexthub::vts_utils::waitForCallback;
 
 namespace {
 
 const std::vector<std::tuple<std::string, std::string>> kTestParameters =
         getHalAndHubIdList<IContexthub>();
 
-class ContexthubHidlTest : public ContexthubHidlTestBase<IContexthub> {};
+class ContexthubCallbackV1_2 : public ContexthubCallbackBase<IContexthubCallback> {
+  public:
+    virtual Return<void> handleClientMsg_1_2(
+            const ContextHubMsg& /*msg*/,
+            const hidl_vec<hidl_string>& /*msgContentPerms*/) override {
+        ALOGD("Got client message callback");
+        return Void();
+    }
+
+    virtual Return<void> handleAppsInfo_1_2(const hidl_vec<HubAppInfo>& /*appInfo*/) override {
+        ALOGD("Got app info callback");
+        return Void();
+    }
+};
+
+class ContexthubHidlTest : public ContexthubHidlTestBase<IContexthub> {
+  public:
+    Result registerCallback_1_2(sp<IContexthubCallback> cb) {
+        return hubApi->registerCallback_1_2(getHubId(), cb);
+    }
+};
+
+// Ensures that the metadata reported in getHubs_1_2() is valid
+TEST_P(ContexthubHidlTest, TestGetHubs_1_2) {
+    hidl_vec<ContextHub> hubList;
+    hubApi->getHubs_1_2(
+            [&hubList](const hidl_vec<ContextHub>& hubs,
+                       const hidl_vec<hidl_string>& /*hubPermissions*/) { hubList = hubs; });
+
+    ALOGD("System reports %zu hubs", hubList.size());
+
+    for (const ContextHub& hub : hubList) {
+        ALOGD("Checking hub ID %" PRIu32, hub.hubId);
+
+        EXPECT_FALSE(hub.name.empty());
+        EXPECT_FALSE(hub.vendor.empty());
+        EXPECT_FALSE(hub.toolchain.empty());
+        EXPECT_GT(hub.peakMips, 0);
+        EXPECT_GE(hub.stoppedPowerDrawMw, 0);
+        EXPECT_GE(hub.sleepPowerDrawMw, 0);
+        EXPECT_GT(hub.peakPowerDrawMw, 0);
+
+        // Minimum 128 byte MTU as required by CHRE API v1.0
+        EXPECT_GE(hub.maxSupportedMsgLen, UINT32_C(128));
+    }
+}
+
+TEST_P(ContexthubHidlTest, TestRegisterCallback) {
+    ALOGD("TestRegisterCallback called, hubId %" PRIu32, getHubId());
+    ASSERT_OK(registerCallback_1_2(new ContexthubCallbackV1_2()));
+}
+
+TEST_P(ContexthubHidlTest, TestRegisterNullCallback) {
+    ALOGD("TestRegisterNullCallback called, hubId %" PRIu32, getHubId());
+    ASSERT_OK(registerCallback_1_2(nullptr));
+}
 
 // In VTS, we only test that sending the values doesn't cause things to blow up - other test
 // suites verify the expected E2E behavior in CHRE
 TEST_P(ContexthubHidlTest, TestOnWifiSettingChanged) {
-    ASSERT_OK(registerCallback(new ContexthubCallbackBase()));
+    ASSERT_OK(registerCallback_1_2(new ContexthubCallbackV1_2()));
     hubApi->onSettingChanged_1_2(Setting::WIFI_AVAILABLE, SettingValue::DISABLED);
     hubApi->onSettingChanged_1_2(Setting::WIFI_AVAILABLE, SettingValue::ENABLED);
-    ASSERT_OK(registerCallback(nullptr));
+    ASSERT_OK(registerCallback_1_2(nullptr));
 }
 
 TEST_P(ContexthubHidlTest, TestOnAirplaneModeSettingChanged) {
-    ASSERT_OK(registerCallback(new ContexthubCallbackBase()));
+    ASSERT_OK(registerCallback_1_2(new ContexthubCallbackV1_2()));
     hubApi->onSettingChanged_1_2(Setting::AIRPLANE_MODE, SettingValue::DISABLED);
     hubApi->onSettingChanged_1_2(Setting::AIRPLANE_MODE, SettingValue::ENABLED);
-    ASSERT_OK(registerCallback(nullptr));
+    ASSERT_OK(registerCallback_1_2(nullptr));
 }
 
 TEST_P(ContexthubHidlTest, TestOnGlobalMicDisableSettingChanged) {
-    ASSERT_OK(registerCallback(new ContexthubCallbackBase()));
+    ASSERT_OK(registerCallback_1_2(new ContexthubCallbackV1_2()));
     hubApi->onSettingChanged_1_2(Setting::GLOBAL_MIC_DISABLE, SettingValue::DISABLED);
     hubApi->onSettingChanged_1_2(Setting::GLOBAL_MIC_DISABLE, SettingValue::ENABLED);
-    ASSERT_OK(registerCallback(nullptr));
+    ASSERT_OK(registerCallback_1_2(nullptr));
+}
+
+// Helper callback that puts the async appInfo callback data into a promise
+class QueryAppsCallback : public ContexthubCallbackV1_2 {
+  public:
+    virtual Return<void> handleAppsInfo_1_2(const hidl_vec<HubAppInfo>& appInfo) override {
+        ALOGD("Got app info callback with %zu apps", appInfo.size());
+        promise.set_value(appInfo);
+        return Void();
+    }
+
+    std::promise<hidl_vec<HubAppInfo>> promise;
+};
+
+// Calls queryApps() and checks the returned metadata
+TEST_P(ContexthubHidlTest, TestQueryApps) {
+    hidl_vec<hidl_string> hubPerms;
+    hubApi->getHubs_1_2([&hubPerms](const hidl_vec<ContextHub>& /*hubs*/,
+                                    const hidl_vec<hidl_string>& hubPermissions) {
+        hubPerms = hubPermissions;
+    });
+
+    ALOGD("TestQueryApps called, hubId %u", getHubId());
+    sp<QueryAppsCallback> cb = new QueryAppsCallback();
+    ASSERT_OK(registerCallback_1_2(cb));
+
+    Result result = hubApi->queryApps(getHubId());
+    ASSERT_OK(result);
+
+    ALOGD("Waiting for app info callback");
+    hidl_vec<HubAppInfo> appList;
+    ASSERT_TRUE(waitForCallback(cb->promise.get_future(), &appList));
+    for (const HubAppInfo& appInfo : appList) {
+        EXPECT_NE(appInfo.info_1_0.appId, UINT64_C(0));
+        EXPECT_NE(appInfo.info_1_0.appId, kNonExistentAppId);
+        for (std::string permission : appInfo.permissions) {
+            ASSERT_TRUE(hubPerms.contains(permission));
+        }
+    }
+}
+
+// Helper callback that puts the TransactionResult for the expectedTxnId into a
+// promise
+class TxnResultCallback : public ContexthubCallbackV1_2 {
+  public:
+    virtual Return<void> handleTxnResult(uint32_t txnId, TransactionResult result) override {
+        ALOGD("Got transaction result callback for txnId %" PRIu32 " (expecting %" PRIu32
+              ") with result %" PRId32,
+              txnId, expectedTxnId, result);
+        if (txnId == expectedTxnId) {
+            promise.set_value(result);
+        }
+        return Void();
+    }
+
+    uint32_t expectedTxnId = 0;
+    std::promise<TransactionResult> promise;
+};
+
+// Parameterized fixture that sets the callback to TxnResultCallback
+class ContexthubTxnTest : public ContexthubHidlTest {
+  public:
+    virtual void SetUp() override {
+        ContexthubHidlTest::SetUp();
+        ASSERT_OK(registerCallback_1_2(cb));
+    }
+
+    sp<TxnResultCallback> cb = new TxnResultCallback();
+};
+
+TEST_P(ContexthubTxnTest, TestSendMessageToNonExistentNanoApp) {
+    ContextHubMsg msg;
+    msg.msg_1_0.appName = kNonExistentAppId;
+    msg.msg_1_0.msgType = 1;
+    msg.msg_1_0.msg.resize(4);
+    std::fill(msg.msg_1_0.msg.begin(), msg.msg_1_0.msg.end(), 0);
+
+    ALOGD("Sending message to non-existent nanoapp");
+    Result result = hubApi->sendMessageToHub_1_2(getHubId(), msg);
+    if (result != Result::OK && result != Result::BAD_PARAMS &&
+        result != Result::TRANSACTION_FAILED) {
+        FAIL() << "Got result " << asBaseType(result) << ", expected OK, BAD_PARAMS"
+               << ", or TRANSACTION_FAILED";
+    }
 }
 
 GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(ContexthubHidlTest);
 INSTANTIATE_TEST_SUITE_P(HubIdSpecificTests, ContexthubHidlTest, testing::ValuesIn(kTestParameters),
                          android::hardware::PrintInstanceTupleNameToString<>);
 
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(ContexthubTxnTest);
+INSTANTIATE_TEST_SUITE_P(HubIdSpecificTests, ContexthubTxnTest, testing::ValuesIn(kTestParameters),
+                         android::hardware::PrintInstanceTupleNameToString<>);
+
 }  // anonymous namespace
diff --git a/contexthub/common/default/1.X/utils/IContextHubCallbackWrapper.h b/contexthub/common/default/1.X/utils/IContextHubCallbackWrapper.h
index df78438..d9459b7 100644
--- a/contexthub/common/default/1.X/utils/IContextHubCallbackWrapper.h
+++ b/contexthub/common/default/1.X/utils/IContextHubCallbackWrapper.h
@@ -54,7 +54,8 @@
  */
 class IContextHubCallbackWrapperBase : public VirtualLightRefBase {
   public:
-    virtual Return<void> handleClientMsg(V1_2::ContextHubMsg msg) = 0;
+    virtual Return<void> handleClientMsg(V1_2::ContextHubMsg msg,
+                                         hidl_vec<hidl_string> msgContentPerms) = 0;
 
     virtual Return<void> handleTxnResult(uint32_t txnId, V1_0::TransactionResult result) = 0;
 
@@ -63,6 +64,11 @@
     virtual Return<void> handleAppAbort(uint64_t appId, uint32_t abortCode) = 0;
 
     virtual Return<void> handleAppsInfo(hidl_vec<V1_2::HubAppInfo> appInfo) = 0;
+
+    virtual Return<bool> linkToDeath(const sp<hidl_death_recipient>& recipient,
+                                     uint64_t cookie) = 0;
+
+    virtual Return<bool> unlinkToDeath(const sp<hidl_death_recipient>& recipient) = 0;
 };
 
 template <typename T>
@@ -70,7 +76,8 @@
   public:
     ContextHubCallbackWrapper(sp<T> callback) : mCallback(callback){};
 
-    virtual Return<void> handleClientMsg(V1_2::ContextHubMsg msg) override {
+    virtual Return<void> handleClientMsg(V1_2::ContextHubMsg msg,
+                                         hidl_vec<hidl_string> /* msgContentPerms */) override {
         return mCallback->handleClientMsg(convertToOldMsg(msg));
     }
 
@@ -90,6 +97,14 @@
         return mCallback->handleAppsInfo(convertToOldAppInfo(appInfo));
     }
 
+    Return<bool> linkToDeath(const sp<hidl_death_recipient>& recipient, uint64_t cookie) override {
+        return mCallback->linkToDeath(recipient, cookie);
+    }
+
+    Return<bool> unlinkToDeath(const sp<hidl_death_recipient>& recipient) override {
+        return mCallback->unlinkToDeath(recipient);
+    }
+
   protected:
     sp<T> mCallback;
 };
@@ -105,8 +120,9 @@
     IContextHubCallbackWrapperV1_2(sp<V1_2::IContexthubCallback> callback)
         : ContextHubCallbackWrapper(callback){};
 
-    Return<void> handleClientMsg(V1_2::ContextHubMsg msg) override {
-        return mCallback->handleClientMsg_1_2(msg);
+    Return<void> handleClientMsg(V1_2::ContextHubMsg msg,
+                                 hidl_vec<hidl_string> msgContentPerms) override {
+        return mCallback->handleClientMsg_1_2(msg, msgContentPerms);
     }
 
     Return<void> handleAppsInfo(hidl_vec<V1_2::HubAppInfo> appInfo) override {
diff --git a/contexthub/common/vts/ContexthubCallbackBase.h b/contexthub/common/vts/ContexthubCallbackBase.h
index 124a116..24d6c52 100644
--- a/contexthub/common/vts/ContexthubCallbackBase.h
+++ b/contexthub/common/vts/ContexthubCallbackBase.h
@@ -27,7 +27,8 @@
 
 // Base callback implementation that just logs all callbacks by default, but
 // records a failure if
-class ContexthubCallbackBase : public V1_0::IContexthubCallback {
+template <class CallbackType>
+class ContexthubCallbackBase : public CallbackType {
   public:
     virtual Return<void> handleClientMsg(const V1_0::ContextHubMsg& /*msg*/) override {
         ALOGD("Got client message callback");
diff --git a/contexthub/common/vts/VtsHalContexthubUtils.h b/contexthub/common/vts/VtsHalContexthubUtils.h
index 8f9b694..dff1865 100644
--- a/contexthub/common/vts/VtsHalContexthubUtils.h
+++ b/contexthub/common/vts/VtsHalContexthubUtils.h
@@ -30,6 +30,10 @@
 namespace contexthub {
 namespace vts_utils {
 
+// App ID with vendor "GoogT" (Google Testing), app identifier 0x555555. This
+// app ID is reserved and must never appear in the list of loaded apps.
+constexpr uint64_t kNonExistentAppId = 0x476f6f6754555555;
+
 #define ASSERT_OK(result) ASSERT_EQ(result, ::android::hardware::contexthub::V1_0::Result::OK)
 #define EXPECT_OK(result) EXPECT_EQ(result, ::android::hardware::contexthub::V1_0::Result::OK)
 
@@ -64,6 +68,29 @@
     return parameters;
 }
 
+// Wait for a callback to occur (signaled by the given future) up to the
+// provided timeout. If the future is invalid or the callback does not come
+// within the given time, returns false.
+template <class ReturnType>
+bool waitForCallback(std::future<ReturnType> future, ReturnType* result,
+                     std::chrono::milliseconds timeout = std::chrono::seconds(5)) {
+    auto expiration = std::chrono::system_clock::now() + timeout;
+
+    EXPECT_NE(result, nullptr);
+    EXPECT_TRUE(future.valid());
+    if (result != nullptr && future.valid()) {
+        std::future_status status = future.wait_until(expiration);
+        EXPECT_NE(status, std::future_status::timeout) << "Timed out waiting for callback";
+
+        if (status == std::future_status::ready) {
+            *result = future.get();
+            return true;
+        }
+    }
+
+    return false;
+}
+
 }  // namespace vts_utils
 }  // namespace contexthub
 }  // namespace hardware
diff --git a/current.txt b/current.txt
index bf6829a..5e9a34c 100644
--- a/current.txt
+++ b/current.txt
@@ -769,7 +769,7 @@
 # ABI preserving changes to HALs during Android S
 e042522daa4b5f7fd4a0a19bcdadb93c79a1b04c09ef2c9813a3a8941032f3f5 android.hardware.contexthub@1.0::IContexthub
 c2f64133b83ede65c9939ef97ab5bd867b73faf3dba0e7e69f77c3c43d9e487e android.hardware.contexthub@1.0::IContexthubCallback
-1ca372cd67d197df099e87616a613ba6ede6552638a603e18f86c8834302c3d1 android.hardware.gnss@1.0::IGnssMeasurementCallback
+bda492ec4021d13869de72bd6f8c15c5837b78d6136b8d538efec5320573a5ec android.hardware.gnss@1.0::IGnssMeasurementCallback
 6a271e493907e8ba20912e42771bd0d99ae45431a851d5675ef9496d02510a34 android.hardware.gnss@1.1::IGnssMeasurementCallback
 2c331a9605f3a08d9c1e0a36169ca57758bc43c11a78ef3f3730509885e52c15 android.hardware.graphics.composer@2.4::IComposerClient
 3da3ce039247872d95c6bd48621dbfdfa1c2d2a91a90f257862f87ee2bc46300 android.hardware.health@2.1::types
@@ -779,8 +779,9 @@
 6017b4f2481feb0fffceae81c62bc372c898998b2d8fe69fbd39859d3a315e5e android.hardware.keymaster@4.0::IKeymasterDevice
 dabe23dde7c9e3ad65c61def7392f186d7efe7f4216f9b6f9cf0863745b1a9f4 android.hardware.keymaster@4.1::IKeymasterDevice
 cd84ab19c590e0e73dd2307b591a3093ee18147ef95e6d5418644463a6620076 android.hardware.neuralnetworks@1.2::IDevice
-9625e85f56515ad2cf87b6a1847906db669f746ea4ab02cd3d4ca25abc9b0109 android.hardware.neuralnetworks@1.2::types
-9e758e208d14f7256e0885d6d8ad0b61121b21d8c313864f981727ae55bffd16 android.hardware.neuralnetworks@1.3::types
+f729ee6a5f136b25d79ea6895d24700fce413df555baaecf2c39e4440d15d043 android.hardware.neuralnetworks@1.0::types
+c6ae443608502339aec4256feef48e7b2d36f7477ca5361cc95cd27a8ed9c612 android.hardware.neuralnetworks@1.2::types
+9fe5a4093043c2b5da4e9491aed1646c388a5d3059b8fd77d5b6a9807e6d3a3e android.hardware.neuralnetworks@1.3::types
 e8c86c69c438da8d1549856c1bb3e2d1b8da52722f8235ff49a30f2cce91742c android.hardware.soundtrigger@2.1::ISoundTriggerHwCallback
 b9fbb6e2e061ed0960939d48b785e9700210add1f13ed32ecd688d0f1ca20ef7 android.hardware.renderscript@1.0::types
 0f53d70e1eadf8d987766db4bf6ae2048004682168f4cab118da576787def3fa android.hardware.radio@1.0::types
diff --git a/drm/1.4/types.hal b/drm/1.4/types.hal
index 706c3aa..17eba8a 100644
--- a/drm/1.4/types.hal
+++ b/drm/1.4/types.hal
@@ -19,11 +19,14 @@
 import @1.2::Status;
 
 enum LogPriority : uint32_t {
-  ERROR,
-  WARN,
-  INFO,
-  DEBUG,
-  VERBOSE
+    UNKNOWN,
+    DEFAULT,
+    VERBOSE,
+    DEBUG,
+    INFO,
+    WARN,
+    ERROR,
+    FATAL,
 };
 
 /**
@@ -37,15 +40,100 @@
 };
 
 enum Status : @1.2::Status {
-
+    /**
+     * queueSecureInput buffer called with 0 subsamples.
+     */
+    CANNOT_DECRYPT_ZERO_SUBSAMPLES,
+    /**
+     * An error happened within the crypto library used by the drm plugin.
+     */
+    CRYPTO_LIBRARY_ERROR,
     /**
      * Non-specific error reported by the device OEM subsystem.
      */
     GENERAL_OEM_ERROR,
-
     /**
      * Unexpected internal failure in the drm/crypto plugin.
      */
     GENERAL_PLUGIN_ERROR,
-
+    /**
+     * The init data parameter passed to getKeyRequest is empty or invalid.
+     */
+    INIT_DATA_INVALID,
+    /**
+     * Either the key was not loaded from the license before attempting the
+     * operation, or the key ID parameter provided by the app is incorrect.
+     */
+    KEY_NOT_LOADED,
+    /**
+     * The license response was empty, fields are missing or otherwise unable
+     * to be parsed.
+     */
+    LICENSE_PARSE_ERROR,
+    /**
+     * The operation (e.g. to renew or persist a license) is prohibited by the
+     * license policy.
+     */
+    LICENSE_POLICY_ERROR,
+    /**
+     * Failed to generate a release request because a field in the stored
+     * license is empty or malformed.
+     */
+    LICENSE_RELEASE_ERROR,
+    /**
+     * The license server detected an error in the license request.
+     */
+    LICENSE_REQUEST_REJECTED,
+    /**
+     * Failed to restore an offline license because a field is empty or
+     * malformed.
+     */
+    LICENSE_RESTORE_ERROR,
+    /**
+     * License is in an invalid state for the attempted operation.
+     */
+    LICENSE_STATE_ERROR,
+    /**
+     * Certificate is malformed or is of the wrong type.
+     */
+    MALFORMED_CERTIFICATE,
+    /**
+     * Failure in the media framework.
+     */
+    MEDIA_FRAMEWORK_ERROR,
+    /**
+     * Certificate has not been set.
+     */
+    MISSING_CERTIFICATE,
+    /**
+     * There was an error loading the provisioned certificate.
+     */
+    PROVISIONING_CERTIFICATE_ERROR,
+    /**
+     * Required steps where not performed before provisioning was attempted.
+     */
+    PROVISIONING_CONFIGURATION_ERROR,
+    /**
+     * The provisioning response was empty, fields are missing or otherwise
+     * unable to be parsed.
+     */
+    PROVISIONING_PARSE_ERROR,
+    /**
+     * Provisioning failed in a way that is likely to succeed on a subsequent
+     * attempt.
+     */
+    RETRYABLE_PROVISIONING_ERROR,
+    /**
+     * Failed to generate a secure stop request because a field in the stored
+     * license is empty or malformed.
+     */
+    SECURE_STOP_RELEASE_ERROR,
+    /**
+     * The plugin was unable to read data from the filesystem.
+     */
+    STORAGE_READ_FAILURE,
+    /**
+     * The plugin was unable to write data to the filesystem.
+     */
+    STORAGE_WRITE_FAILURE,
 };
diff --git a/drm/1.4/vts/OWNERS b/drm/1.4/vts/OWNERS
new file mode 100644
index 0000000..3a0672e
--- /dev/null
+++ b/drm/1.4/vts/OWNERS
@@ -0,0 +1,9 @@
+conglin@google.com
+edwinwong@google.com
+fredgc@google.com
+jtinker@google.com
+juce@google.com
+kylealexander@google.com
+rfrias@google.com
+robertshih@google.com
+sigquit@google.com
diff --git a/drm/1.4/vts/functional/Android.bp b/drm/1.4/vts/functional/Android.bp
new file mode 100644
index 0000000..80b1dd1
--- /dev/null
+++ b/drm/1.4/vts/functional/Android.bp
@@ -0,0 +1,95 @@
+//
+// Copyright (C) 2021 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_library_static {
+    name: "android.hardware.drm@1.4-vts",
+    defaults: ["VtsHalTargetTestDefaults"],
+    local_include_dirs: [
+        "include",
+    ],
+    srcs: [
+        "drm_hal_test.cpp",
+    ],
+    shared_libs: [
+        "android.hardware.drm@1.0",
+        "android.hardware.drm@1.1",
+        "android.hardware.drm@1.2",
+        "android.hardware.drm@1.3",
+        "android.hardware.drm@1.4",
+        "android.hidl.allocator@1.0",
+        "android.hidl.memory@1.0",
+        "libhidlmemory",
+        "libnativehelper",
+    ],
+    static_libs: [
+        "android.hardware.drm@1.0-helper",
+        "android.hardware.drm@1.2-vts",
+        "libdrmvtshelper",
+    ],
+    export_static_lib_headers: [
+        "android.hardware.drm@1.2-vts",
+    ],
+    export_include_dirs: [
+        "include",
+    ],
+}
+
+cc_test {
+    name: "VtsHalDrmV1_4TargetTest",
+    defaults: ["VtsHalTargetTestDefaults"],
+    include_dirs: ["hardware/interfaces/drm/1.0/vts/functional"],
+    srcs: [
+        "drm_hal_test_main.cpp",
+    ],
+    whole_static_libs: [
+        "android.hardware.drm@1.4-vts",
+    ],
+    shared_libs: [
+        "android.hardware.drm@1.0",
+        "android.hardware.drm@1.1",
+        "android.hardware.drm@1.2",
+        "android.hardware.drm@1.3",
+        "android.hardware.drm@1.4",
+        "android.hidl.allocator@1.0",
+        "android.hidl.memory@1.0",
+        "libcrypto",
+        "libhidlmemory",
+        "libnativehelper",
+    ],
+    static_libs: [
+        "android.hardware.drm@1.0-helper",
+        "android.hardware.drm@1.2-vts",
+        "libdrmvtshelper",
+    ],
+    arch: {
+        arm: {
+            data: [":libvtswidevine-arm-prebuilts"],
+        },
+        arm64: {
+            data: [":libvtswidevine-arm64-prebuilts"],
+        },
+        x86: {
+            data: [":libvtswidevine-x86-prebuilts"],
+        },
+        x86_64: {
+            data: [":libvtswidevine-x86_64-prebuilts"],
+        },
+    },
+    test_suites: [
+        "general-tests",
+        "vts",
+    ],
+}
diff --git a/drm/1.4/vts/functional/AndroidTest.xml b/drm/1.4/vts/functional/AndroidTest.xml
new file mode 100644
index 0000000..b18da49
--- /dev/null
+++ b/drm/1.4/vts/functional/AndroidTest.xml
@@ -0,0 +1,38 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Copyright (C) 2021 The Android Open Source Project
+
+     Licensed under the Apache License, Version 2.0 (the "License");
+     you may not use this file except in compliance with the License.
+     You may obtain a copy of the License at
+
+          http://www.apache.org/licenses/LICENSE-2.0
+
+     Unless required by applicable law or agreed to in writing, software
+     distributed under the License is distributed on an "AS IS" BASIS,
+     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+     See the License for the specific language governing permissions and
+     limitations under the License.
+-->
+<configuration description="Runs VtsHalDrmV1_4TargetTest.">
+    <option name="test-suite-tag" value="apct" />
+    <option name="test-suite-tag" value="apct-native" />
+    <option name="not-shardable" value="true" />
+
+    <target_preparer class="com.android.tradefed.targetprep.RootTargetPreparer"/>
+
+    <target_preparer class="com.android.tradefed.targetprep.WifiPreparer" >
+        <option name="verify-only" value="true" />
+    </target_preparer>
+
+    <target_preparer class="com.android.tradefed.targetprep.PushFilePreparer">
+        <option name="cleanup" value="true" />
+        <option name="push-file" key="VtsHalDrmV1_4TargetTest" value="/data/local/tmp/VtsHalDrmV1_4TargetTest" />
+        <option name="push-file" key="libvtswidevine64.so" value="/data/local/tmp/64/lib/libvtswidevine.so" />
+        <option name="push-file" key="libvtswidevine32.so" value="/data/local/tmp/32/lib/libvtswidevine.so" />
+    </target_preparer>
+
+    <test class="com.android.tradefed.testtype.GTest" >
+        <option name="native-test-device-path" value="/data/local/tmp" />
+        <option name="module-name" value="VtsHalDrmV1_4TargetTest" />
+    </test>
+</configuration>
diff --git a/drm/1.4/vts/functional/drm_hal_test.cpp b/drm/1.4/vts/functional/drm_hal_test.cpp
new file mode 100644
index 0000000..ee6635b
--- /dev/null
+++ b/drm/1.4/vts/functional/drm_hal_test.cpp
@@ -0,0 +1,161 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "drm_hal_test@1.4"
+
+#include "android/hardware/drm/1.4/vts/drm_hal_test.h"
+
+namespace android {
+namespace hardware {
+namespace drm {
+namespace V1_4 {
+namespace vts {
+
+const char* const DrmHalTest::kVideoMp4 = "video/mp4";
+const char* const DrmHalTest::kAudioMp4 = "audio/mp4";
+const uint32_t DrmHalTest::kSecLevelDefault = DrmHalTest::kSecLevelMax + 1;
+
+sp<drm::V1_4::IDrmPlugin> DrmHalTest::DrmPluginV1_4() const {
+    sp<drm::V1_4::IDrmPlugin> plugin(drm::V1_4::IDrmPlugin::castFrom(drmPlugin));
+    EXPECT_NE(nullptr, plugin.get());
+    return plugin;
+}
+
+sp<V1_0::ICryptoPlugin> DrmHalTest::CryptoPlugin(const SessionId& sid) {
+    sp<V1_0::ICryptoPlugin> crypto;
+    auto res = cryptoFactory->createPlugin(
+        getUUID(), sid,
+        [&](V1_0::Status status, const sp<V1_0::ICryptoPlugin>& plugin) {
+            EXPECT_EQ(V1_0::Status::OK, status);
+            EXPECT_NE(nullptr, plugin.get());
+            crypto = plugin;
+        });
+    EXPECT_OK(res);
+    return crypto;
+}
+
+SessionId DrmHalTest::OpenSession(uint32_t level = kSecLevelDefault) {
+    V1_0::Status err;
+    SessionId sessionId;
+    bool attemptedProvision = false;
+
+    V1_0::IDrmPlugin::openSession_cb cb = [&](
+            V1_0::Status status,
+            const hidl_vec<unsigned char> &id) {
+        err = status;
+        sessionId = id;
+    };
+
+    while (true) {
+        Return<void> res;
+        if (level > kSecLevelMax) {
+            res = drmPlugin->openSession(cb);
+        } else if (level >= kSecLevelMin) {
+            auto securityLevel = static_cast<SecurityLevel>(level);
+            res = drmPlugin->openSession_1_1(securityLevel, cb);
+        }
+        EXPECT_OK(res);
+        if (V1_0::Status::ERROR_DRM_NOT_PROVISIONED == err
+                && !attemptedProvision) {
+            // provision once if necessary
+            provision();
+            attemptedProvision = true;
+            continue;
+        } else if (V1_0::Status::ERROR_DRM_CANNOT_HANDLE == err) {
+            // must be able to handle default level
+            EXPECT_NE(kSecLevelDefault, level);
+            sessionId = {};
+        } else {
+            EXPECT_EQ(V1_0::Status::OK, err);
+            EXPECT_NE(sessionId.size(), 0u);
+        }
+        break;
+    }
+
+    return sessionId;
+}
+
+TEST_P(DrmHalTest, RequiresSecureDecoder) {
+    for (uint32_t level : {kSecLevelMin, kSecLevelMax, kSecLevelDefault}) {
+        for (auto mime : {kVideoMp4, kAudioMp4}) {
+            auto sid = OpenSession(level);
+            if (sid.size() == 0u) {
+                continue;
+            }
+            auto drm = DrmPluginV1_4();
+            sp<V1_0::ICryptoPlugin> crypto(CryptoPlugin(sid));
+            if (drm == nullptr || crypto == nullptr) {
+                continue;
+            }
+            bool r1 = crypto->requiresSecureDecoderComponent(mime);
+            bool r2;
+            if (level == kSecLevelDefault) {
+                r2 = drm->requiresSecureDecoderDefault(mime);
+            } else {
+                auto sL = static_cast<SecurityLevel>(level);
+                r2 = drm->requiresSecureDecoder(mime, sL);
+            }
+            EXPECT_EQ(r1, r2);
+            closeSession(sid);
+        }
+    }
+}
+
+TEST_P(DrmHalTest, SetPlaybackId) {
+    auto testInfo = ::testing::UnitTest::GetInstance()->current_test_info();
+    auto testName = testInfo->name();
+    const hidl_string& pbId{testName};
+    auto sid = OpenSession();
+    auto drm = DrmPluginV1_4();
+    if (drm == nullptr) {
+        return;
+    }
+    V1_0::Status err = drm->setPlaybackId(sid, pbId);
+    EXPECT_EQ(V1_0::Status::OK, err);
+    closeSession(sid);
+
+    // search for playback id among metric attributes/values
+    bool foundPbId = false;
+    auto res = drmPlugin->getMetrics([&](
+            V1_0::Status status,
+            hidl_vec<V1_1::DrmMetricGroup> metricGroups) {
+        EXPECT_EQ(V1_0::Status::OK, status);
+        for (const auto& group : metricGroups) {
+            for (const auto& metric : group.metrics) {
+                for (const auto& value : metric.values) {
+                    if (value.stringValue == pbId) {
+                        foundPbId = true;
+                        break;
+                    }
+                }
+                for (const auto& attr : metric.attributes) {
+                    if (attr.stringValue == pbId) {
+                        foundPbId = true;
+                        break;
+                    }
+                }
+            }
+        }
+    });
+    EXPECT_OK(res);
+    EXPECT_TRUE(foundPbId);
+}
+
+}  // namespace vts
+}  // namespace V1_4
+}  // namespace drm
+}  // namespace hardware
+}  // namespace android
diff --git a/drm/1.4/vts/functional/drm_hal_test_main.cpp b/drm/1.4/vts/functional/drm_hal_test_main.cpp
new file mode 100644
index 0000000..65d1b76
--- /dev/null
+++ b/drm/1.4/vts/functional/drm_hal_test_main.cpp
@@ -0,0 +1,94 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/**
+ * Instantiate the set of test cases for each vendor module
+ */
+
+#define LOG_TAG "drm_hal_test@1.4"
+
+#include <android/hardware/drm/1.4/ICryptoFactory.h>
+#include <android/hardware/drm/1.4/IDrmFactory.h>
+#include <gtest/gtest.h>
+#include <hidl/HidlSupport.h>
+#include <hidl/ServiceManagement.h>
+#include <log/log.h>
+
+#include <algorithm>
+#include <iterator>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "android/hardware/drm/1.4/vts/drm_hal_test.h"
+
+using drm_vts::DrmHalTestParam;
+using drm_vts::PrintParamInstanceToString;
+
+using android::hardware::drm::V1_4::vts::DrmHalTest;
+
+static const std::vector<DrmHalTestParam> kAllInstances = [] {
+    using ::android::hardware::hidl_array;
+    using ::android::hardware::hidl_vec;
+    using ::android::hardware::drm::V1_4::ICryptoFactory;
+    using ::android::hardware::drm::V1_4::IDrmFactory;
+
+    std::vector<std::string> drmInstances =
+            android::hardware::getAllHalInstanceNames(IDrmFactory::descriptor);
+    std::vector<std::string> cryptoInstances =
+            android::hardware::getAllHalInstanceNames(ICryptoFactory::descriptor);
+    std::set<std::string> allInstances;
+    allInstances.insert(drmInstances.begin(), drmInstances.end());
+    allInstances.insert(cryptoInstances.begin(), cryptoInstances.end());
+
+    std::vector<DrmHalTestParam> firstInstanceUuidCombos;
+    for (const auto &instance : allInstances) {
+        auto drmFactory = IDrmFactory::getService(instance);
+        if (drmFactory == nullptr) {
+            continue;
+        }
+        drmFactory->getSupportedCryptoSchemes(
+            [&](const hidl_vec<hidl_array<uint8_t, 16>>& schemes) {
+                if (schemes.size() > 0) {
+                    firstInstanceUuidCombos.push_back(DrmHalTestParam(instance, schemes[0]));
+                }
+            });
+    }
+    return firstInstanceUuidCombos;
+}();
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(DrmHalTest);
+INSTANTIATE_TEST_SUITE_P(PerInstance, DrmHalTest,
+                         testing::ValuesIn(kAllInstances),
+                         PrintParamInstanceToString);
+
+int main(int argc, char** argv) {
+#if defined(__LP64__)
+    const char* kModulePath = "/data/local/tmp/64/lib";
+#else
+    const char* kModulePath = "/data/local/tmp/32/lib";
+#endif
+    DrmHalTest::gVendorModules
+            = new drm_vts::VendorModules(kModulePath);
+    if (DrmHalTest::gVendorModules->getPathList().size() == 0) {
+        std::cerr << "WARNING: No vendor modules found in " << kModulePath <<
+                ", all vendor tests will be skipped" << std::endl;
+    }
+    ::testing::InitGoogleTest(&argc, argv);
+    int status = RUN_ALL_TESTS();
+    ALOGI("Test result = %d", status);
+    return status;
+}
diff --git a/drm/1.4/vts/functional/include/android/hardware/drm/1.4/vts/drm_hal_test.h b/drm/1.4/vts/functional/include/android/hardware/drm/1.4/vts/drm_hal_test.h
new file mode 100644
index 0000000..ed49a61
--- /dev/null
+++ b/drm/1.4/vts/functional/include/android/hardware/drm/1.4/vts/drm_hal_test.h
@@ -0,0 +1,83 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef DRM_HAL_TEST_V1_4_H
+#define DRM_HAL_TEST_V1_4_H
+
+#include <android/hardware/drm/1.0/IDrmPlugin.h>
+#include <android/hardware/drm/1.3/IDrmFactory.h>
+#include <android/hardware/drm/1.4/ICryptoFactory.h>
+#include <android/hardware/drm/1.4/ICryptoPlugin.h>
+#include <android/hardware/drm/1.4/IDrmFactory.h>
+#include <android/hardware/drm/1.4/IDrmPlugin.h>
+#include <gtest/gtest.h>
+#include <hidl/HidlSupport.h>
+#include <hidl/ServiceManagement.h>
+#include <log/log.h>
+
+#include <algorithm>
+#include <cstdint>
+#include <iterator>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "drm_hal_vendor_module_api.h"
+#include "drm_vts_helper.h"
+#include "vendor_modules.h"
+#include "VtsHalHidlTargetCallbackBase.h"
+
+#include "android/hardware/drm/1.2/vts/drm_hal_common.h"
+
+namespace android {
+namespace hardware {
+namespace drm {
+namespace V1_4 {
+namespace vts {
+
+namespace drm = ::android::hardware::drm;
+using android::hardware::hidl_array;
+using android::hardware::hidl_string;
+using V1_0::SessionId;
+using V1_1::SecurityLevel;
+
+using drm_vts::DrmHalTestParam;
+
+class DrmHalTest : public drm::V1_2::vts::DrmHalTest {
+public:
+  using drm::V1_2::vts::DrmHalTest::DrmHalTest;
+  static const char* const kVideoMp4;
+  static const char* const kAudioMp4;
+  static const uint32_t kSecLevelMin = static_cast<uint32_t>(SecurityLevel::SW_SECURE_CRYPTO);
+  static const uint32_t kSecLevelMax = static_cast<uint32_t>(SecurityLevel::HW_SECURE_ALL);
+  static const uint32_t kSecLevelDefault;
+
+protected:
+  sp<V1_4::IDrmPlugin> DrmPluginV1_4() const;
+  sp<V1_0::ICryptoPlugin> CryptoPlugin(const SessionId& sid);
+  SessionId OpenSession(uint32_t level);
+
+private:
+  void DoProvisioning();
+};
+
+}  // namespace vts
+}  // namespace V1_4
+}  // namespace drm
+}  // namespace hardware
+}  // namespace android
+
+#endif  // DRM_HAL_TEST_V1_4_H
diff --git a/gnss/1.0/IGnssMeasurementCallback.hal b/gnss/1.0/IGnssMeasurementCallback.hal
index d219af0..603680d 100644
--- a/gnss/1.0/IGnssMeasurementCallback.hal
+++ b/gnss/1.0/IGnssMeasurementCallback.hal
@@ -644,22 +644,19 @@
          */
         double snrDb;
 
-        /**
-         * Automatic gain control (AGC) level. AGC acts as a variable gain
-         * amplifier adjusting the power of the incoming signal. The AGC level
-         * may be used to indicate potential interference. When AGC is at a
-         * nominal level, this value must be set as 0. Higher gain (and/or lower
-         * input power) must be output as a positive number. Hence in cases of
-         * strong jamming, in the band of this signal, this value must go more
-         * negative.
-         *
-         * Note: Different hardware designs (e.g. antenna, pre-amplification, or
-         * other RF HW components) may also affect the typical output of of this
-         * value on any given hardware design in an open sky test - the
-         * important aspect of this output is that changes in this value are
-         * indicative of changes on input signal power in the frequency band for
-         * this measurement.
-         */
+
+    /**
+     * Automatic gain control (AGC) level. AGC acts as a variable gain amplifier adjusting the power
+     * of the incoming signal. The AGC level may be used to indicate potential interference. Higher
+     * gain (and/or lower input power) must be output as a positive number. Hence in cases of strong
+     * jamming, in the band of this signal, this value must go more negative. This value must be
+     * consistent given the same level of the incoming signal power.
+     *
+     * Note: Different hardware designs (e.g. antenna, pre-amplification, or other RF HW components)
+     * may also affect the typical output of this value on any given hardware design in an open sky
+     * test - the important aspect of this output is that changes in this value are indicative of
+     * changes on input signal power in the frequency band for this measurement.
+     */
         double agcLevelDb;
     };
 
diff --git a/gnss/aidl/android/hardware/gnss/GnssMeasurement.aidl b/gnss/aidl/android/hardware/gnss/GnssMeasurement.aidl
index 2c56a41..4468b63 100644
--- a/gnss/aidl/android/hardware/gnss/GnssMeasurement.aidl
+++ b/gnss/aidl/android/hardware/gnss/GnssMeasurement.aidl
@@ -547,20 +547,16 @@
     double snrDb;
 
     /**
-     * Automatic gain control (AGC) level. AGC acts as a variable gain
-     * amplifier adjusting the power of the incoming signal. The AGC level
-     * may be used to indicate potential interference. When AGC is at a
-     * nominal level, this value must be set as 0. Higher gain (and/or lower
-     * input power) must be output as a positive number. Hence in cases of
-     * strong jamming, in the band of this signal, this value must go more
-     * negative.
+     * Automatic gain control (AGC) level. AGC acts as a variable gain amplifier adjusting the power
+     * of the incoming signal. The AGC level may be used to indicate potential interference. Higher
+     * gain (and/or lower input power) must be output as a positive number. Hence in cases of strong
+     * jamming, in the band of this signal, this value must go more negative. This value must be
+     * consistent given the same level of the incoming signal power.
      *
-     * Note: Different hardware designs (e.g. antenna, pre-amplification, or
-     * other RF HW components) may also affect the typical output of this
-     * value on any given hardware design in an open sky test - the
-     * important aspect of this output is that changes in this value are
-     * indicative of changes on input signal power in the frequency band for
-     * this measurement.
+     * Note: Different hardware designs (e.g. antenna, pre-amplification, or other RF HW components)
+     * may also affect the typical output of this value on any given hardware design in an open sky
+     * test - the important aspect of this output is that changes in this value are indicative of
+     * changes on input signal power in the frequency band for this measurement.
      */
     double agcLevelDb;
 
diff --git a/health/utils/libhealth2impl/Health.cpp b/health/utils/libhealth2impl/Health.cpp
index f4684ae..035b36f 100644
--- a/health/utils/libhealth2impl/Health.cpp
+++ b/health/utils/libhealth2impl/Health.cpp
@@ -80,14 +80,14 @@
 
 Return<Result> Health::update() {
     Result result = Result::UNKNOWN;
-    getHealthInfo_2_1([&](auto res, const auto& /* health_info */) {
+    getHealthInfo_2_1([&](auto res, const auto& health_info) {
         result = res;
         if (res != Result::SUCCESS) {
             LOG(ERROR) << "Cannot call getHealthInfo_2_1: " << toString(res);
             return;
         }
 
-        battery_monitor_.logValues();
+        BatteryMonitor::logValues(health_info, *healthd_config_);
     });
     return result;
 }
diff --git a/identity/support/src/IdentityCredentialSupport.cpp b/identity/support/src/IdentityCredentialSupport.cpp
index 38348ac..6418028 100644
--- a/identity/support/src/IdentityCredentialSupport.cpp
+++ b/identity/support/src/IdentityCredentialSupport.cpp
@@ -833,9 +833,16 @@
 optional<vector<vector<uint8_t>>> createAttestation(
         const EVP_PKEY* key, const vector<uint8_t>& applicationId, const vector<uint8_t>& challenge,
         uint64_t activeTimeMilliSeconds, uint64_t expireTimeMilliSeconds, bool isTestCredential) {
+    // Pretend to be implemented in a trusted environment just so we can pass
+    // the VTS tests. Of course, this is a pretend-only game since hopefully no
+    // relying party is ever going to trust our batch key and those keys above
+    // it.
+    ::keymaster::PureSoftKeymasterContext context(::keymaster::KmVersion::KEYMASTER_4_1,
+                                                  KM_SECURITY_LEVEL_TRUSTED_ENVIRONMENT);
+
     keymaster_error_t error;
     ::keymaster::CertificateChain attestation_chain =
-            ::keymaster::getAttestationChain(KM_ALGORITHM_EC, &error);
+            context.GetAttestationChain(KM_ALGORITHM_EC, &error);
     if (KM_ERROR_OK != error) {
         LOG(ERROR) << "Error getting attestation chain " << error;
         return {};
@@ -855,12 +862,6 @@
         }
         expireTimeMilliSeconds = bcNotAfter * 1000;
     }
-    const keymaster_key_blob_t* attestation_signing_key =
-            ::keymaster::getAttestationKey(KM_ALGORITHM_EC, nullptr);
-    if (attestation_signing_key == nullptr) {
-        LOG(ERROR) << "Error getting attestation key";
-        return {};
-    }
 
     ::keymaster::X509_NAME_Ptr subjectName;
     if (KM_ERROR_OK !=
@@ -874,8 +875,11 @@
 
     i2d_X509_NAME(subjectName.get(), &subjectPtr);
 
+    uint64_t nowMilliSeconds = time(nullptr) * 1000;
     ::keymaster::AuthorizationSet auth_set(
             ::keymaster::AuthorizationSetBuilder()
+                    .Authorization(::keymaster::TAG_CERTIFICATE_NOT_BEFORE, nowMilliSeconds)
+                    .Authorization(::keymaster::TAG_CERTIFICATE_NOT_AFTER, expireTimeMilliSeconds)
                     .Authorization(::keymaster::TAG_ATTESTATION_CHALLENGE, challenge.data(),
                                    challenge.size())
                     .Authorization(::keymaster::TAG_ACTIVE_DATETIME, activeTimeMilliSeconds)
@@ -914,19 +918,11 @@
     }
     ::keymaster::AuthorizationSet hwEnforced(hwEnforcedBuilder);
 
-    // Pretend to be implemented in a trusted environment just so we can pass
-    // the VTS tests. Of course, this is a pretend-only game since hopefully no
-    // relying party is ever going to trust our batch key and those keys above
-    // it.
-    ::keymaster::PureSoftKeymasterContext context(::keymaster::KmVersion::KEYMASTER_4_1,
-                                                  KM_SECURITY_LEVEL_TRUSTED_ENVIRONMENT);
-
-    ::keymaster::CertificateChain cert_chain_out = generate_attestation_from_EVP(
-            key, swEnforced, hwEnforced, auth_set, context, move(attestation_chain),
-            *attestation_signing_key, &error);
+    ::keymaster::CertificateChain cert_chain_out = generate_attestation(
+            key, swEnforced, hwEnforced, auth_set, {} /* attest_key */, context, &error);
 
     if (KM_ERROR_OK != error) {
-        LOG(ERROR) << "Error generate attestation from EVP key" << error;
+        LOG(ERROR) << "Error generating attestation from EVP key: " << error;
         return {};
     }
 
diff --git a/media/omx/1.0/vts/functional/common/media_hidl_test_common.cpp b/media/omx/1.0/vts/functional/common/media_hidl_test_common.cpp
index 9184c56..ea29f03 100644
--- a/media/omx/1.0/vts/functional/common/media_hidl_test_common.cpp
+++ b/media/omx/1.0/vts/functional/common/media_hidl_test_common.cpp
@@ -215,6 +215,7 @@
     ASSERT_NE(handle, nullptr);
 
     *nStride = static_cast<int32_t>(stride);
+    buffer->handle = handle;
     buffer->omxBuffer.nativeHandle = handle;
     buffer->omxBuffer.attr.anwBuffer.width = nFrameWidth;
     buffer->omxBuffer.attr.anwBuffer.height = nFrameHeight;
@@ -335,6 +336,18 @@
     }
 }
 
+// free buffers needed on a component port
+void freePortBuffers(android::Vector<BufferInfo>* buffArray, PortMode portMode, bool allocGrap) {
+    for (size_t i = 0; i < buffArray->size(); i++) {
+        if (portMode == PortMode::PRESET_ANW_BUFFER ||
+            (allocGrap && portMode == PortMode::DYNAMIC_ANW_BUFFER)) {
+            android::GraphicBufferAllocator& allocator = android::GraphicBufferAllocator::get();
+            android::status_t error = allocator.free((*buffArray)[i].handle);
+            ASSERT_EQ(error, android::NO_ERROR);
+        }
+    }
+}
+
 // State Transition : Loaded -> Idle
 // Note: This function does not make any background checks for this transition.
 // The callee holds the reponsibility to ensure the legality of the transition.
@@ -399,11 +412,15 @@
 // The callee holds the reponsibility to ensure the legality of the transition.
 void changeStateIdletoLoaded(sp<IOmxNode> omxNode, sp<CodecObserver> observer,
                              android::Vector<BufferInfo>* iBuffer,
-                             android::Vector<BufferInfo>* oBuffer,
-                             OMX_U32 kPortIndexInput,
-                             OMX_U32 kPortIndexOutput) {
+                             android::Vector<BufferInfo>* oBuffer, OMX_U32 kPortIndexInput,
+                             OMX_U32 kPortIndexOutput, PortMode* portMode, bool allocGrap) {
     android::hardware::media::omx::V1_0::Status status;
     Message msg;
+    PortMode defaultPortMode[2], *pm;
+
+    defaultPortMode[0] = PortMode::PRESET_BYTE_BUFFER;
+    defaultPortMode[1] = PortMode::PRESET_BYTE_BUFFER;
+    pm = portMode ? portMode : defaultPortMode;
 
     // set state to Loaded
     status = omxNode->sendCommand(toRawCommandType(OMX_CommandStateSet),
@@ -446,6 +463,8 @@
     ASSERT_EQ(msg.data.eventData.data1, OMX_CommandStateSet);
     ASSERT_EQ(msg.data.eventData.data2, OMX_StateLoaded);
 
+    ASSERT_NO_FATAL_FAILURE(freePortBuffers(iBuffer, pm[0], allocGrap));
+    ASSERT_NO_FATAL_FAILURE(freePortBuffers(oBuffer, pm[1], allocGrap));
     return;
 }
 
diff --git a/media/omx/1.0/vts/functional/common/media_hidl_test_common.h b/media/omx/1.0/vts/functional/common/media_hidl_test_common.h
index b16c772..eddf83f 100644
--- a/media/omx/1.0/vts/functional/common/media_hidl_test_common.h
+++ b/media/omx/1.0/vts/functional/common/media_hidl_test_common.h
@@ -115,6 +115,7 @@
 struct BufferInfo {
     uint32_t id;
     bufferOwner owner;
+    buffer_handle_t handle;
     android::hardware::media::omx::V1_0::CodecBuffer omxBuffer;
     ::android::sp<IMemory> mMemory;
     int32_t slot;
@@ -329,6 +330,9 @@
                          PortMode portMode = PortMode::PRESET_BYTE_BUFFER,
                          bool allocGrap = false);
 
+void freePortBuffers(android::Vector<BufferInfo>* buffArray, PortMode portMode,
+                     bool allocGrap = false);
+
 void changeStateLoadedtoIdle(sp<IOmxNode> omxNode, sp<CodecObserver> observer,
                              android::Vector<BufferInfo>* iBuffer,
                              android::Vector<BufferInfo>* oBuffer,
@@ -338,8 +342,9 @@
 
 void changeStateIdletoLoaded(sp<IOmxNode> omxNode, sp<CodecObserver> observer,
                              android::Vector<BufferInfo>* iBuffer,
-                             android::Vector<BufferInfo>* oBuffer,
-                             OMX_U32 kPortIndexInput, OMX_U32 kPortIndexOutput);
+                             android::Vector<BufferInfo>* oBuffer, OMX_U32 kPortIndexInput,
+                             OMX_U32 kPortIndexOutput, PortMode* portMode = nullptr,
+                             bool allocGrap = false);
 
 void changeStateIdletoExecute(sp<IOmxNode> omxNode, sp<CodecObserver> observer);
 
diff --git a/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoDecTest.cpp b/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoDecTest.cpp
index 67b9895..d35ce65 100644
--- a/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoDecTest.cpp
+++ b/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoDecTest.cpp
@@ -451,6 +451,7 @@
                     status,
                     android::hardware::media::omx::V1_0::Status::TIMED_OUT);
 
+                ASSERT_NO_FATAL_FAILURE(freePortBuffers(oBuffer, oPortMode, true));
                 ASSERT_NO_FATAL_FAILURE(allocatePortBuffers(
                     omxNode, oBuffer, kPortIndexOutput, oPortMode, true));
                 status = observer->dequeueMessage(&msg, DEFAULT_TIMEOUT,
@@ -853,9 +854,9 @@
     ASSERT_NO_FATAL_FAILURE(
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode,
+                                                    true));
 }
 
 // Test for adaptive playback support
@@ -1001,9 +1002,9 @@
     ASSERT_NO_FATAL_FAILURE(
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode,
+                                                    true));
 }
 
 // end of sequence test
@@ -1067,9 +1068,9 @@
     ASSERT_NO_FATAL_FAILURE(
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode,
+                                                    true));
 }
 
 // end of sequence test
@@ -1188,9 +1189,9 @@
     ASSERT_NO_FATAL_FAILURE(
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode,
+                                                    true));
 }
 
 // end of sequence test
@@ -1295,9 +1296,9 @@
     ASSERT_NO_FATAL_FAILURE(
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode,
+                                                    true));
 }
 
 // test input/output port flush
@@ -1414,9 +1415,9 @@
     ASSERT_NO_FATAL_FAILURE(
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode,
+                                                    true));
 }
 
 GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(VideoDecHidlTest);
diff --git a/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoEncTest.cpp b/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoEncTest.cpp
index 3c0734e..f24c6d1 100644
--- a/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoEncTest.cpp
+++ b/media/omx/1.0/vts/functional/video/VtsHalMediaOmxV1_0TargetVideoEncTest.cpp
@@ -1057,9 +1057,9 @@
     ASSERT_NO_FATAL_FAILURE(changeStateExecutetoIdle(
         omxNode, observer, &buffersource->iBuffer, &buffersource->oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(
-        omxNode, observer, &buffersource->iBuffer, &buffersource->oBuffer,
-        kPortIndexInput, kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &buffersource->iBuffer,
+                                                    &buffersource->oBuffer, kPortIndexInput,
+                                                    kPortIndexOutput, portMode));
     // test for callbacks
     EXPECT_EQ(buffersource->callback, 31);
 }
@@ -1174,9 +1174,8 @@
     ASSERT_NO_FATAL_FAILURE(
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode));
 }
 
 // test raw stream encode (input is ANW buffers)
@@ -1337,9 +1336,8 @@
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     EXPECT_EQ(portDef.nBufferCountActual, listener->freeBuffers);
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode));
 
     returnval = producer->disconnect(
         NATIVE_WINDOW_API_CPU, IGraphicBufferProducer::DisconnectMode::API);
@@ -1452,9 +1450,8 @@
         changeStateExecutetoIdle(omxNode, observer, &iBuffer, &oBuffer));
     EXPECT_EQ(portDef.nBufferCountActual, listener->freeBuffers);
     // set state to executing
-    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer,
-                                                    &oBuffer, kPortIndexInput,
-                                                    kPortIndexOutput));
+    ASSERT_NO_FATAL_FAILURE(changeStateIdletoLoaded(omxNode, observer, &iBuffer, &oBuffer,
+                                                    kPortIndexInput, kPortIndexOutput, portMode));
 
     returnval = producer->disconnect(
         NATIVE_WINDOW_API_CPU, IGraphicBufferProducer::DisconnectMode::API);
diff --git a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/DeviceInfo.aidl b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/DeviceInfo.aidl
index 00abff9..3e25c56 100644
--- a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/DeviceInfo.aidl
+++ b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/DeviceInfo.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
 // THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
 ///////////////////////////////////////////////////////////////////////////////
 
-// This file is a snapshot of an AIDL interface (or parcelable). Do not try to
-// edit this file. It looks like you are doing that because you have modified
-// an AIDL interface in a backward-incompatible way, e.g., deleting a function
-// from an interface or a field from a parcelable and it broke the build. That
-// breakage is intended.
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
 //
-// You must not make a backward incompatible changes to the AIDL files built
+// You must not make a backward incompatible change to any AIDL file built
 // with the aidl_interface module type with versions property set. The module
 // type is used to build AIDL files in a way that they can be used across
 // independently updatable components of the system. If a device is shipped
diff --git a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/IMemtrack.aidl b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/IMemtrack.aidl
index 844a1bb..2e2b68e 100644
--- a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/IMemtrack.aidl
+++ b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/IMemtrack.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
 // THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
 ///////////////////////////////////////////////////////////////////////////////
 
-// This file is a snapshot of an AIDL interface (or parcelable). Do not try to
-// edit this file. It looks like you are doing that because you have modified
-// an AIDL interface in a backward-incompatible way, e.g., deleting a function
-// from an interface or a field from a parcelable and it broke the build. That
-// breakage is intended.
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
 //
-// You must not make a backward incompatible changes to the AIDL files built
+// You must not make a backward incompatible change to any AIDL file built
 // with the aidl_interface module type with versions property set. The module
 // type is used to build AIDL files in a way that they can be used across
 // independently updatable components of the system. If a device is shipped
diff --git a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackRecord.aidl b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackRecord.aidl
index 09ecefc..0e15ce3 100644
--- a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackRecord.aidl
+++ b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackRecord.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
 // THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
 ///////////////////////////////////////////////////////////////////////////////
 
-// This file is a snapshot of an AIDL interface (or parcelable). Do not try to
-// edit this file. It looks like you are doing that because you have modified
-// an AIDL interface in a backward-incompatible way, e.g., deleting a function
-// from an interface or a field from a parcelable and it broke the build. That
-// breakage is intended.
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
 //
-// You must not make a backward incompatible changes to the AIDL files built
+// You must not make a backward incompatible change to any AIDL file built
 // with the aidl_interface module type with versions property set. The module
 // type is used to build AIDL files in a way that they can be used across
 // independently updatable components of the system. If a device is shipped
diff --git a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackType.aidl b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackType.aidl
index 7f3f939..b19869e 100644
--- a/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackType.aidl
+++ b/memtrack/aidl/aidl_api/android.hardware.memtrack/current/android/hardware/memtrack/MemtrackType.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
 // THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
 ///////////////////////////////////////////////////////////////////////////////
 
-// This file is a snapshot of an AIDL interface (or parcelable). Do not try to
-// edit this file. It looks like you are doing that because you have modified
-// an AIDL interface in a backward-incompatible way, e.g., deleting a function
-// from an interface or a field from a parcelable and it broke the build. That
-// breakage is intended.
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
 //
-// You must not make a backward incompatible changes to the AIDL files built
+// You must not make a backward incompatible change to any AIDL file built
 // with the aidl_interface module type with versions property set. The module
 // type is used to build AIDL files in a way that they can be used across
 // independently updatable components of the system. If a device is shipped
@@ -23,5 +38,4 @@
   GRAPHICS = 2,
   MULTIMEDIA = 3,
   CAMERA = 4,
-  NUM_TYPES = 5,
 }
diff --git a/memtrack/aidl/android/hardware/memtrack/MemtrackType.aidl b/memtrack/aidl/android/hardware/memtrack/MemtrackType.aidl
index 715c6bf..5db735a 100644
--- a/memtrack/aidl/android/hardware/memtrack/MemtrackType.aidl
+++ b/memtrack/aidl/android/hardware/memtrack/MemtrackType.aidl
@@ -27,5 +27,4 @@
     GRAPHICS = 2,
     MULTIMEDIA = 3,
     CAMERA = 4,
-    NUM_TYPES,
 }
diff --git a/memtrack/aidl/default/Memtrack.cpp b/memtrack/aidl/default/Memtrack.cpp
index 000b25c..49a6582 100644
--- a/memtrack/aidl/default/Memtrack.cpp
+++ b/memtrack/aidl/default/Memtrack.cpp
@@ -26,7 +26,8 @@
     if (pid < 0) {
         return ndk::ScopedAStatus(AStatus_fromExceptionCode(EX_ILLEGAL_ARGUMENT));
     }
-    if (type < MemtrackType::OTHER || type >= MemtrackType::NUM_TYPES) {
+    if (type != MemtrackType::OTHER && type != MemtrackType::GL && type != MemtrackType::GRAPHICS &&
+        type != MemtrackType::MULTIMEDIA && type != MemtrackType::CAMERA) {
         return ndk::ScopedAStatus(AStatus_fromExceptionCode(EX_UNSUPPORTED_OPERATION));
     }
     _aidl_return->clear();
diff --git a/memtrack/aidl/vts/Android.bp b/memtrack/aidl/vts/Android.bp
index df87db8..eff2a56 100644
--- a/memtrack/aidl/vts/Android.bp
+++ b/memtrack/aidl/vts/Android.bp
@@ -13,6 +13,6 @@
         "android.hardware.memtrack-V1-ndk_platform",
     ],
     test_suites: [
-        "vts-core",
+        "vts",
     ],
 }
diff --git a/memtrack/aidl/vts/VtsHalMemtrackTargetTest.cpp b/memtrack/aidl/vts/VtsHalMemtrackTargetTest.cpp
index d5f4612..8905f50 100644
--- a/memtrack/aidl/vts/VtsHalMemtrackTargetTest.cpp
+++ b/memtrack/aidl/vts/VtsHalMemtrackTargetTest.cpp
@@ -46,17 +46,19 @@
 
 TEST_P(MemtrackAidlTest, GetMemoryInvalidPid) {
     int pid = -1;
-    MemtrackType type = MemtrackType::OTHER;
-    std::vector<MemtrackRecord> records;
 
-    auto status = memtrack_->getMemory(pid, type, &records);
+    for (MemtrackType type : ndk::enum_range<MemtrackType>()) {
+        std::vector<MemtrackRecord> records;
 
-    EXPECT_EQ(status.getExceptionCode(), EX_ILLEGAL_ARGUMENT);
+        auto status = memtrack_->getMemory(pid, type, &records);
+
+        EXPECT_EQ(status.getExceptionCode(), EX_ILLEGAL_ARGUMENT);
+    }
 }
 
 TEST_P(MemtrackAidlTest, GetMemoryInvalidType) {
     int pid = 1;
-    MemtrackType type = MemtrackType::NUM_TYPES;
+    MemtrackType type = static_cast<MemtrackType>(-1);
     std::vector<MemtrackRecord> records;
 
     auto status = memtrack_->getMemory(pid, type, &records);
@@ -66,12 +68,13 @@
 
 TEST_P(MemtrackAidlTest, GetMemory) {
     int pid = 1;
-    MemtrackType type = MemtrackType::OTHER;
-    std::vector<MemtrackRecord> records;
+    for (MemtrackType type : ndk::enum_range<MemtrackType>()) {
+        std::vector<MemtrackRecord> records;
 
-    auto status = memtrack_->getMemory(pid, type, &records);
+        auto status = memtrack_->getMemory(pid, type, &records);
 
-    EXPECT_TRUE(status.isOk());
+        EXPECT_TRUE(status.isOk());
+    }
 }
 
 TEST_P(MemtrackAidlTest, GetGpuDeviceInfo) {
@@ -87,7 +90,7 @@
                                                ->getRuntimeInfo(RuntimeInfo::FetchFlag::CPU_VERSION)
                                                ->kernelVersion();
         EXPECT_LT(kernel_version, min_kernel_version)
-                << "Devices with 5.10 or later kernels must implement getGpuDeviceInfo()";
+                << "Devices with 5.4 or later kernels must implement getGpuDeviceInfo()";
         return;
     }
 
diff --git a/neuralnetworks/1.0/types.hal b/neuralnetworks/1.0/types.hal
index 620eefb..5bfadd3 100644
--- a/neuralnetworks/1.0/types.hal
+++ b/neuralnetworks/1.0/types.hal
@@ -308,8 +308,9 @@
      * Outputs:
      * * 0: The output 4-D tensor, of shape
      *      [batches, out_height, out_width, depth_out].
-     *      For output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM},
-     *      the following condition must be satisfied: output_scale > input_scale * filter_scale
+     *      For output tensor of
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM}, the following condition must
+     *      be satisfied: output_scale > input_scale * filter_scale
      */
     CONV_2D = 3,
 
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h
index 4cec545..b695f48 100644
--- a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h
@@ -44,6 +44,12 @@
     return result.has_value();
 }
 
+template <typename Type>
+auto convertFromNonCanonical(const Type& nonCanonicalObject)
+        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {
+    return convert(NN_TRY(nn::convert(nonCanonicalObject)));
+}
+
 }  // namespace android::hardware::neuralnetworks::V1_0::utils
 
 #endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_H
diff --git a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
index 052d88e..09597a3 100644
--- a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
+++ b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
@@ -47,6 +47,12 @@
     return result.has_value();
 }
 
+template <typename Type>
+auto convertFromNonCanonical(const Type& nonCanonicalObject)
+        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {
+    return convert(NN_TRY(nn::convert(nonCanonicalObject)));
+}
+
 }  // namespace android::hardware::neuralnetworks::V1_1::utils
 
 #endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_H
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 7441a54..7cec49e 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -314,7 +314,8 @@
      *      tensors. The output shape is [D0, D1, ..., sum(Daxis(i)), ..., Dm].
      *      Since HAL version 1.2, for a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
      *      the scale and zeroPoint values can be different from
-     *      input tensors. Before HAL version 1.2 they have to be the same as for the input tensors.
+     *      input tensors. Before HAL version 1.2 they have to be the same as for the
+     *      input tensors.
      */
     CONCATENATION = @1.1::OperationType:CONCATENATION,
 
@@ -460,8 +461,9 @@
      * Outputs:
      * * 0: The output 4-D tensor, of shape
      *      [batches, out_height, out_width, depth_out].
-     *      Before HAL version 1.2, for output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM},
-     *      the following condition must be satisfied: output_scale > input_scale * filter_scale
+     *      Before HAL version 1.2, for output tensor of
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM}, the following condition must
+     *      be satisfied: output_scale > input_scale * filter_scale
      */
     CONV_2D = @1.1::OperationType:CONV_2D,
 
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h
index c289fc8..3233114 100644
--- a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h
@@ -54,6 +54,12 @@
     return result.has_value();
 }
 
+template <typename Type>
+auto convertFromNonCanonical(const Type& nonCanonicalObject)
+        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {
+    return convert(NN_TRY(nn::convert(nonCanonicalObject)));
+}
+
 }  // namespace android::hardware::neuralnetworks::V1_2::utils
 
 #endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_H
diff --git a/neuralnetworks/1.2/utils/src/Callbacks.cpp b/neuralnetworks/1.2/utils/src/Callbacks.cpp
index fefa122..9f54bb1 100644
--- a/neuralnetworks/1.2/utils/src/Callbacks.cpp
+++ b/neuralnetworks/1.2/utils/src/Callbacks.cpp
@@ -43,6 +43,15 @@
 namespace android::hardware::neuralnetworks::V1_2::utils {
 namespace {
 
+nn::GeneralResult<nn::SharedPreparedModel> prepareModelCallback(
+        V1_0::ErrorStatus status, const sp<V1_0::IPreparedModel>& preparedModel) {
+    if (const auto dynamicPreparedModel =
+                V1_2::IPreparedModel::castFrom(preparedModel).withDefault(nullptr)) {
+        return V1_2::utils::prepareModelCallback(status, dynamicPreparedModel);
+    }
+    return V1_0::utils::prepareModelCallback(status, preparedModel);
+}
+
 nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
 convertExecutionGeneralResultsHelper(const hidl_vec<OutputShape>& outputShapes,
                                      const Timing& timing) {
@@ -72,7 +81,7 @@
 
 Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,
                                            const sp<V1_0::IPreparedModel>& preparedModel) {
-    mData.put(V1_0::utils::prepareModelCallback(status, preparedModel));
+    mData.put(prepareModelCallback(status, preparedModel));
     return Void();
 }
 
diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal
index 5f5ee03..51837fe 100644
--- a/neuralnetworks/1.3/types.hal
+++ b/neuralnetworks/1.3/types.hal
@@ -263,7 +263,8 @@
      *      tensors. The output shape is [D0, D1, ..., sum(Daxis(i)), ..., Dm].
      *      Since HAL version 1.2, for a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
      *      the scale and zeroPoint values can be different from
-     *      input tensors. Before HAL version 1.2 they have to be the same as for the input tensors.
+     *      input tensors. Before HAL version 1.2 they have to be the same as for the
+     *      input tensors.
      *      For a {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
      *      the scale and zeroPoint values can be different from input tensors.
      */
@@ -312,7 +313,8 @@
      * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
      * * * input.scale * filter.scale).
      *
-     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * Quantized signed with filter symmetric per channel quantization
+     *   (since HAL version 1.3):
      * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
      * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
      * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
@@ -425,8 +427,9 @@
      * Outputs:
      * * 0: The output 4-D tensor, of shape
      *      [batches, out_height, out_width, depth_out].
-     *      Before HAL version 1.2, for output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM},
-     *      the following condition must be satisfied: output_scale > input_scale * filter_scale
+     *      Before HAL version 1.2, for output tensor of
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM}, the following condition must
+     *      be satisfied: output_scale > input_scale * filter_scale
      */
     CONV_2D = @1.2::OperationType:CONV_2D,
 
@@ -477,7 +480,8 @@
      * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
      * * * input.scale * filter.scale).
      *
-     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * Quantized signed with filter symmetric per channel quantization
+     *   (since HAL version 1.3):
      * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
      * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
      * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
@@ -3354,7 +3358,8 @@
      * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
      * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
      *
-     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * Quantized signed with filter symmetric per channel quantization
+     *   (since HAL version 1.3):
      * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
      * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
      * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
@@ -4615,7 +4620,8 @@
      * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
      * * * input.scale * filter.scale).
      *
-     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * Quantized signed with filter symmetric per channel quantization
+     *   (since HAL version 1.3):
      * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
      * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
      * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
index 29b0c80..3ce412c 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
@@ -49,6 +49,12 @@
     return result.has_value();
 }
 
+template <typename Type>
+auto convertFromNonCanonical(const Type& nonCanonicalObject)
+        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {
+    return convert(NN_TRY(nn::convert(nonCanonicalObject)));
+}
+
 }  // namespace android::hardware::neuralnetworks::V1_3::utils
 
 #endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_H
diff --git a/neuralnetworks/1.3/utils/src/Callbacks.cpp b/neuralnetworks/1.3/utils/src/Callbacks.cpp
index af76e6a..8e9fb83 100644
--- a/neuralnetworks/1.3/utils/src/Callbacks.cpp
+++ b/neuralnetworks/1.3/utils/src/Callbacks.cpp
@@ -28,6 +28,7 @@
 #include <nnapi/IPreparedModel.h>
 #include <nnapi/Result.h>
 #include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Callbacks.h>
 #include <nnapi/hal/1.0/Conversions.h>
 #include <nnapi/hal/1.0/PreparedModel.h>
 #include <nnapi/hal/1.2/Callbacks.h>
@@ -46,6 +47,20 @@
 namespace android::hardware::neuralnetworks::V1_3::utils {
 namespace {
 
+nn::GeneralResult<nn::SharedPreparedModel> prepareModelCallback(
+        V1_0::ErrorStatus status, const sp<V1_0::IPreparedModel>& preparedModel) {
+    if (const auto dynamicPreparedModel =
+                V1_3::IPreparedModel::castFrom(preparedModel).withDefault(nullptr)) {
+        const auto currentVersionStatus = NN_TRY(convertFromNonCanonical(status));
+        return V1_3::utils::prepareModelCallback(currentVersionStatus, dynamicPreparedModel);
+    }
+    if (const auto dynamicPreparedModel =
+                V1_2::IPreparedModel::castFrom(preparedModel).withDefault(nullptr)) {
+        return V1_2::utils::prepareModelCallback(status, dynamicPreparedModel);
+    }
+    return V1_0::utils::prepareModelCallback(status, preparedModel);
+}
+
 nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
 convertExecutionGeneralResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
                                      const V1_2::Timing& timing) {
@@ -82,13 +97,13 @@
 
 Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,
                                            const sp<V1_0::IPreparedModel>& preparedModel) {
-    mData.put(V1_0::utils::prepareModelCallback(status, preparedModel));
+    mData.put(prepareModelCallback(status, preparedModel));
     return Void();
 }
 
 Return<void> PreparedModelCallback::notify_1_2(V1_0::ErrorStatus status,
                                                const sp<V1_2::IPreparedModel>& preparedModel) {
-    mData.put(V1_2::utils::prepareModelCallback(status, preparedModel));
+    mData.put(prepareModelCallback(status, preparedModel));
     return Void();
 }
 
diff --git a/neuralnetworks/1.3/vts/functional/Android.bp b/neuralnetworks/1.3/vts/functional/Android.bp
index b17d445..ee753bb 100644
--- a/neuralnetworks/1.3/vts/functional/Android.bp
+++ b/neuralnetworks/1.3/vts/functional/Android.bp
@@ -57,6 +57,7 @@
         "VtsHalNeuralNetworksV1_0_utils",
         "VtsHalNeuralNetworksV1_2_utils",
         "VtsHalNeuralNetworksV1_3_utils",
+        "android.hardware.neuralnetworks-V1-ndk_platform",
         "android.hardware.neuralnetworks@1.0",
         "android.hardware.neuralnetworks@1.1",
         "android.hardware.neuralnetworks@1.2",
diff --git a/neuralnetworks/aidl/Android.bp b/neuralnetworks/aidl/Android.bp
new file mode 100644
index 0000000..0557e43
--- /dev/null
+++ b/neuralnetworks/aidl/Android.bp
@@ -0,0 +1,27 @@
+aidl_interface {
+    name: "android.hardware.neuralnetworks",
+    vendor_available: true,
+    srcs: [
+        "android/hardware/neuralnetworks/*.aidl",
+    ],
+    stability: "vintf",
+    imports: [
+        "android.hardware.common",
+    ],
+    backend: {
+        java: {
+            enabled: false,
+        },
+        cpp: {
+            enabled: false,
+        },
+        ndk: {
+            apex_available: [
+                "//apex_available:platform",
+                "com.android.neuralnetworks",
+                "test_com.android.neuralnetworks",
+            ],
+            min_sdk_version: "30",
+        },
+    },
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferDesc.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferDesc.aidl
new file mode 100644
index 0000000..71b7758
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferDesc.aidl
@@ -0,0 +1,37 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable BufferDesc {
+  int[] dimensions;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferRole.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferRole.aidl
new file mode 100644
index 0000000..c2d636c
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferRole.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable BufferRole {
+  int modelIndex;
+  int ioIndex;
+  float frequency;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Capabilities.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Capabilities.aidl
new file mode 100644
index 0000000..01cc753
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Capabilities.aidl
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Capabilities {
+  android.hardware.neuralnetworks.PerformanceInfo relaxedFloat32toFloat16PerformanceScalar;
+  android.hardware.neuralnetworks.PerformanceInfo relaxedFloat32toFloat16PerformanceTensor;
+  android.hardware.neuralnetworks.OperandPerformance[] operandPerformance;
+  android.hardware.neuralnetworks.PerformanceInfo ifPerformance;
+  android.hardware.neuralnetworks.PerformanceInfo whilePerformance;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DataLocation.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DataLocation.aidl
new file mode 100644
index 0000000..074cc09
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DataLocation.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable DataLocation {
+  int poolIndex;
+  long offset;
+  long length;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DeviceBuffer.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DeviceBuffer.aidl
new file mode 100644
index 0000000..7bc8aa7
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DeviceBuffer.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable DeviceBuffer {
+  android.hardware.neuralnetworks.IBuffer buffer;
+  int token;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DeviceType.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DeviceType.aidl
new file mode 100644
index 0000000..1abacc8
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/DeviceType.aidl
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum DeviceType {
+  OTHER = 1,
+  CPU = 2,
+  GPU = 3,
+  ACCELERATOR = 4,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ErrorStatus.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ErrorStatus.aidl
new file mode 100644
index 0000000..873c584
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ErrorStatus.aidl
@@ -0,0 +1,45 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum ErrorStatus {
+  NONE = 0,
+  DEVICE_UNAVAILABLE = 1,
+  GENERAL_FAILURE = 2,
+  OUTPUT_INSUFFICIENT_SIZE = 3,
+  INVALID_ARGUMENT = 4,
+  MISSED_DEADLINE_TRANSIENT = 5,
+  MISSED_DEADLINE_PERSISTENT = 6,
+  RESOURCE_EXHAUSTED_TRANSIENT = 7,
+  RESOURCE_EXHAUSTED_PERSISTENT = 8,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExecutionPreference.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExecutionPreference.aidl
new file mode 100644
index 0000000..c4badc0
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExecutionPreference.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum ExecutionPreference {
+  LOW_POWER = 0,
+  FAST_SINGLE_ANSWER = 1,
+  SUSTAINED_SPEED = 2,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExecutionResult.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExecutionResult.aidl
new file mode 100644
index 0000000..b99bb31
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExecutionResult.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable ExecutionResult {
+  boolean outputSufficientSize;
+  android.hardware.neuralnetworks.OutputShape[] outputShapes;
+  android.hardware.neuralnetworks.Timing timing;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Extension.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Extension.aidl
new file mode 100644
index 0000000..a7ae942
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Extension.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Extension {
+  String name;
+  android.hardware.neuralnetworks.ExtensionOperandTypeInformation[] operandTypes;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExtensionNameAndPrefix.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExtensionNameAndPrefix.aidl
new file mode 100644
index 0000000..4c25538
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExtensionNameAndPrefix.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable ExtensionNameAndPrefix {
+  String name;
+  char prefix;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExtensionOperandTypeInformation.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExtensionOperandTypeInformation.aidl
new file mode 100644
index 0000000..b32b217
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ExtensionOperandTypeInformation.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable ExtensionOperandTypeInformation {
+  char type;
+  boolean isTensor;
+  int byteSize;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/FusedActivationFunc.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/FusedActivationFunc.aidl
new file mode 100644
index 0000000..2fee136
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/FusedActivationFunc.aidl
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum FusedActivationFunc {
+  NONE = 0,
+  RELU = 1,
+  RELU1 = 2,
+  RELU6 = 3,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IBuffer.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IBuffer.aidl
new file mode 100644
index 0000000..2860692
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IBuffer.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+interface IBuffer {
+  void copyFrom(in android.hardware.neuralnetworks.Memory src, in int[] dimensions);
+  void copyTo(in android.hardware.neuralnetworks.Memory dst);
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IDevice.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IDevice.aidl
new file mode 100644
index 0000000..4c5fd2f
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IDevice.aidl
@@ -0,0 +1,51 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+interface IDevice {
+  android.hardware.neuralnetworks.DeviceBuffer allocate(in android.hardware.neuralnetworks.BufferDesc desc, in android.hardware.neuralnetworks.IPreparedModelParcel[] preparedModels, in android.hardware.neuralnetworks.BufferRole[] inputRoles, in android.hardware.neuralnetworks.BufferRole[] outputRoles);
+  android.hardware.neuralnetworks.Capabilities getCapabilities();
+  android.hardware.neuralnetworks.NumberOfCacheFiles getNumberOfCacheFilesNeeded();
+  android.hardware.neuralnetworks.Extension[] getSupportedExtensions();
+  boolean[] getSupportedOperations(in android.hardware.neuralnetworks.Model model);
+  android.hardware.neuralnetworks.DeviceType getType();
+  String getVersionString();
+  void prepareModel(in android.hardware.neuralnetworks.Model model, in android.hardware.neuralnetworks.ExecutionPreference preference, in android.hardware.neuralnetworks.Priority priority, in long deadline, in ParcelFileDescriptor[] modelCache, in ParcelFileDescriptor[] dataCache, in byte[] token, in android.hardware.neuralnetworks.IPreparedModelCallback callback);
+  void prepareModelFromCache(in long deadline, in ParcelFileDescriptor[] modelCache, in ParcelFileDescriptor[] dataCache, in byte[] token, in android.hardware.neuralnetworks.IPreparedModelCallback callback);
+  const int BYTE_SIZE_OF_CACHE_TOKEN = 32;
+  const int MAX_NUMBER_OF_CACHE_FILES = 32;
+  const int EXTENSION_TYPE_HIGH_BITS_PREFIX = 15;
+  const int EXTENSION_TYPE_LOW_BITS_TYPE = 16;
+  const int OPERAND_TYPE_BASE_MAX = 65535;
+  const int OPERATION_TYPE_BASE_MAX = 65535;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IFencedExecutionCallback.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IFencedExecutionCallback.aidl
new file mode 100644
index 0000000..abe67b8
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IFencedExecutionCallback.aidl
@@ -0,0 +1,37 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+interface IFencedExecutionCallback {
+  android.hardware.neuralnetworks.ErrorStatus getExecutionInfo(out android.hardware.neuralnetworks.Timing timingLaunched, out android.hardware.neuralnetworks.Timing timingFenced);
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModel.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModel.aidl
new file mode 100644
index 0000000..3ca1550
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModel.aidl
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+interface IPreparedModel {
+  android.hardware.neuralnetworks.ExecutionResult executeSynchronously(in android.hardware.neuralnetworks.Request request, in boolean measureTiming, in long deadline, in long loopTimeoutDuration);
+  android.hardware.neuralnetworks.IFencedExecutionCallback executeFenced(in android.hardware.neuralnetworks.Request request, in ParcelFileDescriptor[] waitFor, in boolean measureTiming, in long deadline, in long loopTimeoutDuration, in long duration, out @nullable ParcelFileDescriptor syncFence);
+  const long DEFAULT_LOOP_TIMEOUT_DURATION_NS = 2000000000;
+  const long MAXIMUM_LOOP_TIMEOUT_DURATION_NS = 15000000000;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModelCallback.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModelCallback.aidl
new file mode 100644
index 0000000..8eaaab6
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModelCallback.aidl
@@ -0,0 +1,37 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+interface IPreparedModelCallback {
+  void notify(in android.hardware.neuralnetworks.ErrorStatus status, in android.hardware.neuralnetworks.IPreparedModel preparedModel);
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModelParcel.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModelParcel.aidl
new file mode 100644
index 0000000..8388fda
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/IPreparedModelParcel.aidl
@@ -0,0 +1,37 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable IPreparedModelParcel {
+  android.hardware.neuralnetworks.IPreparedModel preparedModel;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Memory.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Memory.aidl
new file mode 100644
index 0000000..3b2f240
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Memory.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Memory {
+  android.hardware.common.NativeHandle handle;
+  long size;
+  String name;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Model.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Model.aidl
new file mode 100644
index 0000000..9d12e58
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Model.aidl
@@ -0,0 +1,42 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Model {
+  android.hardware.neuralnetworks.Subgraph main;
+  android.hardware.neuralnetworks.Subgraph[] referenced;
+  byte[] operandValues;
+  android.hardware.neuralnetworks.Memory[] pools;
+  boolean relaxComputationFloat32toFloat16;
+  android.hardware.neuralnetworks.ExtensionNameAndPrefix[] extensionNameToPrefix;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/NumberOfCacheFiles.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/NumberOfCacheFiles.aidl
new file mode 100644
index 0000000..c1e87da
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/NumberOfCacheFiles.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable NumberOfCacheFiles {
+  int numModelCache;
+  int numDataCache;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Operand.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Operand.aidl
new file mode 100644
index 0000000..bb78caa
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Operand.aidl
@@ -0,0 +1,43 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Operand {
+  android.hardware.neuralnetworks.OperandType type;
+  int[] dimensions;
+  float scale;
+  int zeroPoint;
+  android.hardware.neuralnetworks.OperandLifeTime lifetime;
+  android.hardware.neuralnetworks.DataLocation location;
+  @nullable android.hardware.neuralnetworks.OperandExtraParams extraParams;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandExtraParams.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandExtraParams.aidl
new file mode 100644
index 0000000..3f6d93b
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandExtraParams.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+union OperandExtraParams {
+  android.hardware.neuralnetworks.SymmPerChannelQuantParams channelQuant;
+  byte[] extension;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandLifeTime.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandLifeTime.aidl
new file mode 100644
index 0000000..d581ced
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandLifeTime.aidl
@@ -0,0 +1,43 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum OperandLifeTime {
+  TEMPORARY_VARIABLE = 0,
+  SUBGRAPH_INPUT = 1,
+  SUBGRAPH_OUTPUT = 2,
+  CONSTANT_COPY = 3,
+  CONSTANT_POOL = 4,
+  NO_VALUE = 5,
+  SUBGRAPH = 6,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandPerformance.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandPerformance.aidl
new file mode 100644
index 0000000..87fd3a6
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandPerformance.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable OperandPerformance {
+  android.hardware.neuralnetworks.OperandType type;
+  android.hardware.neuralnetworks.PerformanceInfo info;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandType.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandType.aidl
new file mode 100644
index 0000000..186c13d
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperandType.aidl
@@ -0,0 +1,52 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum OperandType {
+  FLOAT32 = 0,
+  INT32 = 1,
+  UINT32 = 2,
+  TENSOR_FLOAT32 = 3,
+  TENSOR_INT32 = 4,
+  TENSOR_QUANT8_ASYMM = 5,
+  BOOL = 6,
+  TENSOR_QUANT16_SYMM = 7,
+  TENSOR_FLOAT16 = 8,
+  TENSOR_BOOL8 = 9,
+  FLOAT16 = 10,
+  TENSOR_QUANT8_SYMM_PER_CHANNEL = 11,
+  TENSOR_QUANT16_ASYMM = 12,
+  TENSOR_QUANT8_SYMM = 13,
+  TENSOR_QUANT8_ASYMM_SIGNED = 14,
+  SUBGRAPH = 15,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Operation.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Operation.aidl
new file mode 100644
index 0000000..fec83a8
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Operation.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Operation {
+  android.hardware.neuralnetworks.OperationType type;
+  int[] inputs;
+  int[] outputs;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperationType.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperationType.aidl
new file mode 100644
index 0000000..ad42b02
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OperationType.aidl
@@ -0,0 +1,138 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum OperationType {
+  ADD = 0,
+  AVERAGE_POOL_2D = 1,
+  CONCATENATION = 2,
+  CONV_2D = 3,
+  DEPTHWISE_CONV_2D = 4,
+  DEPTH_TO_SPACE = 5,
+  DEQUANTIZE = 6,
+  EMBEDDING_LOOKUP = 7,
+  FLOOR = 8,
+  FULLY_CONNECTED = 9,
+  HASHTABLE_LOOKUP = 10,
+  L2_NORMALIZATION = 11,
+  L2_POOL_2D = 12,
+  LOCAL_RESPONSE_NORMALIZATION = 13,
+  LOGISTIC = 14,
+  LSH_PROJECTION = 15,
+  LSTM = 16,
+  MAX_POOL_2D = 17,
+  MUL = 18,
+  RELU = 19,
+  RELU1 = 20,
+  RELU6 = 21,
+  RESHAPE = 22,
+  RESIZE_BILINEAR = 23,
+  RNN = 24,
+  SOFTMAX = 25,
+  SPACE_TO_DEPTH = 26,
+  SVDF = 27,
+  TANH = 28,
+  BATCH_TO_SPACE_ND = 29,
+  DIV = 30,
+  MEAN = 31,
+  PAD = 32,
+  SPACE_TO_BATCH_ND = 33,
+  SQUEEZE = 34,
+  STRIDED_SLICE = 35,
+  SUB = 36,
+  TRANSPOSE = 37,
+  ABS = 38,
+  ARGMAX = 39,
+  ARGMIN = 40,
+  AXIS_ALIGNED_BBOX_TRANSFORM = 41,
+  BIDIRECTIONAL_SEQUENCE_LSTM = 42,
+  BIDIRECTIONAL_SEQUENCE_RNN = 43,
+  BOX_WITH_NMS_LIMIT = 44,
+  CAST = 45,
+  CHANNEL_SHUFFLE = 46,
+  DETECTION_POSTPROCESSING = 47,
+  EQUAL = 48,
+  EXP = 49,
+  EXPAND_DIMS = 50,
+  GATHER = 51,
+  GENERATE_PROPOSALS = 52,
+  GREATER = 53,
+  GREATER_EQUAL = 54,
+  GROUPED_CONV_2D = 55,
+  HEATMAP_MAX_KEYPOINT = 56,
+  INSTANCE_NORMALIZATION = 57,
+  LESS = 58,
+  LESS_EQUAL = 59,
+  LOG = 60,
+  LOGICAL_AND = 61,
+  LOGICAL_NOT = 62,
+  LOGICAL_OR = 63,
+  LOG_SOFTMAX = 64,
+  MAXIMUM = 65,
+  MINIMUM = 66,
+  NEG = 67,
+  NOT_EQUAL = 68,
+  PAD_V2 = 69,
+  POW = 70,
+  PRELU = 71,
+  QUANTIZE = 72,
+  QUANTIZED_16BIT_LSTM = 73,
+  RANDOM_MULTINOMIAL = 74,
+  REDUCE_ALL = 75,
+  REDUCE_ANY = 76,
+  REDUCE_MAX = 77,
+  REDUCE_MIN = 78,
+  REDUCE_PROD = 79,
+  REDUCE_SUM = 80,
+  ROI_ALIGN = 81,
+  ROI_POOLING = 82,
+  RSQRT = 83,
+  SELECT = 84,
+  SIN = 85,
+  SLICE = 86,
+  SPLIT = 87,
+  SQRT = 88,
+  TILE = 89,
+  TOPK_V2 = 90,
+  TRANSPOSE_CONV_2D = 91,
+  UNIDIRECTIONAL_SEQUENCE_LSTM = 92,
+  UNIDIRECTIONAL_SEQUENCE_RNN = 93,
+  RESIZE_NEAREST_NEIGHBOR = 94,
+  QUANTIZED_LSTM = 95,
+  IF = 96,
+  WHILE = 97,
+  ELU = 98,
+  HARD_SWISH = 99,
+  FILL = 100,
+  RANK = 101,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OutputShape.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OutputShape.aidl
new file mode 100644
index 0000000..09a43f7
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/OutputShape.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable OutputShape {
+  int[] dimensions;
+  boolean isSufficient;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/PerformanceInfo.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/PerformanceInfo.aidl
new file mode 100644
index 0000000..178946c
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/PerformanceInfo.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable PerformanceInfo {
+  float execTime;
+  float powerUsage;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Priority.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Priority.aidl
new file mode 100644
index 0000000..d9b77fa
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Priority.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@Backing(type="int") @VintfStability
+enum Priority {
+  LOW = 0,
+  MEDIUM = 1,
+  HIGH = 2,
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Request.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Request.aidl
new file mode 100644
index 0000000..599b3f4
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Request.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Request {
+  android.hardware.neuralnetworks.RequestArgument[] inputs;
+  android.hardware.neuralnetworks.RequestArgument[] outputs;
+  android.hardware.neuralnetworks.RequestMemoryPool[] pools;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/RequestArgument.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/RequestArgument.aidl
new file mode 100644
index 0000000..91b9aa7
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/RequestArgument.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable RequestArgument {
+  boolean hasNoValue;
+  android.hardware.neuralnetworks.DataLocation location;
+  int[] dimensions;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/RequestMemoryPool.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/RequestMemoryPool.aidl
new file mode 100644
index 0000000..3813b51
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/RequestMemoryPool.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+union RequestMemoryPool {
+  android.hardware.neuralnetworks.Memory pool;
+  int token;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Subgraph.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Subgraph.aidl
new file mode 100644
index 0000000..dec976f
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Subgraph.aidl
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Subgraph {
+  android.hardware.neuralnetworks.Operand[] operands;
+  android.hardware.neuralnetworks.Operation[] operations;
+  int[] inputIndexes;
+  int[] outputIndexes;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/SymmPerChannelQuantParams.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/SymmPerChannelQuantParams.aidl
new file mode 100644
index 0000000..66fdfe7
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/SymmPerChannelQuantParams.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable SymmPerChannelQuantParams {
+  float[] scales;
+  int channelDim;
+}
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Timing.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Timing.aidl
new file mode 100644
index 0000000..d0de34a
--- /dev/null
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/Timing.aidl
@@ -0,0 +1,38 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.neuralnetworks;
+@VintfStability
+parcelable Timing {
+  long timeOnDevice;
+  long timeInDriver;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferDesc.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferDesc.aidl
new file mode 100644
index 0000000..bec7e86
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferDesc.aidl
@@ -0,0 +1,30 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * A buffer descriptor. Describes the properties of a buffer.
+ */
+@VintfStability
+parcelable BufferDesc {
+    /**
+     * Dimensions of the buffer. May have unknown dimensions or rank. A buffer with some number of
+     * unspecified dimensions is represented by setting each unspecified dimension to 0. A buffer
+     * with unspecified rank is represented by providing an empty dimensions vector.
+     */
+    int[] dimensions;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferRole.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferRole.aidl
new file mode 100644
index 0000000..0d7f678
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferRole.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Describes a role of an input or output to a prepared model.
+ */
+@VintfStability
+parcelable BufferRole {
+    /**
+     * The index of the IPreparedModel within the "preparedModel" argument passed in
+     * IDevice::allocate.
+     */
+    int modelIndex;
+    /**
+     * The index of the input or output operand.
+     */
+    int ioIndex;
+    /**
+     * A floating-point value within the range (0.0, 1.0]. Describes how likely the buffer is to be
+     * used in the specified role. This is provided as a hint to optimize the case when multiple
+     * roles prefer different buffer locations or data layouts.
+     */
+    float frequency;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Capabilities.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Capabilities.aidl
new file mode 100644
index 0000000..3802f1f
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Capabilities.aidl
@@ -0,0 +1,62 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.OperandPerformance;
+import android.hardware.neuralnetworks.PerformanceInfo;
+
+/**
+ * The capabilities of a driver.
+ *
+ * This represents performance of non-extension operations.
+ *
+ * Performance of an operation other than {@link OperationType::IF} and {@link OperationType::WHILE}
+ * comes from the type of its first operand.
+ */
+@VintfStability
+parcelable Capabilities {
+    /**
+     * Driver performance when operating on float32 data but performing calculations with range
+     * and/or precision as low as that of the IEEE 754 16-bit floating-point format.
+     */
+    PerformanceInfo relaxedFloat32toFloat16PerformanceScalar;
+    PerformanceInfo relaxedFloat32toFloat16PerformanceTensor;
+    /**
+     * Performance by operand type. Must be sorted by OperandType.
+     *
+     * If a particular {@link OperandType} is not present in operandPerformance, its performance is
+     * treated as { .execTime = FLT_MAX, .powerUsage = FLT_MAX }.
+     *
+     * Performance does not apply to {@link OperandType::SUBGRAPH}, and a driver must not report
+     * operand performance for {@link OperandType::SUBGRAPH}.
+     */
+    OperandPerformance[] operandPerformance;
+    /**
+     * Performance of an {@link OperationType::IF} operation is the sum of
+     * {@link Capabilities::ifPerformance} and the mean of performance for the two branch subgraphs,
+     * where performance for a subgraph is the sum of the performance of all operations within the
+     * subgraph.
+     */
+    PerformanceInfo ifPerformance;
+    /**
+     * Performance of a {@link OperationType::WHILE} operation is the sum of
+     * {@link Capabilities::whilePerformance}, performance for the condition subgraph and
+     * performance for the body subgraph, where performance for a subgraph is the sum of the
+     * performance of all operations within the subgraph.
+     */
+    PerformanceInfo whilePerformance;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/DataLocation.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/DataLocation.aidl
new file mode 100644
index 0000000..f6b5e0d
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/DataLocation.aidl
@@ -0,0 +1,36 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Describes the location of a data object.
+ */
+@VintfStability
+parcelable DataLocation {
+    /**
+     * The index of the memory pool where this location is found.
+     */
+    int poolIndex;
+    /**
+     * Offset in bytes from the start of the pool.
+     */
+    long offset;
+    /**
+     * The length of the data in bytes.
+     */
+    long length;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/DeviceBuffer.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/DeviceBuffer.aidl
new file mode 100644
index 0000000..07930a6
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/DeviceBuffer.aidl
@@ -0,0 +1,36 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.IBuffer;
+
+/**
+ * A type that is used to represent a driver allocated buffer and token that corresponds to it.
+ */
+@VintfStability
+parcelable DeviceBuffer {
+    /**
+     * An IBuffer object used to interact with the device allocated buffer.
+     */
+    IBuffer buffer;
+    /**
+     * A positive token identifying the allocated buffer. The token is provided when referencing the
+     * buffer as one of the memory pools in the request of an execution. The token must not collide
+     * with the tokens of other IBuffer objects that are currently alive in the same driver service.
+     */
+    int token;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/DeviceType.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/DeviceType.aidl
new file mode 100644
index 0000000..815be64
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/DeviceType.aidl
@@ -0,0 +1,44 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Device types.
+ *
+ * The type of NNAPI device.
+ */
+@VintfStability
+@Backing(type="int")
+enum DeviceType {
+    /**
+     * The device does not fall into any category below.
+     */
+    OTHER = 1,
+    /**
+     * The device runs NNAPI models on single or multi-core CPU.
+     */
+    CPU = 2,
+    /**
+     * The device can run NNAPI models and also accelerate graphics APIs such as OpenGL ES and
+     * Vulkan.
+     */
+    GPU = 3,
+    /**
+     * Dedicated accelerator for Machine Learning workloads.
+     */
+    ACCELERATOR = 4,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/ErrorStatus.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/ErrorStatus.aidl
new file mode 100644
index 0000000..c2752d9
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/ErrorStatus.aidl
@@ -0,0 +1,51 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Calls to neural networks AIDL interfaces may return a ServiceSpecificException with the following
+ * error codes.
+ */
+@VintfStability
+@Backing(type="int")
+enum ErrorStatus {
+    NONE,
+    DEVICE_UNAVAILABLE,
+    GENERAL_FAILURE,
+    OUTPUT_INSUFFICIENT_SIZE,
+    INVALID_ARGUMENT,
+    /**
+     * Failure because a deadline could not be met for a task, but future deadlines may still be met
+     * for the same task after a short delay.
+     */
+    MISSED_DEADLINE_TRANSIENT,
+    /**
+     * Failure because a deadline could not be met for a task, and future deadlines will likely also
+     * not be met for the same task even after a short delay.
+     */
+    MISSED_DEADLINE_PERSISTENT,
+    /**
+     * Failure because of a resource limitation within the driver, but future calls for the same
+     * task may still succeed after a short delay.
+     */
+    RESOURCE_EXHAUSTED_TRANSIENT,
+    /**
+     * Failure because of a resource limitation within the driver, and future calls for the same
+     * task will likely also fail even after a short delay.
+     */
+    RESOURCE_EXHAUSTED_PERSISTENT,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/ExecutionPreference.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExecutionPreference.aidl
new file mode 100644
index 0000000..a3e3ce3
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExecutionPreference.aidl
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Execution preferences.
+ */
+@VintfStability
+@Backing(type="int")
+enum ExecutionPreference {
+    /**
+     * Prefer executing in a way that minimizes battery drain. This is desirable for compilations
+     * that will be executed often.
+     */
+    LOW_POWER,
+    /**
+     * Prefer returning a single answer as fast as possible, even if this causes more power
+     * consumption.
+     */
+    FAST_SINGLE_ANSWER,
+    /**
+     * Prefer maximizing the throughput of successive frames, for example when processing successive
+     * frames coming from the camera.
+     */
+    SUSTAINED_SPEED,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/ExecutionResult.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExecutionResult.aidl
new file mode 100644
index 0000000..1f88207
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExecutionResult.aidl
@@ -0,0 +1,45 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.ErrorStatus;
+import android.hardware.neuralnetworks.OutputShape;
+import android.hardware.neuralnetworks.Timing;
+
+/**
+ * A result from running a synchronous execution of a prepared model.
+ */
+@VintfStability
+parcelable ExecutionResult {
+    /**
+     * A value of "true" indicates that the execution was successful. A value of "false" indicates
+     * the execution failed because at least one output operand buffer was not large enough to store
+     * the corresponding output.
+     */
+    boolean outputSufficientSize;
+    /**
+     * A list of shape information of model output operands. The index in "outputShapes" corresponds
+     * to the index of the output operand in the Request outputs vector.
+     */
+    OutputShape[] outputShapes;
+    /**
+     * Duration of execution. Unless measure is true and the execution is successful, all times must
+     * be reported as -1. A driver may choose to report any time as -1, indicating that measurement
+     * is not available.
+     */
+    Timing timing;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Extension.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Extension.aidl
new file mode 100644
index 0000000..20109bd
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Extension.aidl
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.ExtensionOperandTypeInformation;
+
+/**
+ * Information about an extension.
+ */
+@VintfStability
+parcelable Extension {
+    /**
+     * The extension name.
+     *
+     * The name must consist of lowercase latin letters, numbers, periods, and underscore signs. The
+     * name must contain at least one period.
+     *
+     * The name must start with the reverse domain name of the vendor.
+     *
+     * Example: com.google.test_extension
+     */
+    String name;
+    /**
+     * Information about operand types defined by the extension.
+     */
+    ExtensionOperandTypeInformation[] operandTypes;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/ExtensionNameAndPrefix.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExtensionNameAndPrefix.aidl
new file mode 100644
index 0000000..29be93f
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExtensionNameAndPrefix.aidl
@@ -0,0 +1,48 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * The mapping between extension names and prefixes of operand and operation type values.
+ *
+ * An operand or operation whose numeric type value is above {@link IDevice::OPERAND_TYPE_BASE_MAX}
+ * or {@link IDevice::OPERATION_TYPE_BASE_MAX} respectively should be interpreted as an extension
+ * operand/operation. The low {@link IDevice::EXTENSION_TYPE_LOW_BITS_TYPE} bits of the value
+ * correspond to the type ID within the extension and the high
+ * {@link IDevice::EXTENSION_TYPE_HIGH_BITS_PREFIX} bits encode the "prefix", which maps uniquely to
+ * the extension name. The sign bit is always 0.
+ *
+ * For example, if a model contains an operation whose value is 0x7AAABBBB and extensionNameToPrefix
+ * contains an entry with prefix=0x7AAA and name="vendor.test.test_extension", then the operation
+ * should be interpreted as the operation 0xBBBB of the extension named vendor.test.test_extension.
+ *
+ * This is a one-to-one correspondence. That is, there must be at most one prefix corresponding to
+ * each extension name and at most one extension name corresponding to each prefix.
+ */
+@VintfStability
+parcelable ExtensionNameAndPrefix {
+    /**
+     * The extension name.
+     *
+     * See {@link Extension::name} for the format specification.
+     */
+    String name;
+    /**
+     * The extension prefix. Only the lowest 15 bits are used, so the value must be less than 32768.
+     */
+    char prefix;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/ExtensionOperandTypeInformation.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExtensionOperandTypeInformation.aidl
new file mode 100644
index 0000000..b8e3449
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/ExtensionOperandTypeInformation.aidl
@@ -0,0 +1,36 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Information about an extension operand type.
+ */
+@VintfStability
+parcelable ExtensionOperandTypeInformation {
+    /**
+     * The extension operand type.
+     */
+    char type;
+    /**
+     * Indicates whether the extension operand type represents a tensor or a scalar.
+     */
+    boolean isTensor;
+    /**
+     * The byte size of the operand (if scalar) or of a single element (if tensor).
+     */
+    int byteSize;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/FusedActivationFunc.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/FusedActivationFunc.aidl
new file mode 100644
index 0000000..861b6f0
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/FusedActivationFunc.aidl
@@ -0,0 +1,29 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Fused activation function types.
+ */
+@VintfStability
+@Backing(type="int")
+enum FusedActivationFunc {
+    NONE,
+    RELU,
+    RELU1,
+    RELU6,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IBuffer.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IBuffer.aidl
new file mode 100644
index 0000000..2915a22
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IBuffer.aidl
@@ -0,0 +1,57 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.Memory;
+
+/**
+ * This interface represents a device memory buffer.
+ */
+@VintfStability
+interface IBuffer {
+    /**
+     * Sets the content of this buffer from a shared memory region.
+     *
+     * @param src The source shared memory region.
+     * @param dimensions Updated dimensional information. If the dimensions of the IBuffer object
+     *                   are not fully specified, then the dimensions must be fully specified here.
+     *                   If the dimensions of the IBuffer object are fully specified, then the
+     *                   dimensions may be empty here. If dimensions.size() > 0, then all dimensions
+     *                   must be specified here, and any dimension that was specified in the IBuffer
+     *                   object must have the same value here.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if provided memory is invalid, or if the dimensions is invalid
+     */
+    void copyFrom(in Memory src, in int[] dimensions);
+
+    /**
+     * Retrieves the content of this buffer to a shared memory region.
+     *
+     * The IBuffer object must have been initialized before the call to IBuffer::copyTo. For more
+     * information on the state of the IBuffer object, refer to IDevice::allocate.
+     *
+     * @param dst The destination shared memory region.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if the IBuffer object is uninitialized, or there is an unspecified
+     *       error
+     *     - INVALID_ARGUMENT if provided memory is invalid
+     */
+    void copyTo(in Memory dst);
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IDevice.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IDevice.aidl
new file mode 100644
index 0000000..e17e0cd
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IDevice.aidl
@@ -0,0 +1,432 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.BufferDesc;
+import android.hardware.neuralnetworks.BufferRole;
+import android.hardware.neuralnetworks.Capabilities;
+import android.hardware.neuralnetworks.DeviceBuffer;
+import android.hardware.neuralnetworks.DeviceType;
+import android.hardware.neuralnetworks.ExecutionPreference;
+import android.hardware.neuralnetworks.Extension;
+import android.hardware.neuralnetworks.IPreparedModel;
+import android.hardware.neuralnetworks.IPreparedModelCallback;
+import android.hardware.neuralnetworks.IPreparedModelParcel;
+import android.hardware.neuralnetworks.Model;
+import android.hardware.neuralnetworks.NumberOfCacheFiles;
+import android.hardware.neuralnetworks.Priority;
+
+/**
+ * This interface represents a device driver.
+ */
+@VintfStability
+interface IDevice {
+    /**
+     * The byte size of the cache token.
+     */
+    const int BYTE_SIZE_OF_CACHE_TOKEN = 32;
+    /**
+     * The maximum number of files for each type of cache in compilation caching.
+     */
+    const int MAX_NUMBER_OF_CACHE_FILES = 32;
+
+    /**
+     * Numeric values of extension operand and operation types have the following structure:
+     * - The sign bit is always 0.
+     * - 15 high bits represent the "prefix", which corresponds uniquely to the extension name.
+     * - 16 low bits represent the type ID within the extension.
+     */
+    const int EXTENSION_TYPE_HIGH_BITS_PREFIX = 15;
+    const int EXTENSION_TYPE_LOW_BITS_TYPE = 16;
+    /**
+     * OperandType with any value above {@link IDevice::OPERAND_TYPE_BASE_MAX} must be interpreted
+     * as an extension type according to {@link Model::extensionNameToPrefix}.
+     */
+    const int OPERAND_TYPE_BASE_MAX = 0xFFFF;
+    /**
+     * OperationType with any value above {@link IDevice::OPERATION_TYPE_BASE_MAX} must be
+     * interpreted as an extension type according to {@link Model::extensionNameToPrefix}.
+     */
+    const int OPERATION_TYPE_BASE_MAX = 0xFFFF;
+
+    /**
+     * Allocates a driver-managed buffer with the properties specified by the buffer descriptor as
+     * well as the input and output roles.
+     *
+     * The allocate function must verify its inputs are correct. If there is an error, or if a
+     * certain role or property is not supported by the driver, the allocate function must return a
+     * service specific exception with an appropriate ErrorStatus. If the allocation is successful,
+     * this method must return a DeviceBuffer object with the produced IBuffer and a positive token
+     * identifying the allocated buffer. A successful allocation must accommodate all of the
+     * specified roles and buffer properties.
+     *
+     * The buffer is allocated to an uninitialized state. An uninitialized buffer may only be used
+     * in ways that are specified by outputRoles. A buffer is initialized after it is used as an
+     * output in a successful execution, or after a successful invocation of IBuffer::copyFrom on
+     * the buffer. An initialized buffer may be used according to all roles specified in inputRoles
+     * and outputRoles. A buffer will return to the uninitialized state if it is used as an output
+     * in a failed execution, or after a failed invocation of IBuffer::copyFrom on the buffer.
+     *
+     * The dimensions of the buffer can be deduced from the buffer descriptor as well as the
+     * dimensions of the corresponding model operands of the input and output roles. The dimensions
+     * or rank of the buffer may be unknown at this stage. As such, some driver services may only
+     * create a placeholder and defer the actual allocation until execution time. Note that the same
+     * buffer may be used for different shapes of outputs on different executions. When the buffer
+     * is used as an input, the input shape must be the same as the output shape from the last
+     * execution using this buffer as an output.
+     *
+     * The driver must apply proper validatation upon every usage of the buffer, and must fail the
+     * execution immediately if the usage is illegal.
+     *
+     * @param desc A buffer descriptor specifying the properties of the buffer to allocate.
+     * @param preparedModels A vector of IPreparedModel objects. Must only contain IPreparedModel
+     *                       objects from the same IDevice as this method is being invoked on.
+     * @param inputRoles A vector of roles with each specifying an input to a prepared model.
+     * @param outputRoles A vector of roles with each specifying an output to a prepared model. Each
+     *                    role specified in inputRoles and outputRoles must be unique. The
+     *                    corresponding model operands of the roles must have the same OperandType,
+     *                    scale, zero point, and ExtraParams. The dimensions of the operands and the
+     *                    dimensions specified in the buffer descriptor must be compatible with each
+     *                    other. Two dimensions are incompatible if there is at least one axis that
+     *                    is fully specified in both but has different values.
+     * @return DeviceBuffer object containing the allocated IBuffer object and a positive token that
+     *     can be used to reference the buffer as one of the memory pools.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if a certain buffer property or a certain role is not supported,
+     *       or if there is an unspecified error
+     *     - INVALID_ARGUMENT if one of the input arguments is invalid
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    DeviceBuffer allocate(in BufferDesc desc, in IPreparedModelParcel[] preparedModels,
+            in BufferRole[] inputRoles, in BufferRole[] outputRoles);
+
+    /**
+     * Gets the capabilities of a driver.
+     *
+     * @return Capabilities of the driver.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     */
+    Capabilities getCapabilities();
+
+    /**
+     * Gets the caching requirements of the driver implementation.
+     *
+     * There are two types of cache file descriptors provided to the driver: model cache and data
+     * cache.
+     *
+     * The data cache is for caching constant data, possibly including preprocessed and transformed
+     * tensor buffers. Any modification to the data cache should have no worse effect than
+     * generating bad output values at execution time.
+     *
+     * The model cache is for caching security-sensitive data such as compiled executable machine
+     * code in the device's native binary format. A modification to the model cache may affect the
+     * driver's execution behavior, and a malicious client could make use of this to execute beyond
+     * the granted permission. Thus, the driver must always check whether the model cache is
+     * corrupted before preparing the model from cache.
+     *
+     * getNumberOfCacheFilesNeeded returns how many of each type of cache files the driver
+     * implementation needs to cache a single prepared model. Returning 0 for both types indicates
+     * compilation caching is not supported by this driver. The driver may still choose not to cache
+     * certain compiled models even if it reports that caching is supported.
+     *
+     * If the device reports that caching is not supported, the user may avoid calling
+     * IDevice::prepareModelFromCache or providing cache file descriptors to
+     * IDevice::prepareModel.
+     *
+     * @return NumberOfCacheFiles structure indicating how many files for model and data cache the
+     *     driver needs to cache a single prepared model. It must be less than or equal to
+     *     MAX_NUMBER_OF_CACHE_FILES.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     */
+    NumberOfCacheFiles getNumberOfCacheFilesNeeded();
+
+    /**
+     * Gets information about extensions supported by the driver implementation.
+     *
+     * All extension operations and operands must be fully supported for the extension to appear in
+     * the list of supported extensions.
+     *
+     * @return A list of supported extensions.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     */
+    Extension[] getSupportedExtensions();
+
+    /**
+     * Gets the supported operations in a model.
+     *
+     * getSupportedOperations indicates which operations of the top-level subgraph are fully
+     * supported by the vendor driver. If an operation may not be supported for any reason,
+     * getSupportedOperations must return false for that operation.
+     *
+     * The {@link OperationType::IF} and {@link OperationType::WHILE} operations may only be fully
+     * supported if the vendor driver fully supports all operations in the referenced subgraphs.
+     *
+     * @param model A model whose operations -- and their corresponding operands -- are to be
+     *              verified by the driver.
+     * @return A list of supported operations, where true indicates the operation is supported and
+     *     false indicates the operation is not supported. The index of "supported" corresponds with
+     *     the index of the operation it is describing in the main subgraph.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if provided model is invalid
+     */
+    boolean[] getSupportedOperations(in Model model);
+
+    /**
+     * Get the type of a given device.
+     *
+     * The device type can be used to help application developers to distribute Machine Learning
+     * workloads and other workloads such as graphical rendering. E.g., for an app which renders AR
+     * scenes based on real time object detection results, the developer could choose an ACCELERATOR
+     * type device for ML workloads, and reserve GPU for graphical rendering.
+     *
+     * @return The DeviceType of the device. Please note, this is not a bitfield of DeviceTypes.
+     *     Each device must only be of a single DeviceType.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if the query resulted in an unspecified error
+     */
+    DeviceType getType();
+
+    /**
+     * Get the version string of the driver implementation.
+     *
+     * The version string must be a unique token among the set of version strings of drivers of a
+     * specific device. The token identifies the device driver's implementation. The token must not
+     * be confused with the feature level which is solely defined by the interface version. This API
+     * is opaque to the Android framework, but the Android framework may use the information for
+     * debugging or to pass on to NNAPI applications.
+     *
+     * Application developers sometimes have specific requirements to ensure good user experiences,
+     * and they need more information to make intelligent decisions when the Android framework
+     * cannot. For example, combined with the device name and other information, the token can help
+     * NNAPI applications filter devices based on their needs:
+     *     - An application demands a certain level of performance, but a specific version of the
+     *       driver cannot meet that requirement because of a performance regression.
+     *       The application can disallow the driver based on the version provided.
+     *     - An application has a minimum precision requirement, but certain versions of
+     *       the driver cannot meet that requirement because of bugs or certain optimizations.
+     *       The application can filter out versions of these drivers.
+     *
+     * @return The version string of the device implementation. Must have nonzero length.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if the query resulted in an unspecified error
+     */
+    String getVersionString();
+
+    /**
+     * Asynchronously creates a prepared model for execution and optionally saves it into cache
+     * files.
+     *
+     * prepareModel is used to make any necessary transformations to or alternative representations
+     * to a model for execution, possibly including transformations on the constant data,
+     * optimization on the model's graph, or compilation into the device's native binary format. The
+     * model itself is not changed.
+     *
+     * Optionally, caching information may be provided for the driver to save the prepared model to
+     * cache files for faster model compilation time when the same model preparation is requested in
+     * the future. There are two types of cache file descriptors provided to the driver: model cache
+     * and data cache. For more information on the two types of cache, refer to
+     * getNumberOfCacheFilesNeeded.
+     *
+     * The file descriptors must be opened with read and write permission. A file may have any size,
+     * and the corresponding file descriptor may have any offset. The driver must truncate a file to
+     * zero size before writing to that file. The file descriptors may be closed by the client once
+     * the asynchronous preparation has finished. The driver must dup a file descriptor if it wants
+     * to get access to the cache file later.
+     *
+     * The model is prepared asynchronously with respect to the caller. The prepareModel function
+     * must verify the inputs to the preparedModel function related to preparing the model (as
+     * opposed to saving the prepared model to cache) are correct. If there is an error,
+     * prepareModel must immediately invoke the callback with the appropriate ErrorStatus value and
+     * nullptr for the IPreparedModel, then return a status with a service specific exception with
+     * the same ErrorStatus. If the inputs to the prepareModel function that are related to
+     * preparing the model are valid and there is no error, prepareModel must launch an asynchronous
+     * task to prepare the model in the background, and immediately return from prepareModel. If the
+     * asynchronous task fails to launch, prepareModel must immediately invoke the callback with
+     * ErrorStatus::GENERAL_FAILURE and nullptr for the IPreparedModel, then return a service
+     * specific exception with ErrorStatus::GENERAL_FAILURE.
+     *
+     * When the asynchronous task has finished preparing the model, it must immediately invoke the
+     * callback function provided as an input to prepareModel. If the model was prepared
+     * successfully, the callback object must be invoked with an error status of ErrorStatus::NONE
+     * and the produced IPreparedModel object. If an error occurred preparing the model, the
+     * callback object must be invoked with the appropriate ErrorStatus value and nullptr for the
+     * IPreparedModel.
+     *
+     * The model is prepared with a priority. This priority is relative to other prepared models
+     * owned by the same client. Higher priority executions may use more compute resources than
+     * lower priority executions, and may preempt or starve lower priority executions.
+     *
+     * prepareModel can be called with an optional deadline. If the model is not able to be prepared
+     * before the provided deadline, the model preparation may be aborted, and either
+     * {@link ErrorStatus::MISSED_DEADLINE_TRANSIENT} or {@link
+     * ErrorStatus::MISSED_DEADLINE_PERSISTENT} may be returned. The error due to an abort must be
+     * sent the same way as other errors, described above.
+     *
+     * Optionally, the driver may save the prepared model to cache during the asynchronous
+     * preparation. Any error that occurs when saving to cache must not affect the status of
+     * preparing the model. Even if the input arguments related to the cache may be invalid, or the
+     * driver may fail to save to cache, the prepareModel function must finish preparing the model.
+     * The driver may choose not to save to cache even if the caching information is provided and
+     * valid.
+     *
+     * The only information that may be unknown to the model at this stage is the shape of the
+     * tensors, which may only be known at execution time. As such, some driver services may return
+     * partially prepared models, where the prepared model may only be finished when it is paired
+     * with a set of inputs to the model. Note that the same prepared model object may be used with
+     * different shapes of inputs on different (possibly concurrent) executions.
+     *
+     * Multiple threads may call prepareModel on the same model concurrently.
+     *
+     * @param model The model to be prepared for execution.
+     * @param preference Indicates the intended execution behavior of a prepared model.
+     * @param priority The priority of the prepared model relative to other prepared models owned by
+     *                 the client.
+     * @param deadline The time by which the model is expected to be prepared. The time is measured
+     *                 in nanoseconds since epoch of the steady clock (as from
+     *                 std::chrono::steady_clock). If the model cannot be prepared by the deadline,
+     *                 the preparation may be aborted. Passing -1 means the deadline is omitted.
+     *                 Other negative values are invalid.
+     * @param modelCache A vector of file descriptors for the security-sensitive cache. The length
+     *                   of the vector must either be 0 indicating that caching information is not
+     *                   provided, or match the numModelCache returned from
+     *                   getNumberOfCacheFilesNeeded. The cache file descriptors will be provided in
+     *                   the same order when retrieving the preparedModel from cache files with
+     *                   prepareModelFromCache.
+     * @param dataCache A vector of file descriptors for the constants' cache. The length of the
+     *                  vector must either be 0 indicating that caching information is not provided,
+     *                  or match the numDataCache returned from getNumberOfCacheFilesNeeded. The
+     *                  cache file descriptors will be provided in the same order when retrieving
+     *                  the preparedModel from cache files with prepareModelFromCache.
+     * @param token A caching token of length BYTE_SIZE_OF_CACHE_TOKEN identifying the prepared
+     *              model. The same token will be provided when retrieving the prepared model from
+     *              the cache files with prepareModelFromCache.  Tokens should be chosen to have a
+     *              low rate of collision for a particular application. The driver cannot detect a
+     *              collision; a collision will result in a failed execution or in a successful
+     *              execution that produces incorrect output values. If both modelCache and
+     *              dataCache are empty indicating that caching information is not provided, this
+     *              token must be ignored.
+     * @param callback A callback object used to return the error status of preparing the model for
+     *                 execution and the prepared model if successful, nullptr otherwise. The
+     *                 callback object's notify function must be called exactly once, even if the
+     *                 model could not be prepared.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if one of the input arguments related to preparing the model is
+     *       invalid
+     *     - MISSED_DEADLINE_* if the preparation is aborted because the model cannot be prepared by
+     *       the deadline
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    void prepareModel(in Model model, in ExecutionPreference preference, in Priority priority,
+            in long deadline, in ParcelFileDescriptor[] modelCache,
+            in ParcelFileDescriptor[] dataCache, in byte[] token,
+            in IPreparedModelCallback callback);
+
+    /**
+     * Creates a prepared model from cache files for execution.
+     *
+     * prepareModelFromCache is used to retrieve a prepared model directly from cache files to avoid
+     * slow model compilation time. There are two types of cache file descriptors provided to the
+     * driver: model cache and data cache. For more information on the two types of cache files,
+     * refer to getNumberOfCacheFilesNeeded.
+     *
+     * The file descriptors must be opened with read and write permission. A file may have any size,
+     * and the corresponding file descriptor may have any offset. The driver must truncate a file to
+     * zero size before writing to that file. The file descriptors may be closed by the client once
+     * the asynchronous preparation has finished. The driver must dup a file descriptor if it wants
+     * to get access to the cache file later.
+     *
+     * The model is prepared asynchronously with respect to the caller. The prepareModelFromCache
+     * function must verify the inputs to the prepareModelFromCache function are correct, and that
+     * the security-sensitive cache has not been modified since it was last written by the driver.
+     * If there is an error, or if compilation caching is not supported, or if the
+     * security-sensitive cache has been modified, prepareModelFromCache must immediately invoke the
+     * callback with the appropriate ErrorStatus value and nullptr for the IPreparedModel, then
+     * return a status with a service specific exception with the same ErrorStatus. If the inputs to
+     * the prepareModelFromCache function are valid, the security-sensitive cache is not modified,
+     * and there is no error, prepareModelFromCache must launch an asynchronous task to prepare the
+     * model in the background, and immediately return from prepareModelFromCache. If the
+     * asynchronous task fails to launch, prepareModelFromCache must immediately invoke the callback
+     * with ErrorStatus::GENERAL_FAILURE and nullptr for the IPreparedModel, then return a service
+     * specific exception with ErrorStatus::GENERAL_FAILURE.
+     *
+     * When the asynchronous task has finished preparing the model, it must immediately invoke the
+     * callback function provided as an input to prepareModelFromCache. If the model was prepared
+     * successfully, the callback object must be invoked with an error status of ErrorStatus::NONE
+     * and the produced IPreparedModel object. If an error occurred preparing the model, the
+     * callback object must be invoked with the appropriate ErrorStatus value and nullptr for the
+     * IPreparedModel.
+     *
+     * prepareModelFromCache can be called with an optional deadline. If the model is not able to
+     * prepared before the provided deadline, the model preparation may be aborted, and either
+     * {@link ErrorStatus::MISSED_DEADLINE_TRANSIENT} or
+     * {@link ErrorStatus::MISSED_DEADLINE_PERSISTENT} may be returned. The error due to an abort
+     * must be sent the same way as other errors, described above.
+     *
+     * The only information that may be unknown to the model at this stage is the shape of the
+     * tensors, which may only be known at execution time. As such, some driver services may return
+     * partially prepared models, where the prepared model may only be finished when it is paired
+     * with a set of inputs to the model. Note that the same prepared model object may be used with
+     * different shapes of inputs on different (possibly concurrent) executions.
+     *
+     * @param deadline The time by which the model is expected to be prepared. The time is measured
+     *                 in nanoseconds since epoch of the steady clock (as from
+     *                 std::chrono::steady_clock). If the model cannot be prepared by the deadline,
+     *                 the preparation may be aborted. Passing -1 means the deadline is omitted.
+     *                 Other negative values are invalid.
+     * @param modelCache A vector of file descriptors for the security-sensitive cache. The length
+     *                   of the vector must match the numModelCache returned from
+     *                   getNumberOfCacheFilesNeeded. The cache file descriptors will be provided in
+     *                   the same order as with prepareModel.
+     * @param dataCache A vector of file descriptors for the constants' cache. The length of the
+     *                  vector must match the numDataCache returned from
+     *                  getNumberOfCacheFilesNeeded. The cache file descriptors will be provided in
+     *                  the same order as with prepareModel.
+     * @param token A caching token of length BYTE_SIZE_OF_CACHE_TOKEN identifying the prepared
+     *              model. It is the same token provided when saving the cache files with
+     *              prepareModel. Tokens should be chosen to have a low rate of collision for a
+     *              particular application. The driver cannot detect a collision; a collision will
+     *              result in a failed execution or in a successful execution that produces
+     *              incorrect output values.
+     * @param callback A callback object used to return the error status of preparing the model for
+     *                 execution and the prepared model if successful, nullptr otherwise. The
+     *                 callback object's notify function must be called exactly once, even if the
+     *                 model could not be prepared.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if caching is not supported or if there is an unspecified error
+     *     - INVALID_ARGUMENT if one of the input arguments is invalid
+     *     - MISSED_DEADLINE_* if the preparation is aborted because the model cannot be prepared by
+     *       the deadline
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    void prepareModelFromCache(in long deadline, in ParcelFileDescriptor[] modelCache,
+            in ParcelFileDescriptor[] dataCache, in byte[] token,
+            in IPreparedModelCallback callback);
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IFencedExecutionCallback.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IFencedExecutionCallback.aidl
new file mode 100644
index 0000000..cb6db11
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IFencedExecutionCallback.aidl
@@ -0,0 +1,55 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.ErrorStatus;
+import android.hardware.neuralnetworks.Timing;
+
+/**
+ * IFencedExecutionCallback can be used to query the error status result and duration information
+ * from an IPreparedModel::executeFenced call.
+ */
+@VintfStability
+interface IFencedExecutionCallback {
+    /**
+     * The getExecutionInfo method is used by the clients to query error status result and duration
+     * information. The method must only be called after the actual evaluation has finished or
+     * resulted in an runtime error, as indicated by the status of the sync fence returned by the
+     * IPreparedModel::executeFenced call, otherwise GENERAL_FAILURE must be returned.
+     *
+     * @param out timingLaunched The duration starts when executeFenced is called and ends when
+     *                           executeFenced signals the returned syncFence. Unless measureTiming
+     *                           was set to true when launching the execution and status is NONE,
+     *                           all times must be reported as -1. A driver may choose to report any
+     *                           time as -1, indicating that particular measurement is not
+     *                           available.
+     * @param out timingFenced The duration starts when all waitFor sync fences have been signaled
+     *                         and ends when executeFenced signals the returned syncFence. Unless
+     *                         measureTiming was set to true when launching the execution and status
+     *                         is NONE, all times must be reported as -1. A driver may choose to
+     *                         report any time as -1, indicating that particular measurement is not
+     *                         available.
+     * @return Error status returned from the asynchronously dispatched execution must be:
+     *     - NONE if the asynchronous execution was successful
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if the asynchronous task resulted in an unspecified error
+     *     - MISSED_DEADLINE_* if the execution is aborted because it cannot be completed by the
+     *       deadline
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    ErrorStatus getExecutionInfo(out Timing timingLaunched, out Timing timingFenced);
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModel.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModel.aidl
new file mode 100644
index 0000000..2414a4a
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModel.aidl
@@ -0,0 +1,172 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.common.NativeHandle;
+import android.hardware.neuralnetworks.ErrorStatus;
+import android.hardware.neuralnetworks.ExecutionResult;
+import android.hardware.neuralnetworks.IFencedExecutionCallback;
+import android.hardware.neuralnetworks.Request;
+
+/**
+ * IPreparedModel describes a model that has been prepared for execution and is used to launch
+ * executions.
+ */
+@VintfStability
+interface IPreparedModel {
+    /**
+     * Each {@link OperationType::WHILE} operation in the model has an implicit execution timeout
+     * duration associated with it ("loop timeout duration"). This duration is configurable on a
+     * per-execution basis and must not exceed 15 seconds. The default value is 2 seconds. The units
+     * are nanoseconds.
+     */
+    const long DEFAULT_LOOP_TIMEOUT_DURATION_NS = 2000000000;
+    const long MAXIMUM_LOOP_TIMEOUT_DURATION_NS = 15000000000;
+
+    /**
+     * Performs a synchronous execution on a prepared model.
+     *
+     * The execution is performed synchronously with respect to the caller. executeSynchronously
+     * must verify the inputs to the function are correct, and the usages of memory pools allocated
+     * by IDevice::allocate are valid. If there is an error, executeSynchronously must immediately
+     * return a service specific exception with the appropriate ErrorStatus value. If the inputs to
+     * the function are valid and there is no error, executeSynchronously must perform the
+     * execution, and must not return until the execution is complete.
+     *
+     * The caller must not change the content of any data object referenced by 'request' (described
+     * by the {@link DataLocation} of a {@link RequestArgument}) until executeSynchronously returns.
+     * executeSynchronously must not change the content of any of the data objects corresponding to
+     * 'request' inputs.
+     *
+     * If the prepared model was prepared from a model wherein all tensor operands have fully
+     * specified dimensions, and the inputs to the function are valid, and at execution time every
+     * operation's input operands have legal values, then the execution should complete
+     * successfully: there must be no failure unless the device itself is in a bad state.
+     *
+     * executeSynchronously may be called with an optional deadline. If the execution is not able to
+     * be completed before the provided deadline, the execution may be aborted, and either
+     * {@link ErrorStatus::MISSED_DEADLINE_TRANSIENT} or {@link
+     * ErrorStatus::MISSED_DEADLINE_PERSISTENT} may be returned. The error due to an abort must be
+     * sent the same way as other errors, described above.
+     *
+     * Any number of calls to the execute* functions, in any combination, may be made concurrently,
+     * even on the same IPreparedModel object.
+     *
+     * @param request The input and output information on which the prepared model is to be
+     *                executed.
+     * @param measure Specifies whether or not to measure duration of the execution. The duration
+     *                runs from the time the driver sees the call to the executeSynchronously
+     *                function to the time the driver returns from the function.
+     * @param deadline The time by which the execution is expected to complete. The time is measured
+     *                 in nanoseconds since epoch of the steady clock (as from
+     *                 std::chrono::steady_clock). If the execution cannot be finished by the
+     *                 deadline, the execution may be aborted. Passing -1 means the deadline is
+     *                 omitted. Other negative values are invalid.
+     * @param loopTimeoutDuration The maximum amount of time in nanoseconds that should be spent
+     *                            executing a {@link OperationType::WHILE} operation. If a loop
+     *                            condition model does not output false within this duration, the
+     *                            execution must be aborted. If -1 is provided, the maximum amount
+     *                            of time is {@link DEFAULT_LOOP_TIMEOUT_DURATION_NS}. Other
+     *                            negative values are invalid. When provided, the duration must not
+     *                            exceed {@link MAXIMUM_LOOP_TIMEOUT_DURATION_NS}.
+     * @return ExecutionResult parcelable, containing the status of the execution, output shapes and
+     *     timing information.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if one of the input arguments is invalid
+     *     - MISSED_DEADLINE_* if the execution is aborted because it cannot be completed by the
+     *       deadline
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    ExecutionResult executeSynchronously(in Request request, in boolean measureTiming,
+            in long deadline, in long loopTimeoutDuration);
+
+    /**
+     * Launch a fenced asynchronous execution on a prepared model.
+     *
+     * The execution is performed asynchronously with respect to the caller. executeFenced must
+     * verify the inputs to the function are correct, and the usages of memory pools allocated by
+     * IDevice::allocate are valid. If there is an error, executeFenced must immediately return a
+     * service specific exception with the corresponding ErrorStatus. If the inputs to the function
+     * are valid and there is no error, executeFenced must dispatch an asynchronous task to perform
+     * the execution in the background, assign a sync fence that will be signaled once the execution
+     * is completed and immediately return a callback that can be used by the client to query the
+     * duration and runtime error status. If the task has finished before the call returns,
+     * syncFence file descriptor may be set to -1. The execution must wait for all the sync fences
+     * (if any) in waitFor to be signaled before starting the actual execution.
+     *
+     * When the asynchronous task has finished its execution, it must immediately signal the
+     * syncFence returned from the executeFenced call. After the syncFence is signaled, the task
+     * must not modify the content of any data object referenced by 'request' (described by the
+     * {@link DataLocation} of a {@link RequestArgument}).
+     *
+     * executeFenced may be called with an optional deadline and an optional duration. If the
+     * execution is not able to be completed before the provided deadline or within the timeout
+     * duration (measured from when all sync fences in waitFor are signaled), whichever comes
+     * earlier, the execution may be aborted, and either
+     * {@link ErrorStatus::MISSED_DEADLINE_TRANSIENT} or {@link
+     * ErrorStatus::MISSED_DEADLINE_PERSISTENT} may be returned. The error due to an abort must be
+     * sent the same way as other errors, described above.
+     *
+     * If any of the sync fences in waitFor changes to error status after the executeFenced call
+     * succeeds, or the execution is aborted because it cannot finish before the deadline has been
+     * reached or the duration has elapsed, the driver must immediately set the returned syncFence
+     * to error status.
+     *
+     * Any number of calls to the execute* functions, in any combination, may be made concurrently,
+     * even on the same IPreparedModel object.
+     *
+     * @param request The input and output information on which the prepared model is to be
+     *                executed. The outputs in the request must have fully specified dimensions.
+     * @param waitFor A vector of sync fence file descriptors. Execution must not start until all
+     *                sync fences have been signaled.
+     * @param measure Specifies whether or not to measure duration of the execution.
+     * @param deadline The time by which the execution is expected to complete. The time is measured
+     *                 in nanoseconds since epoch of the steady clock (as from
+     *                 std::chrono::steady_clock).If the execution cannot be finished by the
+     *                 deadline, the execution may be aborted. Passing -1 means the deadline is
+     *                 omitted. Other negative values are invalid.
+     * @param loopTimeoutDuration The maximum amount of time in nanoseconds that should be spent
+     *                            executing a {@link OperationType::WHILE} operation. If a loop
+     *                            condition model does not output false within this duration, the
+     *                            execution must be aborted. If -1 is provided, the maximum amount
+     *                            of time is {@link DEFAULT_LOOP_TIMEOUT_DURATION_NS}. Other
+     *                            negative values are invalid. When provided, the duration must not
+     *                            exceed {@link MAXIMUM_LOOP_TIMEOUT_DURATION_NS}.
+     * @param duration The length of time in nanoseconds within which the execution is expected to
+     *                 complete after all sync fences in waitFor are signaled. If the execution
+     *                 cannot be finished within the duration, the execution may be aborted. Passing
+     *                 -1 means the duration is omitted. Other negative values are invalid.
+     * @param out syncFence The sync fence that will be signaled when the task is completed. The
+     *                      sync fence will be set to error if a critical error, e.g. hardware
+     *                      failure or kernel panic, occurs when doing execution.
+     * @return The IFencedExecutionCallback can be used to query information like duration and error
+     *     status when the execution is completed.
+     * @throws ServiceSpecificException with one of the following ErrorStatus values:
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if one of the input arguments is invalid, including fences in error
+     *       states.
+     *     - MISSED_DEADLINE_* if the execution is aborted because it cannot be completed by the
+     *       deadline
+     *     - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     */
+    IFencedExecutionCallback executeFenced(in Request request, in ParcelFileDescriptor[] waitFor,
+            in boolean measureTiming, in long deadline, in long loopTimeoutDuration,
+            in long duration, out @nullable ParcelFileDescriptor syncFence);
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModelCallback.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModelCallback.aidl
new file mode 100644
index 0000000..29cca6d
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModelCallback.aidl
@@ -0,0 +1,50 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.ErrorStatus;
+import android.hardware.neuralnetworks.IPreparedModel;
+
+/**
+ * IPreparedModelCallback must be used to return a prepared model produced by an asynchronous task
+ * launched from IDevice::prepareModel*.
+ */
+@VintfStability
+interface IPreparedModelCallback {
+    /**
+     * Notify must be invoked immediately after the asynchronous task holding this callback has
+     * finished preparing the model. If the model was successfully prepared, the method must be
+     * invoked with ErrorStatus::NONE and the prepared model. If the model was not able to be
+     * successfully prepared, the method must be invoked with the appropriate ErrorStatus and
+     * nullptr as the IPreparedModel. If the asynchronous task holding this callback fails to launch
+     * or if the model provided to IDevice::prepareModel is invalid, notify method must be invoked
+     * with the appropriate error as well as nullptr for the IPreparedModel.
+     *
+     * @param status Error status returned from the asynchronous model preparation task; must be:
+     *               - NONE if the asynchronous task successfully prepared the model
+     *               - DEVICE_UNAVAILABLE if driver is offline or busy
+     *               - GENERAL_FAILURE if the asynchronous task resulted in an unspecified error
+     *               - INVALID_ARGUMENT if one of the input arguments to prepareModel is invalid
+     *               - MISSED_DEADLINE_* if the preparation is aborted because the model cannot be
+     *                 prepared by the deadline
+     *               - RESOURCE_EXHAUSTED_* if the task was aborted by the driver
+     * @param preparedModel A model that has been asynchronously prepared for execution. If the
+     *                      model was unable to be prepared due to an error, nullptr must be passed
+     *                      in place of the IPreparedModel object.
+     */
+    void notify(in ErrorStatus status, in IPreparedModel preparedModel);
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModelParcel.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModelParcel.aidl
new file mode 100644
index 0000000..878b0ad
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/IPreparedModelParcel.aidl
@@ -0,0 +1,27 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.IPreparedModel;
+
+/**
+ * A parcelable for passing a vector of IPreparedModel objects.
+ */
+@VintfStability
+parcelable IPreparedModelParcel {
+    IPreparedModel preparedModel;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Memory.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Memory.aidl
new file mode 100644
index 0000000..870f0ae
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Memory.aidl
@@ -0,0 +1,30 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+import android.hardware.common.NativeHandle;
+import android.os.ParcelFileDescriptor;
+
+/**
+ * A type that is used to pass pieces of shared memory between processes.
+ * The type structure mimics hidl_memory type from HIDL.
+ */
+@VintfStability
+parcelable Memory {
+    NativeHandle handle;
+    long size;
+    String name;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Model.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Model.aidl
new file mode 100644
index 0000000..2f11dec
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Model.aidl
@@ -0,0 +1,69 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.ExtensionNameAndPrefix;
+import android.hardware.neuralnetworks.Memory;
+import android.hardware.neuralnetworks.Subgraph;
+
+/**
+ * A Neural Network Model.
+ *
+ * This includes not only the execution graph, but also constant data such as weights or scalars
+ * added at construction time. The only information that may not be known is the shape of the input
+ * tensors.
+ */
+@VintfStability
+parcelable Model {
+    /**
+     * The top-level subgraph.
+     */
+    Subgraph main;
+    /**
+     * Referenced subgraphs.
+     *
+     * Each subgraph is referenced by the main subgraph or at least one other referenced subgraph.
+     *
+     * There must be no reference cycles.
+     */
+    Subgraph[] referenced;
+    /**
+     * A byte buffer containing operand data that were copied into the model.
+     *
+     * An operand's value must be located here if and only if Operand::lifetime equals
+     * OperandLifeTime::CONSTANT_COPY.
+     */
+    byte[] operandValues;
+    /**
+     * A collection of shared memory pools containing operand values.
+     *
+     * An operand's value must be located here if and only if Operand::lifetime equals
+     * OperandLifeTime::CONSTANT_POOL.
+     */
+    Memory[] pools;
+    /**
+     * 'true' indicates TENSOR_FLOAT32 may be calculated with range and/or precision as low as that
+     * of the IEEE 754 16-bit floating-point format.
+     * 'false' indicates TENSOR_FLOAT32 must be calculated using at least the range and precision of
+     * the IEEE 754 32-bit floating-point format.
+     */
+    boolean relaxComputationFloat32toFloat16;
+    /**
+     * The mapping between extension names and prefixes of operand and operation type values.
+     */
+    ExtensionNameAndPrefix[] extensionNameToPrefix;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/NumberOfCacheFiles.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/NumberOfCacheFiles.aidl
new file mode 100644
index 0000000..1ca2676
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/NumberOfCacheFiles.aidl
@@ -0,0 +1,27 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Structure indicating how many files for model and numDataCache cache the driver needs to cache a
+ * single prepared model.
+ */
+@VintfStability
+parcelable NumberOfCacheFiles {
+    int numModelCache;
+    int numDataCache;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Operand.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Operand.aidl
new file mode 100644
index 0000000..4d2260f
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Operand.aidl
@@ -0,0 +1,112 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.DataLocation;
+import android.hardware.neuralnetworks.OperandExtraParams;
+import android.hardware.neuralnetworks.OperandLifeTime;
+import android.hardware.neuralnetworks.OperandType;
+
+/**
+ * Describes one operand of the model's graph.
+ */
+@VintfStability
+parcelable Operand {
+    /**
+     * The data type.
+     *
+     * Besides the values listed in {@link OperandType}, any value above
+     * {@link IDevice::OPERAND_TYPE_BASE_MAX} is possible and should be interpreted as an extension
+     * type according to {@link Model::extensionNameToPrefix}.
+     */
+    OperandType type;
+    /**
+     * Dimensions of the operand.
+     *
+     * For a scalar operand, dimensions.size() must be 0.
+     *
+     * A tensor operand with all dimensions specified has "fully specified" dimensions. Whenever
+     * possible (i.e., whenever the dimensions are known at model construction time), a tensor
+     * operand should have (but is not required to have) fully specified dimensions, in order to
+     * enable the best possible performance.
+     *
+     * If a tensor operand's dimensions are not fully specified, the dimensions of the operand are
+     * deduced from the operand dimensions and values of the operation for which that operand is an
+     * output or from the corresponding {@link OperationType::IF} or {@link OperationType::WHILE}
+     * operation input operand dimensions in the case of referenced subgraph input operands.
+     *
+     * In the following situations, a tensor operand's dimensions must be fully specified:
+     *
+     *     . The operand has lifetime CONSTANT_COPY or CONSTANT_POOL.
+     *
+     *     . The operand has lifetime SUBGRAPH_INPUT and belongs to the main subgraph. Fully
+     *       specified dimensions must either be present in the Operand or they must be provided in
+     *       the corresponding RequestArgument.
+     *       EXCEPTION: If the input is optional and omitted (by setting the hasNoValue field of the
+     *       corresponding RequestArgument to true) then it need not have fully specified
+     *       dimensions.
+     *
+     * A tensor operand with some number of unspecified dimensions is represented by setting each
+     * unspecified dimension to 0.
+     *
+     * A tensor operand with unspecified rank is represented by providing an empty dimensions
+     * vector.
+     */
+    int[] dimensions;
+    /**
+     * Quantized scale of the operand.
+     *
+     * Must be 0 when not applicable to an operand type.
+     *
+     * See {@link OperandType}.
+     */
+    float scale;
+    /**
+     * Quantized zero-point offset of the operand.
+     *
+     * Must be 0 when not applicable to an operand type.
+     *
+     * See {@link OperandType}.
+     */
+    int zeroPoint;
+    /**
+     * How the operand is used.
+     */
+    OperandLifeTime lifetime;
+    /**
+     * Where to find the data for this operand.
+     * If the lifetime is TEMPORARY_VARIABLE, SUBGRAPH_INPUT, SUBGRAPH_OUTPUT, or NO_VALUE:
+     * - All the fields must be 0.
+     * If the lifetime is CONSTANT_COPY:
+     * - location.poolIndex is 0.
+     * - location.offset is the offset in bytes into Model.operandValues.
+     * - location.length is set.
+     * If the lifetime is CONSTANT_POOL:
+     * - location.poolIndex is set.
+     * - location.offset is the offset in bytes into the specified pool.
+     * - location.length is set.
+     * If the lifetime is SUBGRAPH:
+     * - location.poolIndex is 0.
+     * - location.offset is the index of the referenced subgraph in {@link Model::referenced}.
+     * - location.length is 0.
+     */
+    DataLocation location;
+    /**
+     * Additional parameters specific to a particular operand type.
+     */
+    @nullable OperandExtraParams extraParams;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandExtraParams.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandExtraParams.aidl
new file mode 100644
index 0000000..229754a
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandExtraParams.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.SymmPerChannelQuantParams;
+
+/**
+ * Parameters specific to a particular operand type.
+ */
+@VintfStability
+union OperandExtraParams {
+    /**
+     * Symmetric per-channel quantization parameters.
+     *
+     * Only applicable to operands of type TENSOR_QUANT8_SYMM_PER_CHANNEL.
+     */
+    SymmPerChannelQuantParams channelQuant;
+    /**
+     * Extension operand parameters.
+     *
+     * The framework treats this as an opaque data blob.
+     * The format is up to individual extensions.
+     */
+    byte[] extension;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandLifeTime.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandLifeTime.aidl
new file mode 100644
index 0000000..1d18149
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandLifeTime.aidl
@@ -0,0 +1,62 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * How an operand is used.
+ */
+@VintfStability
+@Backing(type="int")
+enum OperandLifeTime {
+    /**
+     * The operand is internal to the model. It's created by an operation and consumed by other
+     * operations. It must be an output operand of exactly one operation.
+     */
+    TEMPORARY_VARIABLE,
+    /**
+     * The operand is an input of a subgraph. It must not be an output operand of any operation.
+     *
+     * An operand can't be both input and output of a subgraph.
+     */
+    SUBGRAPH_INPUT,
+    /**
+     * The operand is an output of a subgraph. It must be an output operand of exactly one
+     * operation.
+     *
+     * An operand can't be both input and output of a subgraph.
+     */
+    SUBGRAPH_OUTPUT,
+    /**
+     * The operand is a constant found in Model.operandValues. It must not be an output operand of
+     * any operation.
+     */
+    CONSTANT_COPY,
+    /**
+     * The operand is a constant that was specified via a Memory object. It must not be an output
+     * operand of any operation.
+     */
+    CONSTANT_POOL,
+    /**
+     * The operand does not have a value. This is valid only for optional arguments of operations.
+     */
+    NO_VALUE,
+    /**
+     * The operand is a reference to a subgraph. It must be an input to one or more
+     * {@link OperationType::IF} or {@link OperationType::WHILE} operations.
+     */
+    SUBGRAPH,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandPerformance.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandPerformance.aidl
new file mode 100644
index 0000000..7fd86f9
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandPerformance.aidl
@@ -0,0 +1,30 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.OperandType;
+import android.hardware.neuralnetworks.PerformanceInfo;
+
+/**
+ * Driver performance when operating on a particular data type. In the case of float32 data, this is
+ * used when the calculations are not relaxed.
+ */
+@VintfStability
+parcelable OperandPerformance {
+    OperandType type;
+    PerformanceInfo info;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandType.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandType.aidl
new file mode 100644
index 0000000..12edc0f
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperandType.aidl
@@ -0,0 +1,153 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Operand types.
+ *
+ * The type of an operand in a model.
+ *
+ * Types prefaced with TENSOR_* must be used for tensor data (i.e., tensors
+ * with at least one dimension). Types not prefaced by TENSOR_* represent
+ * scalar values and must have no dimensions.
+ */
+@VintfStability
+@Backing(type="int")
+enum OperandType {
+    /**
+     * A 32 bit floating point scalar value.
+     */
+    FLOAT32 = 0,
+    /**
+     * A signed 32 bit integer scalar value.
+     */
+    INT32 = 1,
+    /**
+     * An unsigned 32 bit integer scalar value.
+     */
+    UINT32 = 2,
+    /**
+     * A tensor of 32 bit floating point values.
+     */
+    TENSOR_FLOAT32 = 3,
+    /**
+     * A tensor of 32 bit integer values.
+     */
+    TENSOR_INT32 = 4,
+    /**
+     * A tensor of 8 bit unsigned integers that represent real numbers.
+     *
+     * Attached to this tensor are two numbers that can be used to convert the 8 bit integer to the
+     * real value and vice versa. These two numbers are:
+     * - scale: a 32 bit floating point value greater than zero.
+     * - zeroPoint: a 32 bit integer, in range [0, 255].
+     *
+     * The formula is:
+     *   real_value = (integer_value - zeroPoint) * scale.
+     */
+    TENSOR_QUANT8_ASYMM = 5,
+    /**
+     * An 8 bit boolean scalar value.
+     *
+     * Values of this operand type are either true or false. A zero value represents false; any
+     * other value represents true.
+     */
+    BOOL = 6,
+    /**
+     * A tensor of 16 bit signed integers that represent real numbers.
+     *
+     * Attached to this tensor is a number representing real value scale that is used to convert the
+     * 16 bit number to a real value in the following way:
+     * realValue = integerValue * scale.
+     *
+     * scale is a 32 bit floating point with value greater than zero.
+     */
+    TENSOR_QUANT16_SYMM = 7,
+    /**
+     * A tensor of IEEE 754 16 bit floating point values.
+     */
+    TENSOR_FLOAT16 = 8,
+    /**
+     * A tensor of 8 bit boolean values.
+     *
+     * Values of this operand type are either true or false. A zero value represents false; any
+     * other value represents true.
+     */
+    TENSOR_BOOL8 = 9,
+    /**
+     * An IEEE 754 16 bit floating point scalar value.
+     */
+    FLOAT16 = 10,
+    /**
+     * A tensor of 8 bit signed integers that represent real numbers.
+     *
+     * This tensor is associated with additional fields that can be used to convert the 8 bit signed
+     * integer to the real value and vice versa. These fields are:
+     * - channelDim: a 32 bit unsigned integer indicating channel dimension.
+     * - scales: an array of positive 32 bit floating point values.
+     * The size of the scales array must be equal to dimensions[channelDim].
+     *
+     * {@link SymmPerChannelQuantParams} must hold the parameters for an Operand of this type.
+     * The channel dimension of this tensor must not be unknown (dimensions[channelDim] != 0).
+     *
+     * The formula is:
+     * realValue[..., C, ...] =
+     *     integerValue[..., C, ...] * scales[C]
+     * where C is an index in the Channel dimension.
+     */
+    TENSOR_QUANT8_SYMM_PER_CHANNEL = 11,
+    /**
+     * A tensor of 16 bit unsigned integers that represent real numbers.
+     *
+     * Attached to this tensor are two numbers that can be used to convert the 16 bit integer to the
+     * real value and vice versa. These two numbers are:
+     * - scale: a 32 bit floating point value greater than zero.
+     * - zeroPoint: a 32 bit integer, in range [0, 65535].
+     *
+     * The formula is:
+     * real_value = (integer_value - zeroPoint) * scale.
+     */
+    TENSOR_QUANT16_ASYMM = 12,
+    /**
+     * A tensor of 8 bit signed integers that represent real numbers.
+     *
+     * Attached to this tensor is a number representing real value scale that is used to convert the
+     * 8 bit number to a real value in the following way:
+     * realValue = integerValue * scale.
+     *
+     * scale is a 32 bit floating point with value greater than zero.
+     */
+    TENSOR_QUANT8_SYMM = 13,
+    /**
+     * A tensor of 8 bit signed integers that represent real numbers.
+     *
+     * Attached to this tensor are two numbers that can be used to convert the 8 bit integer to the
+     * real value and vice versa. These two numbers are:
+     * - scale: a 32 bit floating point value greater than zero.
+     * - zeroPoint: a 32 bit integer, in range [-128, 127].
+     *
+     * The formula is:
+     * real_value = (integer_value - zeroPoint) * scale.
+     */
+    TENSOR_QUANT8_ASYMM_SIGNED = 14,
+    /**
+     * A reference to a subgraph.
+     *
+     * Must have the lifetime {@link OperandLifeTime::SUBGRAPH}.
+     */
+    SUBGRAPH = 15,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Operation.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Operation.aidl
new file mode 100644
index 0000000..0c6032f
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Operation.aidl
@@ -0,0 +1,44 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.OperationType;
+
+/**
+ * Describes one operation of the model's graph.
+ */
+@VintfStability
+parcelable Operation {
+    /**
+     * The operation type.
+     *
+     * Besides the values listed in {@link OperationType}, any value above
+     * {@link IDevice::OPERATION_TYPE_BASE_MAX} is possible and should be interpreted as an
+     * extension type according to {@link Model::extensionNameToPrefix}.
+     */
+    OperationType type;
+    /**
+     * Describes the table that contains the indexes of the inputs of the operation. The offset is
+     * the index in the operandIndexes table.
+     */
+    int[] inputs;
+    /**
+     * Describes the table that contains the indexes of the outputs of the operation. The offset is
+     * the index in the operandIndexes table.
+     */
+    int[] outputs;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/OperationType.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperationType.aidl
new file mode 100644
index 0000000..3f49154
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/OperationType.aidl
@@ -0,0 +1,5131 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Operation types.
+ *
+ * The type of an operation in a model.
+ */
+@VintfStability
+@Backing(type="int")
+enum OperationType {
+    /**
+     * Adds two tensors, element-wise.
+     *
+     * Takes two input tensors of identical {@link OperandType} and compatible
+     * dimensions. The output is the sum of both input tensors, optionally
+     * modified by an activation function.
+     *
+     * Two dimensions are compatible when:
+     *     1. they are equal, or
+     *     2. one of them is 1
+     *
+     * The size of the output is the maximum size along each dimension of the
+     * input operands. It starts with the trailing dimensions, and works its
+     * way forward.
+     *
+     * Example:
+     *
+     *     input1.dimension = {4, 1, 2}
+     *     input2.dimension = {5, 4, 3, 1}
+     *     output.dimension = {5, 4, 3, 2}
+     *
+     * Since HAL version 1.2, generic zero-sized input tensor is supported. Zero
+     * dimension is only compatible with 0 or 1. The size of the output
+     * dimension is zero if either of corresponding input dimension is zero.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     * * {@link OperandType::TENSOR_INT32} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType}, and compatible dimensions
+     *      as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scales and zeroPoint can be different from input0 scale and zeroPoint.
+     * * 2: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     *      For a {@link OperandType::TENSOR_INT32} tensor,
+     *      the {@link FusedActivationFunc} must be "NONE".
+     *
+     * Outputs:
+     * * 0: The sum, a tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.
+     */
+    ADD = 0,
+    /**
+     * Performs a 2-D average pooling operation.
+     *
+     * The output dimensions are functions of the filter dimensions, stride, and
+     * padding.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[b, i, j, channel] =
+     *         sum_{di, dj}(
+     *             input[b, strides[1] * i + di, strides[2] * j + dj, channel]
+     *         ) / sum(1)
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Both explicit padding and implicit padding are supported.
+     *
+     * Inputs (explicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the left, in the ‘width’ dimension.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the right, in the ‘width’ dimension.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the top, in the ‘height’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the bottom, in the ‘height’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the filter
+     *      width.
+     * * 8: An {@link OperandType::INT32} scalar, specifying the filter
+     *      height.
+     * * 9: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 10: An optional {@link OperandType::BOOL} scalar, default to false.
+     *       Set to true to specify NCHW data layout for input0 and output0.
+     *       Available since HAL version 1.2.
+     *
+     * Inputs (implicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the implicit
+     *      padding scheme, has to be one of the
+     *      following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the filter
+     *      width.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the filter
+     *      height.
+     * * 6: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 7: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, out_height, out_width, depth].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    AVERAGE_POOL_2D = 1,
+    /**
+     * Concatenates the input tensors along the given dimension.
+     *
+     * The input tensors must have identical {@link OperandType} and the same
+     * dimensions except the dimension along the concatenation axis.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *   (full support since HAL version 1.2, see the input section)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0 ~ n-1: The list of n input tensors, of shape
+     *            [D0, D1, ..., Daxis(i), ..., Dm].
+     *            Before HAL version 1.2, all input tensors of
+     *            {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *            must have the same scale and zeroPoint as the output tensor.
+     *            Input tensors of
+     *            {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *            are allowed to have different scale and zeroPoint.
+     *            Since HAL version 1.2, zero-sized tensors are supported.
+     * * n: An {@link OperandType::INT32} scalar, specifying the
+     *      concatenation axis.
+     *
+     * Outputs:
+     * * 0: The output, a tensor of the same {@link OperandType} as the input
+     *      tensors. The output shape is [D0, D1, ..., sum(Daxis(i)), ..., Dm].
+     *      Since HAL version 1.2, for a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
+     *      the scale and zeroPoint values can be different from
+     *      input tensors. Before HAL version 1.2 they have to be the same as for the input tensors.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint values can be different from input tensors.
+     */
+    CONCATENATION = 2,
+    /**
+     * Performs a 2-D convolution operation.
+     *
+     * The CONV_2D op sweeps a 2-D filter that can mix channels together over a
+     * batch of images, applying the filter to each window of each image of the
+     * appropriate size.
+     *
+     * The output dimensions are functions of the filter dimensions, stride, and
+     * padding.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[b, i, j, channel] =
+     *         sum_{di, dj, k} (
+     *             input[b, strides[1] * i + di, strides[2] * j + dj, k] *
+     *             filter[channel, di, dj, k]
+     *         ) + bias[channel]
+     *
+     * Supported tensor {@link OperandType} configurations:
+     * * 32 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT32} for input, filter, output, and bias.
+     *
+     * * Quantized:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * Available since HAL version 1.2:
+     * * 16 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT16} for input, filter, output, and bias.
+     *
+     * * Quantized with symmetric per channel quantization for the filter:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * Available since HAL version 1.3:
+     * * Quantized signed (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Both explicit padding and implicit padding are supported.
+     *
+     * Inputs (explicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: A 4-D tensor, of shape
+     *      [depth_out, filter_height, filter_width, depth_in], specifying the
+     *      filter.
+     *      For tensor of type {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
+     *      the channel dimension (SymmPerChannelQuantParams::channelDim)
+     *      must be set to 0.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32}
+     *      or {@link OperandType::TENSOR_FLOAT16} the bias must be of the same type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint
+     *      of 0 and bias_scale == input_scale * filter_scale.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0
+     *      and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the left, in the ‘width’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the right, in the ‘width’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the top, in the ‘height’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the bottom, in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 8: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 9: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 10: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     * * 11: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for width. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on width dimension. If this input is set,
+     *      input 12 (dilation factor for height) must be specified as well.
+     *      Available since HAL version 1.2.
+     * * 12: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for height. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on height dimension. If this input is set,
+     *      input 11 (dilation factor for width) must be specified as well.
+     *      Available since HAL version 1.2.
+     *
+     * Inputs (implicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: A 4-D tensor, of shape
+     *      [depth_out, filter_height, filter_width, depth_in], specifying the
+     *      filter.
+     *      For tensor of type {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
+     *      the channel dimension (SymmPerChannelQuantParams::channelDim)
+     *      must be set to 0.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32}
+     *      or {@link OperandType::TENSOR_FLOAT16} the bias must be of the same
+     *      type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint
+     *      of 0 and bias_scale == input_scale * filter_scale.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0
+     *      and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::INT32} scalar, specifying the implicit
+     *      padding scheme, has to be one of the
+     *      following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 7: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     * * 8: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for width. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on width dimension. If this input is set,
+     *      input 9 (dilation factor for height) must be specified as well.
+     *      Available since HAL version 1.2.
+     * * 9: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for height. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on height dimension. If this input is set,
+     *      input 8 (dilation factor for width) must be specified as well.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, out_height, out_width, depth_out].
+     *      Before HAL version 1.2, for output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      the following condition must be satisfied: output_scale > input_scale * filter_scale
+     */
+    CONV_2D = 3,
+    /**
+     * Performs a depthwise 2-D convolution operation.
+     *
+     * Given an input tensor of shape [batches, height, width, depth_in] and a
+     * filter tensor of shape [1, filter_height, filter_width, depth_out]
+     * containing depth_out convolutional filters of depth 1, DEPTHWISE_CONV
+     * applies a different filter to each input channel (expanding from 1
+     * channel to channel_multiplier channels for each), then concatenates the
+     * results together.
+     *
+     * The output has depth_out = depth_in * depth_multiplier channels.
+     * The output dimensions are functions of the filter dimensions, stride, and
+     * padding.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[b, i, j, k * channel_multiplier + q] =
+     *         sum_{di, dj} (
+     *             input[b, strides[1] * i + di, strides[2] * j + dj, k] *
+     *             filter[1, di, dj, k * channel_multiplier + q]
+     *         ) + bias[k * channel_multiplier + q]
+     *
+     * Supported tensor {@link OperandType} configurations:
+     * * 32 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT32} for input, filter, output, and bias.
+     *
+     * * Quantized:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * Available since HAL version 1.2:
+     * * 16 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT16} for input, filter, output, and bias.
+     *
+     * * Quantized with symmetric per channel quantization for the filter:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * Available since HAL version 1.3:
+     * * Quantized signed (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Both explicit padding and implicit padding are supported.
+     *
+     * Inputs (explicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     * * 1: A 4-D tensor, of shape [1, filter_height, filter_width, depth_out],
+     *      specifying the filter.
+     *      For tensor of type {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
+     *      the channel dimension (SymmPerChannelQuantParams::channelDim)
+     *      must be set to 3.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32}
+     *      or {@link OperandType::TENSOR_FLOAT16} the bias must be of the same type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint
+     *      of 0 and bias_scale == input_scale * filter_scale.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0
+     *      and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the left, in the ‘width’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the right, in the ‘width’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the top, in the ‘height’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the bottom, in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 8: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 9: An {@link OperandType::INT32} scalar, specifying the depthwise
+     *      multiplier.
+     * * 10: An {@link OperandType::INT32} scalar, and has to be one of the
+     *       {@link FusedActivationFunc} values. Specifies the activation to
+     *       invoke on the result.
+     * * 11: An optional {@link OperandType::BOOL} scalar, default to false.
+     *       Set to true to specify NCHW data layout for input0 and output0.
+     *       Available since HAL version 1.2.
+     * * 12: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for width. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on width dimension. If this input is set,
+     *      input 13 (dilation factor for height) must be specified as well.
+     *      Available since HAL version 1.2.
+     * * 13: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for height. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on height dimension. If this input is set,
+     *      input 12 (dilation factor for width) must be specified as well.
+     *      Available since HAL version 1.2.
+     *
+     * Inputs (implicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     * * 1: A 4-D tensor, of shape [1, filter_height, filter_width, depth_out],
+     *      specifying the filter.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32}
+     *      or {@link OperandType::TENSOR_FLOAT16} the bias must be of the same type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint
+     *      of 0 and bias_scale == input_scale * filter_scale.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL},
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0
+     *      and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::INT32} scalar, specifying the implicit
+     *      padding scheme, has to be one of the
+     *      following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the depthwise
+     *      multiplier.
+     * * 7: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 8: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     * * 9: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for width. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on width dimension. If this input is set,
+     *      input 10 (dilation factor for height) must be specified as well.
+     *      Available since HAL version 1.2.
+     * * 10: An optional {@link OperandType::INT32} scalar, specifying the dilation
+     *      factor for height. Defaults to 1. If set to k > 1, there will be k-1 skipped
+     *      cells between each filter element on height dimension. If this input is set,
+     *      input 9 (dilation factor for width) must be specified as well.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, out_height, out_width, depth_out]. Before HAL version 1.2, for
+     *      output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      the following condition must be satisfied:
+     *      output_scale > input_scale * filter_scale
+     */
+    DEPTHWISE_CONV_2D = 4,
+    /**
+     * Rearranges data from depth into blocks of spatial data.
+     *
+     * More specifically, this op outputs a copy of the input tensor where
+     * values from the depth dimension are moved in spatial blocks to the height
+     * and width dimensions. The value block_size indicates the input block size
+     * and how the data is moved.
+     *
+     * Chunks of data of size block_size * block_size from depth are rearranged
+     * into non-overlapping blocks of size block_size x block_size.
+     *
+     * The width of the output tensor is input_depth * block_size, whereas the
+     * height is input_height * block_size. The depth of the input tensor must
+     * be divisible by block_size * block_size
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Inputs:
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the block_size.
+     *      block_size must be >=1 and block_size * block_size must be a divisor
+     *      of the input depth.
+     * * 2: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape [batch, height*block_size,
+     *      width*block_size, depth/(block_size*block_size)].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    DEPTH_TO_SPACE = 5,
+    /**
+     * Dequantizes the input tensor.
+     *
+     * The formula is:
+     *
+     *     output = (input - zeroPoint) * scale.
+     *
+     * Supported input tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_SYMM} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported output tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}.
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     *
+     * Outputs:
+     * * 0: A tensor with the same shape as input0.
+     */
+    DEQUANTIZE = 6,
+    /**
+     * Looks up sub-tensors in the input tensor.
+     *
+     * This operator takes for input a tensor of values (Values) and
+     * a one-dimensional tensor of selection indices (Lookups).
+     * The output tensor is the concatenation of sub-tensors of Values as
+     * selected by Lookups.
+     *
+     * Think of Values as being sliced along its first dimension:
+     * The entries in Lookups select which slices are concatenated together
+     * to create the output tensor.
+     *
+     * For example, if Values has shape of [40, 200, 300] and
+     * Lookups has shape of [3], all three values found in Lookups are
+     * expected to be between 0 and 39. The resulting tensor must
+     * have shape of [3, 200, 300].
+     *
+     * If a value in Lookups is out of bounds, the operation must fail
+     * and an error must be reported.
+     *
+     * Supported value tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.3)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported value tensor rank: from 2
+     *
+     * Inputs:
+     * * 0: Lookups. A 1-D tensor of {@link OperandType::TENSOR_INT32}.
+     *      The values are indices into the first dimension of Values.
+     * * 1: Values. An n-D tensor, where n >= 2, from which sub-tensors are
+     *      extracted.
+     *
+     * Output:
+     * * 0: A n-D tensor with the same rank and shape as the Values
+     *      tensor, except for the first dimension which has the same size
+     *      as Lookups' only dimension.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input1.
+     */
+    EMBEDDING_LOOKUP = 7,
+    /**
+     * Computes element-wise floor() on the input tensor.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor, of the same {@link OperandType} and dimensions as
+     *      the input tensor.
+     */
+    FLOOR = 8,
+    /**
+     * Denotes a fully (densely) connected layer, which connects all elements
+     * in the input tensor with each element in the output tensor.
+     *
+     * This layer implements the operation:
+     *
+     *     outputs = activation(inputs * weights’ + bias)
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     *
+     * Inputs:
+     * * 0: A tensor of at least rank 2, specifying the input. If rank is
+     *      greater than 2, then it gets flattened to a 2-D Tensor. The
+     *      (flattened) 2-D Tensor is reshaped (if necessary) to
+     *      [batch_size, input_size], where "input_size" corresponds to the
+     *      number of inputs to the layer, matching the second dimension of
+     *      weights, and "batch_size" is calculated by dividing the number of
+     *      elements by "input_size".
+     *      Since HAL version 1.2, zero batch_size is supported for this tensor.
+     * * 1: A 2-D tensor, specifying the weights, of shape
+     *      [num_units, input_size], where "num_units" corresponds to the number
+     *      of output nodes.
+     * * 2: A 1-D tensor, of shape [num_units], specifying the bias. For input
+     *      tensor of {@link OperandType::TENSOR_FLOAT32}, the bias should
+     *      also be of {@link OperandType::TENSOR_FLOAT32}.
+     *      For input tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the bias should be of {@link OperandType::TENSOR_INT32},
+     *      with zeroPoint of 0 and bias_scale == input_scale * filter_scale.
+     * * 3: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     *
+     * Outputs:
+     * * 0: The output tensor, of shape [batch_size, num_units]. Before HAL version 1.2, for
+     *      output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}, the following
+     *      condition must be satisfied: output_scale > input_scale * filter_scale.
+     */
+    FULLY_CONNECTED = 9,
+    /**
+     * Looks up sub-tensors in the input tensor using a key-value map.
+     *
+     * This operator takes for input a tensor of values (Values),
+     * a one-dimensional tensor of selection values (Lookups) and
+     * a one-dimensional tensor that maps these values to Values
+     * indexes. The output tensor is the concatenation of sub-tensors of
+     * Values as selected by Lookups via Keys.
+     *
+     * Think of Values as being sliced along its outer-most dimension.
+     * The output is a concatenation of selected slices, with one slice
+     * for each entry of Lookups. The slice selected is the one at the
+     * same index as the Maps entry that matches the value in Lookups.
+     *
+     * For a hit, the corresponding sub-tensor of Values is included
+     * in the Output tensor. For a miss, the corresponding sub-tensor in
+     * Output must have zero values.
+     *
+     * For example, if Values has shape of [40, 200, 300],
+     * Keys should have a shape of [40]. If Lookups tensor has shape
+     * of [3], three slices are being concatenated, so the resulting tensor
+     * must have the shape of [3, 200, 300]. If the first entry in Lookups
+     * has the value 123456, that value must be located in Keys tensor.
+     * If the sixth entry of Keys contains 123456, the sixth slice of Values
+     * must be selected. If no entry in Keys has 123456, a slice of zeroes
+     * must be concatenated.
+     *
+     * Supported value tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *
+     * Supported value tensor rank: from 2
+     *
+     * Inputs:
+     * * 0: Lookups. A 1-D {@link OperandType::TENSOR_INT32} tensor with
+     *      shape [ k ].
+     * * 1: Keys. A 1-D {@link OperandType::TENSOR_INT32} tensor with shape
+     *      [ n ]; Keys and Values pair represent a map, i.e., the ith element
+     *      in Keys (Keys[i]) is the key to select the ith sub-tensor in Values
+     *      (Values[i]), where 0 <= i <= n-1. Keys tensor *MUST* be sorted in
+     *      ascending order.
+     * * 2: Values. A tensor with shape of [ n, … ]; i.e., the first dimension
+     *      must be n.
+     *
+     * Outputs:
+     * * 0: Output. A tensor with shape [ k …].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
+     *      the scale and zeroPoint must be the same as input2.
+     * * 1: Hits. A boolean tensor with shape [ k ] indicates whether the lookup
+     *      hits (True) or not (False).
+     *      Stored as {@link OperandType::TENSOR_QUANT8_ASYMM} with offset 0
+     *      and scale 1.0f.
+     *      A non-zero byte represents True, a hit. A zero indicates otherwise.
+     */
+    HASHTABLE_LOOKUP = 10,
+    /**
+     * Applies L2 normalization along the axis dimension.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[batch, row, col, channel] =
+     *         input[batch, row, col, channel] /
+     *         sqrt(sum_{c} pow(input[batch, row, col, c], 2))
+     *
+     * By default the axis dimension is the last dimension of the input tensor.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     * Tensors with rank less than 4 are only supported since HAL version 1.2.
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be normalized.
+     * * 1: An optional {@link OperandType::INT32} scalar, default to -1,
+     *      specifying the dimension normalization would be performed on.
+     *      Negative index is used to specify axis from the end (e.g. -1 for
+     *      the last axis). Must be in the range [-n, n).
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} and same shape as input0.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      the scale must be 1.f / 128 and the zeroPoint must be 128.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the scale must be 1.f / 128 and the zeroPoint must be 0.
+     *
+     *      NOTE: Before HAL version 1.3, if the elements along an axis are all zeros,
+     *      the result is undefined. Since HAL version 1.3, if the elements along an axis
+     *      are all zeros, the result is logical zero.
+     */
+    L2_NORMALIZATION = 11,
+    /**
+     * Performs an 2-D L2 pooling operation.
+     *
+     * The output dimensions are functions of the filter dimensions, stride, and
+     * padding.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[b, i, j, c] =
+     *         sqrt(sum_{di, dj} pow(input[b, strides[1] * i + di, strides[2] * j + dj, c], 2) /
+     *              sum(1))
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Both explicit padding and implicit padding are supported.
+     *
+     * Inputs (explicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the left, in the ‘width’ dimension.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the right, in the ‘width’ dimension.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the top, in the ‘height’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the bottom, in the ‘height’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the filter
+     *      width.
+     * * 8: An {@link OperandType::INT32} scalar, specifying the filter
+     *      height.
+     * * 9: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 10: An optional {@link OperandType::BOOL} scalar, default to false.
+     *       Set to true to specify NCHW data layout for input0 and output0.
+     *       Available since HAL version 1.2.
+     *
+     * Inputs (implicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the implicit
+     *      padding scheme, has to be one of the
+     *      following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the filter
+     *      width.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the filter
+     *      height.
+     * * 6: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 7: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, out_height, out_width, depth].
+     */
+    L2_POOL_2D = 12,
+    /**
+     * Applies Local Response Normalization along the depth dimension.
+     *
+     * The 4-D input tensor is treated as a 3-D array of 1-D vectors (along the
+     * last dimension), and each vector is normalized independently. Within a
+     * given vector, each component is divided by the weighted, squared sum of
+     * inputs within depth_radius.
+     *
+     * The output is calculated using this formula:
+     *
+     *     sqr_sum[a, b, c, d] = sum(
+     *         pow(input[a, b, c, d - depth_radius : d + depth_radius + 1], 2))
+     *     output = input / pow((bias + alpha * sqr_sum), beta)
+     *
+     * For input tensor with rank less than 4, independently normalizes each
+     * 1-D slice along specified dimension.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: up to 4
+     * Tensors with rank less than 4 are only supported since HAL version 1.2.
+     *
+     * Inputs:
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the radius of
+     *      the normalization window.
+     * * 2: A scalar, specifying the bias, must not be zero.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT16}, the bias
+     *      value must be of {@link OperandType::FLOAT16}.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT32}, the bias
+     *      value must be of {@link OperandType::FLOAT32}.
+     * * 3: A scalar, specifying the scale factor, alpha.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT16}, the
+     *      alpha value must be of {@link OperandType::FLOAT16}.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT32}, the
+     *      alpha value must be of {@link OperandType::FLOAT32}.
+     * * 4: A scalar, specifying the exponent, beta.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT16}, the beta
+     *      value must be of {@link OperandType::FLOAT16}.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT32}, the beta
+     *      value must be of {@link OperandType::FLOAT32}.
+     * * 5: An optional {@link OperandType::INT32} scalar, default to -1,
+     *      specifying the dimension normalization would be performed on.
+     *      Negative index is used to specify axis from the end (e.g. -1 for
+     *      the last axis). Must be in the range [-n, n).
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    LOCAL_RESPONSE_NORMALIZATION = 13,
+    /**
+     * Computes sigmoid activation on the input tensor element-wise.
+     *
+     * The output is calculated using this formula:
+     *
+     *     output = 1 / (1 + exp(-input))
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      the scale must be 1.f / 256 and the zeroPoint must be 0.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the scale must be 1.f / 256 and the zeroPoint must be -128.
+     */
+    LOGISTIC = 14,
+    /**
+     * Projects an input to a bit vector via locality senstive hashing.
+     *
+     * Supported input tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *
+     * Supported input tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: Hash functions. Dim.size == 2, DataType: Float.
+     *      Tensor[0].Dim[0]: 15 of hash functions.
+     *      Tensor[0].Dim[1]: 16 of projected output bits generated by each
+     *      hash function.
+     *      If the projection type is Sparse:
+     *      Tensor[0].Dim[1] + ceil(log2(Tensor[0].Dim[0])) <= 32
+     *
+     * * 1: Input. Dim.size >= 1, no restriction on DataType.
+     * * 2: Weight. Optional. Dim.size == 1, DataType: Float.
+     *      If not set, each input element is considered to have the same weight
+     *      of 1.0.
+     *      Tensor[1].Dim[0] == Tensor[2].Dim[0]
+     * * 3: Type:
+     *        Sparse:
+     *          Value LSHProjectionType_SPARSE(=3) (since HAL version 1.2).
+     *          Computed bit vector is considered to be sparse.
+     *          Each output element is an int32 made up of multiple bits
+     *          computed from hash functions.
+     *
+     *          NOTE: To avoid collisions across hash functions, an offset value
+     *          of k * (1 << Tensor[0].Dim[1]) will be added to each signature,
+     *          where k is the index of the hash function.
+     *
+     *          Value LSHProjectionType_SPARSE_DEPRECATED(=1).
+     *          Legacy behavior that does not include the offset value.
+     *
+     *        Dense:
+     *          Value LSHProjectionType_DENSE(=2).
+     *          Computed bit vector is considered to be dense. Each output
+     *          element represents a bit and can take the value of either
+     *          0 or 1.
+     *
+     * Outputs:
+     * * 0: If the projection type is Sparse:
+     *      Output.Dim == { Tensor[0].Dim[0] }
+     *      A tensor of int32 that represents hash signatures.
+     *
+     *      If the projection type is Dense:
+     *      Output.Dim == { Tensor[0].Dim[0] * Tensor[0].Dim[1] }
+     *      A flattened tensor that represents projected bit vectors.
+     * The offset value for sparse projections was added in HAL version 1.2.
+     */
+    LSH_PROJECTION = 15,
+    /**
+     * Performs a single time step in a Long Short-Term Memory (LSTM) layer
+     *
+     * The LSTM operation is described by the following equations.
+     *
+     * \f{eqnarray*}{
+     * i_t =& \sigma(W_{xi}x_t+W_{hi}h_{t-1}+W_{ci}C_{t-1}+b_i) & \\
+     * f_t =& \sigma(W_{xf}x_t+W_{hf}h_{t-1}+W_{cf}C_{t-1}+b_f) & \\
+     * C_t =& clip(f_t \odot C_{t-1} + i_t \odot
+     *        g(W_{xc}x_t+W_{hc}h_{t-1}+b_c),\ t_{cell}) & \\
+     * o_t =& \sigma(W_{xo}x_t+W_{ho}h_{t-1}+W_{co}C_t+b_o) & \\
+     *      & & \\
+     *      & clip(W_{proj}(o_t \odot g(C_t))+b_{proj},\ t_{proj})
+     *      & if\ there\ is\ a\ projection; \\
+     * h_t =& & \\
+     *      & o_t \odot g(C_t) & otherwise. \\
+     * \f}
+     * Where:
+     * * \f$x_t\f$ is the input,
+     * * \f$i_t\f$ is the input gate,
+     * * \f$f_t\f$ is the forget gate,
+     * * \f$C_t\f$ is the cell state,
+     * * \f$o_t\f$ is the output,
+     * * \f$h_t\f$ is the output state,
+     * * \f$\sigma\f$ is the logistic sigmoid function,
+     * * \f$g\f$ is the cell input and cell output activation function, usually
+     *   \f$tahn\f$,
+     * * \f$W_{xi}\f$ is the input-to-input weight matrix,
+     * * \f$W_{hi}\f$ is the recurrent to input weight matrix,
+     * * \f$W_{ci}\f$ is the cell-to-input weight matrix,
+     * * \f$b_i\f$ is the input gate bias,
+     * * \f$W_{xf}\f$ is the input-to-forget weight matrix,
+     * * \f$W_{hf}\f$ is the recurrent-to-forget weight matrix,
+     * * \f$W_{cf}\f$ is the cell-to-forget weight matrix,
+     * * \f$b_f\f$ is the forget gate bias,
+     * * \f$W_{xc}\f$ is the input-to-cell weight matrix,
+     * * \f$W_{hc}\f$ is the recurrent-to-cell weight matrix,
+     * * \f$b_c\f$ is the cell bias,
+     * * \f$W_{xo}\f$ is the input-to-output weight matrix,
+     * * \f$W_{ho}\f$ is the recurrent-to-output weight matrix,
+     * * \f$W_{co}\f$ is the cell-to-output weight matrix,
+     * * \f$b_o\f$ is the output gate bias,
+     * * \f$W_{proj}\f$ is the projection weight matrix,
+     * * \f$b_{proj}\f$ is the projection bias,
+     * * \f$t_{cell}\f$ is the threshold for clipping the cell state, and
+     * * \f$t_{proj}\f$ is the threshold for clipping the projected output.
+     * * \f$\odot\f$ is the
+     *   <a href="https://en.wikipedia.org/wiki/Hadamard_product_(matrices)">
+     *   Hadamard product</a> that takes two matrices and produces another
+     *   matrix, each element of which is the product of the corresponding
+     *   elements of the input matrices.
+     *
+     * Since HAL version 1.2 LSTM supports layer normalization.
+     * In case layer normalization is used, the inputs to internal activation
+     * functions (sigmoid and \f$g\f$) are normalized, rescaled and recentered
+     * following an approach from section 3.1 from
+     * https://arxiv.org/pdf/1607.06450.pdf
+     *
+     * The operation has the following independently optional inputs:
+     * * The cell-to-input weights (\f$W_{ci}\f$), cell-to-forget weights
+     *   (\f$W_{cf}\f$) and cell-to-output weights (\f$W_{co}\f$) either all
+     *   have values or neither of them have values (i.e., all set to null). If
+     *   they have values, the peephole optimization is used.
+     * * The input-to-input weights (\f$W_{xi}\f$), recurrent-to-input weights
+     *   (\f$W_{hi}\f$) and input gate bias (\f$b_i\f$) either all have values,
+     *   or none of them have values. If they have no values, coupling of input
+     *   and forget gates (CIFG) is used, in which case the input gate
+     *   (\f$i_t\f$) is calculated using the following equation instead.
+     *   \f{eqnarray*}{
+     *   i_t = 1 - f_t
+     *   \f}
+     *   In case peephole optimization is used and CIFG is not used
+     *   cell-to-input (\f$W_{ci}\f$) weights must be present. Otherwise, the
+     *   cell-to-input weights must have no value.
+     * * The projection weights (\f$W_{proj}\f$) is required only for the
+     *   recurrent projection layer, and should otherwise have no value.
+     * * The projection bias (\f$b_{proj}\f$) may (but not required to) have a
+     *   value if the recurrent projection layer exists, and should otherwise
+     *   have no value.
+     * * (HAL version 1.2 or later) The four layer normalization weights either all have
+     *   values or none of them have values. Additionally, if CIFG is used,
+     *   input layer normalization weights tensor is omitted and the other layer
+     *   normalization weights either all have values or none of them have
+     *   values. Layer normalization is used when the values of all the layer
+     *   normalization weights are present.
+     *
+     * References:
+     *
+     * The default non-peephole non-CIFG implementation is based on:
+     * http://www.bioinf.jku.at/publications/older/2604.pdf
+     * S. Hochreiter and J. Schmidhuber. "Long Short-Term Memory". Neural
+     * Computation, 9(8):1735-1780, 1997.
+     *
+     * The peephole implementation and projection layer is based on:
+     * https://research.google.com/pubs/archive/43905.pdf
+     * Hasim Sak, Andrew Senior, and Francoise Beaufays. "Long short-term memory
+     * recurrent neural network architectures for large scale acoustic
+     * modeling." INTERSPEECH, 2014.
+     * (However, the concept of peephole optimization was introduced in work
+     * prior to this paper.)
+     *
+     * The coupling of input and forget gate (CIFG) is based on:
+     * http://arxiv.org/pdf/1503.04069.pdf
+     * Greff et al. "LSTM: A Search Space Odyssey"
+     *
+     * The layer normalization is based on:
+     * https://arxiv.org/pdf/1607.06450.pdf
+     * Jimmy Ba et al. "Layer Normalization"
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * All input and output tensors must be of the same type.
+     *
+     * Inputs:
+     * * 0: The input (\f$x_t\f$).
+     *      A 2-D tensor of shape [batch_size, input_size], where “batch_size”
+     *      corresponds to the batching dimension, and “input_size” is the size
+     *      of the input.
+     * * 1: The input-to-input weights (\f$W_{xi}\f$). Optional.
+     *      A 2-D tensor of shape [num_units, input_size], where “num_units”
+     *      corresponds to the number of cell units.
+     * * 2: The input-to-forget weights (\f$W_{xf}\f$).
+     *      A 2-D tensor of shape [num_units, input_size].
+     * * 3: The input-to-cell weights (\f$W_{xc}\f$).
+     *      A 2-D tensor of shape [num_units, input_size].
+     * * 4: The input-to-output weights (\f$W_{xo}\f$).
+     *      A 2-D tensor of shape [num_units, input_size].
+     * * 5: The recurrent-to-input weights (\f$W_{hi}\f$). Optional.
+     *      A 2-D tensor of shape [num_units, output_size], where “output_size”
+     *      corresponds to either the number of cell units (i.e., “num_units”),
+     *      or the second dimension of the “projection_weights”, if defined.
+     * * 6: The recurrent-to-forget weights (\f$W_{hf}\f$).
+     *      A 2-D tensor of shape [num_units, output_size].
+     * * 7: The recurrent-to-cell weights (\f$W_{hc}\f$).
+     *      A 2-D tensor of shape [num_units, output_size].
+     * * 8: The recurrent-to-output weights (\f$W_{ho}\f$).
+     *      A 2-D tensor of shape [num_units, output_size].
+     * * 9: The cell-to-input weights (\f$W_{ci}\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 10:The cell-to-forget weights (\f$W_{cf}\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 11:The cell-to-output weights (\f$W_{co}\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 12:The input gate bias (\f$b_i\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 13:The forget gate bias (\f$b_f\f$).
+     *      A 1-D tensor of shape [num_units].
+     * * 14:The cell bias (\f$b_c\f$).
+     *      A 1-D tensor of shape [num_units].
+     * * 15:The output gate bias (\f$b_o\f$).
+     *      A 1-D tensor of shape [num_units].
+     * * 16:The projection weights (\f$W_{proj}\f$). Optional.
+     *      A 2-D tensor of shape [output_size, num_units].
+     * * 17:The projection bias (\f$b_{proj}\f$). Optional.
+     *      A 1-D tensor of shape [output_size].
+     * * 18:The output state (in) (\f$h_{t-1}\f$).
+     *      A 2-D tensor of shape [batch_size, output_size].
+     * * 19:The cell state (in) (\f$C_{t-1}\f$).
+     *      A 2-D tensor of shape [batch_size, num_units].
+     * * 20:The activation function (\f$g\f$).
+     *      A value indicating the activation function:
+     *      <ul>
+     *      <li>0: None;
+     *      <li>1: Relu;
+     *      <li>3: Relu6;
+     *      <li>4: Tanh;
+     *      <li>6: Sigmoid.
+     *      </ul>
+     * * 21:The clipping threshold (\f$t_{cell}\f$) for the cell state, such
+     *      that values are bound within [-cell_clip, cell_clip]. If set to 0.0
+     *      then clipping is disabled.
+     *      Until HAL version 1.2 this scalar must be of type {@link
+     *      OperandType::FLOAT32}. Since HAL version 1.2, if all the input
+     *      tensors have type {@link OperandType::TENSOR_FLOAT32}, this
+     *      scalar must be of the type {@link OperandType::FLOAT32},
+     *      otherwise if all the input tensors have the type {@link
+     *      OperandType::TENSOR_FLOAT16}, this scalar must be of type {@link
+     *      OperandType::FLOAT16}.
+     * * 22:The clipping threshold (\f$t_{proj}\f$) for the output from the
+     *      projection layer, such that values are bound within
+     *      [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     *      Until HAL version 1.2 this scalar must be of type {@link
+     *      OperandType::FLOAT32}. Since HAL version 1.2, if all the input
+     *      tensors have type {@link OperandType::TENSOR_FLOAT32}, this
+     *      scalar must be of the type {@link OperandType::FLOAT32},
+     *      otherwise if all the input tensors have the type {@link
+     *      OperandType::TENSOR_FLOAT16}, this scalar must be of type {@link
+     *      OperandType::FLOAT16}.
+     * Since HAL version 1.2 there are additional inputs to this op:
+     * * 23:The input layer normalization weights.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at input gate.
+     * * 24:The forget layer normalization weights.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at forget gate.
+     * * 25:The cell layer normalization weights.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at cell gate.
+     * * 26:The output layer normalization weights.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at output gate.
+     *
+     * Outputs:
+     * * 0: The scratch buffer.
+     *      A 2-D tensor of shape [batch_size, num_units * 3] with CIFG, or
+     *      [batch_size, num_units * 4] without CIFG.
+     * * 1: The output state (out) (\f$h_t\f$).
+     *      A 2-D tensor of shape [batch_size, output_size].
+     * * 2: The cell state (out) (\f$C_t\f$).
+     *      A 2-D tensor of shape [batch_size, num_units].
+     * * 3: The output (\f$o_t\f$).
+     *      A 2-D tensor of shape [batch_size, output_size]. This is effectively
+     *      the same as the current “output state (out)” value.
+     */
+    LSTM = 16,
+    /**
+     * Performs an 2-D max pooling operation.
+     *
+     * The output dimensions are functions of the filter dimensions, stride, and
+     * padding.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[b, i, j, channel] =
+     *         max_{di, dj} (
+     *             input[b, strides[1] * i + di, strides[2] * j + dj, channel]
+     *         )
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Both explicit padding and implicit padding are supported.
+     *
+     * Inputs (explicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the left, in the ‘width’ dimension.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the right, in the ‘width’ dimension.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the top, in the ‘height’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the bottom, in the ‘height’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the filter
+     *      width.
+     * * 8: An {@link OperandType::INT32} scalar, specifying the filter
+     *      height.
+     * * 9: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 10: An optional {@link OperandType::BOOL} scalar, default to false.
+     *       Set to true to specify NCHW data layout for input0 and output0.
+     *       Available since HAL version 1.2.
+     *
+     * Inputs (implicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the implicit
+     *      padding scheme, has to be one of the
+     *      following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the filter
+     *      width.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the filter
+     *      height.
+     * * 6: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 7: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, out_height, out_width, depth].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    MAX_POOL_2D = 17,
+    /**
+     * Multiplies two tensors, element-wise.
+     *
+     * Takes two input tensors of identical {@link OperandType} and compatible
+     * dimensions. The output is the product of both input tensors, optionally
+     * modified by an activation function.
+     *
+     * Two dimensions are compatible when:
+     *     1. they are equal, or
+     *     2. one of them is 1
+     *
+     * The size of the resulting output is the maximum size along each dimension
+     * of the input operands. It starts with the trailing dimensions, and works
+     * its way forward.
+     *
+     * Since HAL version 1.2, generic zero-sized input tensor is supported. Zero
+     * dimension is only compatible with 0 or 1. The size of the output
+     * dimension is zero if either of corresponding input dimension is zero.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     * * {@link OperandType::TENSOR_INT32} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType}, and compatible dimensions
+     *      as input0.
+     * * 2: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     *      For a {@link OperandType::TENSOR_INT32} tensor,
+     *      the {@link FusedActivationFunc} must be "NONE".
+     *
+     * Outputs:
+     * * 0: The product, a tensor of the same {@link OperandType} as input0.
+     *      For output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the following condition must be satisfied:
+     *      output_scale > input1_scale * input2_scale.
+     */
+    MUL = 18,
+    /**
+     * Computes rectified linear activation on the input tensor element-wise.
+     *
+     * The output is calculated using this formula:
+     *
+     *     output = max(0, input)
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    RELU = 19,
+    /**
+     * Computes rectified linear 1 activation on the input tensor element-wise.
+     *
+     * The output is calculated using this formula:
+     *
+     *     output = min(1.f, max(-1.f, input))
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of the same shape as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    RELU1 = 20,
+    /**
+     * Computes rectified linear 6 activation on the input tensor element-wise.
+     *
+     * The output is calculated using this formula:
+     *
+     *     output = min(6, max(0, input))
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    RELU6 = 21,
+    /**
+     * Reshapes a tensor.
+     *
+     * Given tensor, this operation returns a tensor that has the same values as
+     * tensor, but with a newly specified shape.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the tensor to be reshaped.
+     * * 1: A 1-D tensor of {@link OperandType::TENSOR_INT32}, defining the
+     *      shape of the output tensor. The number of elements implied by shape
+     *      must be the same as the number of elements in the input tensor.
+     *
+     *      If one component of shape is the special value -1, the size of that
+     *      dimension is computed so that the total size remains constant. In
+     *      particular, a shape of [-1] flattens into 1-D. At most one component
+     *      of shape can be -1.
+     *
+     * Outputs:
+     * * 0: The output tensor, of shape specified by the input shape.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    RESHAPE = 22,
+    /**
+     * Resizes images to given size using the bilinear interpretation.
+     *
+     * Resized images must be distorted if their output aspect ratio is not the
+     * same as input aspect ratio. The corner pixels of output may not be the
+     * same as corner pixels of input.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Both resizing by shape and resizing by scale are supported.
+     *
+     * Inputs (resizing by shape):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input.
+     *      Since HAL version 1.2, zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the output
+     *      width of the output tensor.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the output
+     *      height of the output tensor.
+     * * 3: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     * * 4: Align corners. An optional {@link OperandType::BOOL}
+     *      scalar, default to false.  If True, the centers of the 4 corner
+     *      pixels of the input and output tensors are aligned, preserving the
+     *      values at the corner pixels.
+     *      Available since HAL version 1.3.
+     * * 5: Half pixel centers. An optional {@link OperandType::BOOL}
+     *      scalar, default to false. If True, the pixel centers are assumed to
+     *      be at (0.5, 0.5). This is the default behavior of image.resize in
+     *      TF 2.0. If this parameter is True, then align_corners parameter
+     *      must be False.
+     *      Available since HAL version 1.3.
+     *
+     * Inputs (resizing by scale, since HAL version 1.2):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input. Zero batches is supported for this tensor.
+     * * 1: A scalar, specifying width_scale, the scaling factor of the width
+     *      dimension from the input tensor to the output tensor. The output
+     *      width is calculated as new_width = floor(width * width_scale).
+     *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
+     *      of {@link OperandType::TENSOR_FLOAT16} and of
+     *      {@link OperandType::FLOAT32} otherwise.
+     * * 2: A scalar, specifying height_scale, the scaling factor of the height
+     *      dimension from the input tensor to the output tensor. The output
+     *      height is calculated as new_height = floor(height * height_scale).
+     *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
+     *      of {@link OperandType::TENSOR_FLOAT16} and of
+     *      {@link OperandType::FLOAT32} otherwise.
+     * * 3: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     * * 4: Align corners. An optional {@link OperandType::BOOL}
+     *      scalar, default to false.  If True, the centers of the 4 corner
+     *      pixels of the input and output tensors are aligned, preserving the
+     *      values at the corner pixels.
+     *      Available since HAL version 1.3.
+     * * 5: Half pixel centers. An optional {@link OperandType::BOOL}
+     *      scalar, default to false. If True, the pixel centers are assumed to
+     *      be at (0.5, 0.5). This is the default behavior of image.resize in
+     *      TF 2.0. If this parameter is True, then align_corners parameter
+     *      must be False.
+     *      Available since HAL version 1.3.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, new_height, new_width, depth].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    RESIZE_BILINEAR = 23,
+    /**
+     * A basic recurrent neural network layer.
+     *
+     * This layer implements the operation:
+     * outputs = state = activation(inputs * input_weights +
+     *                              state * recurrent_weights + bias)
+     *
+     * Where:
+     * * “input_weights” is a weight matrix that multiplies the inputs;
+     * * “recurrent_weights” is a weight matrix that multiplies the current
+     *    “state” which itself is the output from the previous time step
+     *    computation;
+     * * “bias” is a bias vector (added to each output vector in the batch);
+     * * “activation” is the function passed as the “fused_activation_function”
+     *   argument (if not “NONE”).
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * The input tensors must all be the same type.
+     *
+     * Inputs:
+     * * 0: input.
+     *      A 2-D tensor of shape [batch_size, input_size], where “batch_size”
+     *      corresponds to the batching dimension, and “input_size” is the size
+     *      of the input.
+     * * 1: weights.
+     *      A 2-D tensor of shape [num_units, input_size], where “num_units”
+     *      corresponds to the number of units.
+     * * 2: recurrent_weights.
+     *      A 2-D tensor of shape [num_units, num_units], with columns
+     *      corresponding to the weights from each unit.
+     * * 3: bias.
+     *      A 1-D tensor of shape [num_units].
+     * * 4: hidden state (in).
+     *      A 2-D tensor of shape [batch_size, num_units].
+     * * 5: fused_activation_function.
+     *      An optional {@link FusedActivationFunc} value indicating the
+     *      activation function. If “NONE” is specified then it results in a
+     *      linear activation.
+     *
+     * Outputs:
+     * * 0: hidden state (out).
+     *      A 2-D tensor of shape [batch_size, num_units].
+     *
+     * * 1: output.
+     *      A 2-D tensor of shape [batch_size, num_units]. This is effectively
+     *      the same as the current state value.
+     */
+    RNN = 24,
+    /**
+     * Computes the softmax activation on the input tensor element-wise, per
+     * batch, by normalizing the input vector so the maximum coefficient is
+     * zero.
+     *
+     * The output is calculated using this formula:
+     *
+     *     output[batch, i] =
+     *         exp((input[batch, i] - max(input[batch, :])) * beta) /
+     *         sum_{k}{exp((input[batch, k] - max(input[batch, :])) * beta)}
+     *
+     * For input tensor with rank other than 2, the activation will be applied
+     * independently on each 1-D slice along specified dimension.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     * Tensors with rank other than 2 or 4 are only supported since HAL version 1.2.
+     *
+     * Inputs:
+     * * 0: A 2-D or 4-D tensor, specifying the tensor to be reshaped.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     * * 1: A scalar, specifying the positive scaling factor for the exponent,
+     *      beta. If input0 is of {@link OperandType::TENSOR_FLOAT32},
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} or
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}, the scalar
+     *      must be of {@link OperandType::FLOAT32}.
+     *      If input0 is of {@link OperandType::TENSOR_FLOAT16}, then the
+     *      scalar must be of {@link OperandType::FLOAT16}.
+     * * 2: An optional {@link OperandType::INT32} scalar, default to -1,
+     *      specifying the dimension the activation would be performed on.
+     *      Negative index is used to specify axis from the end (e.g. -1 for
+     *      the last axis). Must be in the range [-n, n).
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      the scale must be 1.f / 256 and the zeroPoint must be 0.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the scale must be 1.f / 256 and the zeroPoint must be -128.
+     */
+    SOFTMAX = 25,
+    /**
+     * Rearranges blocks of spatial data, into depth.
+     *
+     * More specifically, this op outputs a copy of the input tensor where
+     * values from the height and width dimensions are moved to the depth
+     * dimension. The value block_size indicates the input block size and how
+     * the data is moved.
+     *
+     * Chunks of data of size block_size * block_size from depth are rearranged
+     * into non-overlapping blocks of size block_size x block_size.
+     *
+     * The depth of the output tensor is input_depth * block_size * block_size.
+     * The input tensor's height and width must be divisible by block_size.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Inputs:
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the block_size.
+     *      block_size must be >=1 and block_size must be a divisor of both the
+     *      input height and width.
+     * * 2: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape [batches, height/block_size,
+     *      width/block_size, depth_in*block_size*block_size].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    SPACE_TO_DEPTH = 26,
+    /**
+     * SVDF op is a kind of stateful layer derived from the notion that a
+     * densely connected layer that's processing a sequence of input frames can
+     * be approximated by using a singular value decomposition of each of its
+     * nodes. The implementation is based on:
+     *
+     * https://research.google.com/pubs/archive/43813.pdf
+     *
+     * P. Nakkiran, R. Alvarez, R. Prabhavalkar, C. Parada.
+     * “Compressing Deep Neural Networks using a Rank-Constrained Topology”.
+     * INTERSPEECH, 2015.
+     *
+     * It processes the incoming input using a 2-stage filtering mechanism:
+     * * stage 1 performs filtering on the "features" dimension, whose outputs
+     *   get pushed into a memory of fixed-size memory_size.
+     * * stage 2 performs filtering on the "time" dimension of the memory_size
+     *   memoized outputs of stage 1.
+     *
+     * Specifically, for rank 1, this layer implements the operation:
+     *
+     *     memory = push(conv1d(inputs, weights_feature, feature_dim,
+     *                          "PADDING_VALID"));
+     *     outputs = activation(memory * weights_time + bias);
+     *
+     * Where:
+     * * “weights_feature” is a weights matrix that processes the inputs (by
+     *   convolving the input with every “feature filter”), and whose outputs
+     *   get pushed, stacked in order, into the fixed-size “memory” (the oldest
+     *   entry gets dropped);
+     * * “weights_time” is a weights matrix that processes the “memory” (by a
+     *   batched matrix multiplication on the num_units);
+     * * “bias” is an optional bias vector (added to each output vector in the
+     *   batch); and
+     * * “activation” is the function passed as the “fused_activation_function”
+     *   argument (if not “NONE”).
+     *
+     * Each rank adds a dimension to the weights matrices by means of stacking
+     * the filters.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * All input tensors must be the same type.
+     *
+     * Inputs:
+     * * 0: input.
+     *      A 2-D tensor of shape [batch_size, input_size], where “batch_size”
+     *      corresponds to the batching dimension, and “input_size” is the size
+     *      of the input.
+     * * 1: weights_feature.
+     *      A 2-D tensor of shape [num_units, input_size], where “num_units”
+     *      corresponds to the number of units.
+     * * 2: weights_time.
+     *      A 2-D tensor of shape [num_units, memory_size], where “memory_size”
+     *      corresponds to the fixed-size of the memory.
+     * * 3: bias.
+     *      An optional 1-D tensor of shape [num_units].
+     * * 4: state (in).
+     *      A 2-D tensor of shape [batch_size, (memory_size - 1) * num_units * rank].
+     * * 5: rank.
+     *      The rank of the SVD approximation.
+     * * 6: fused_activation_function.
+     *      An optional {@link FusedActivationFunc} value indicating the
+     *      activation function. If “NONE” is specified then it results in a
+     *      linear activation.
+     *
+     * Outputs:
+     * * 0: state (out).
+     *      A 2-D tensor of the same {@link OperandType} as the inputs, with shape
+     *      [batch_size, (memory_size - 1) * num_units * rank].
+     * * 1: output.
+     *      A 2-D tensor of the same {@link OperandType} as the inputs, with shape
+     *      [batch_size, num_units].
+     */
+    SVDF = 27,
+    /**
+     * Computes hyperbolic tangent of input tensor element-wise.
+     *
+     * The output is calculated using this formula:
+     *
+     *     output = tanh(input)
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      the scale must be 1.f / 128 and the zeroPoint must be 128.
+     *      For {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the scale must be 1.f / 128 and the zeroPoint must be 0.
+     */
+    TANH = 28,
+    /**
+     * BatchToSpace for N-dimensional tensors.
+     *
+     * This operation reshapes the batch dimension (dimension 0) into M + 1
+     * dimensions of shape block_shape + [batch], interleaves these blocks back
+     * into the grid defined by the spatial dimensions [1, ..., M], to obtain a
+     * result with the same rank as the input.
+     *
+     * This is the reverse of SpaceToBatch.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be reshaped
+     * * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}, the block
+     *      sizes for each spatial dimension of the input tensor. All values
+     *      must be >= 1.
+     * * 2: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since API level 29.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    BATCH_TO_SPACE_ND = 29,
+    /**
+     * Element-wise division of two tensors.
+     *
+     * Takes two input tensors of identical {@link OperandType} and compatible
+     * dimensions. The output is the result of dividing the first input tensor
+     * by the second, optionally modified by an activation function.
+     *
+     * For inputs of {@link OperandType::TENSOR_INT32}, performs
+     * "floor division" ("//" in Python). For example,
+     *     5 // 2 = 2
+     *    -5 // 2 = -3
+     *
+     * Two dimensions are compatible when:
+     *     1. they are equal, or
+     *     2. one of them is 1
+     *
+     * The size of the output is the maximum size along each dimension of the
+     * input operands. It starts with the trailing dimensions, and works its way
+     * forward.
+     *
+     * Example:
+     *     input1.dimension =    {4, 1, 2}
+     *     input2.dimension = {5, 4, 3, 1}
+     *     output.dimension = {5, 4, 3, 2}
+     *
+     * Since HAL version 1.2, generic zero-sized input tensor is supported. Zero
+     * dimension is only compatible with 0 or 1. The size of the output
+     * dimension is zero if either of corresponding input dimension is zero.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the first input.
+     * * 1: A tensor of the same {@link OperandType}, and compatible dimensions
+     *      as input0.
+     * * 2: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     *      For a {@link OperandType::TENSOR_INT32} tensor,
+     *      the {@link FusedActivationFunc} must be "NONE".
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     */
+    DIV = 30,
+    /**
+     * Computes the mean of elements across dimensions of a tensor.
+     *
+     * Reduces the input tensor along the given dimensions to reduce. Unless
+     * keep_dims is true, the rank of the tensor is reduced by 1 for each entry
+     * in axis. If keep_dims is true, the reduced dimensions are retained with
+     * length 1.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input.
+     * * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}. The dimensions
+     *      to reduce. Must be in the range
+     *      [-rank(input_tensor), rank(input_tensor)).
+     *
+     *      NOTE: When the operation was introduced, the documentation
+     *      incorrectly stated that if dimensions were empty, the operation
+     *      would reduce across all dimensions. This behavior was never
+     *      implemented.
+     *
+     * * 2: An {@link OperandType::INT32} scalar, keep_dims. If positive,
+     *      retains reduced dimensions with length 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     *      If all dimensions are reduced and keep_dims is false, the output
+     *      shape is [1].
+     */
+    MEAN = 31,
+    /**
+     * Pads a tensor.
+     *
+     * This operation pads a tensor according to the specified paddings.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *   (full support since HAL version 1.2, see the output section)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be padded.
+     * * 1: A 2-D Tensor of {@link OperandType::TENSOR_INT32}, the paddings
+     *      for each spatial dimension of the input tensor. The shape of the
+     *      tensor must be {rank(input0), 2}.
+     *      padding[i, 0] specifies the number of elements to be padded in the
+     *      front of dimension i.
+     *      padding[i, 1] specifies the number of elements to be padded after the
+     *      end of dimension i.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0. The
+     *      output tensor has the same rank as input0, and each
+     *      dimension of the output tensor has the same size as the
+     *      corresponding dimension of the input tensor plus the size
+     *      of the padding:
+     *          output0.dimension[i] =
+     *              padding[i, 0] + input0.dimension[i] + padding[i, 1]
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     *
+     *      NOTE: Before HAL version 1.2, the pad value for
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} is undefined.
+     *      Since HAL version 1.2, the pad value is always the logical zero.
+     */
+    PAD = 32,
+    /**
+     * SpaceToBatch for N-Dimensional tensors.
+     *
+     * This operation divides "spatial" dimensions [1, ..., M] of the input into
+     * a grid of blocks of shape block_shape, and interleaves these blocks with
+     * the "batch" dimension (0) such that in the output, the spatial dimensions
+     * [1, ..., M] correspond to the position within the grid, and the batch
+     * dimension combines both the position within a spatial block and the
+     * original batch position. Prior to division into blocks, the spatial
+     * dimensions of the input are optionally zero padded according to paddings.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *   (full support since HAL version 1.2, see the output section)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     * NCHW is supported since HAL version 1.2.
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the input.
+     * * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}, the block
+     *      sizes for each spatial dimension of the input tensor. All values
+     *      must be >= 1.
+     * * 2: A 2-D Tensor of {@link OperandType::TENSOR_INT32}, the paddings
+     *      for each spatial dimension of the input tensor. All values must be
+     *      >= 0. The shape of the tensor must be {M, 2}, where M is the number
+     *      of spatial dimensions.
+     *      padding[i, 0] specifies the number of element to be padded in the
+     *      front of dimension i.
+     *      padding[i, 1] specifies the number of element to be padded after the
+     *      end of dimension i.
+     * * 3: An optional {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     *      Available since HAL version 1.2.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     *
+     *      NOTE: Before HAL version 1.2, the pad value for
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} is undefined.
+     *      Since HAL version 1.2, the pad value is always the logical zero.
+     */
+    SPACE_TO_BATCH_ND = 33,
+    /**
+     * Removes dimensions of size 1 from the shape of a tensor.
+     *
+     * Given a tensor input, this operation returns a tensor of the same
+     * {@link OperandType} with all dimensions of size 1 removed. If you don't
+     * want to remove all size 1 dimensions, you can remove specific size 1
+     * dimensions by specifying the axes (input1).
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, the tensor to be squeezed.
+     * * 1: An optional 1-D tensor of {@link OperandType::TENSOR_INT32}. The
+     *      dimensions to squeeze. If specified only squeezes the dimensions
+     *      listed. Otherwise, squeezes all dimensions. The dimension index
+     *      starts at 0. An error must be reported if squeezing a dimension that
+     *      is not 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0. Contains the
+     *      same data as input, but has one or more dimensions of size 1
+     *      removed.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     *      If all input dimensions are equal to 1 and are to be squeezed, the
+     *      output shape is [1].
+     */
+    SQUEEZE = 34,
+    /**
+     * Extracts a strided slice of a tensor.
+     *
+     * Roughly speaking, this op extracts a slice of size (end - begin) / stride
+     * from the given input tensor. Starting at the location specified by begin
+     * the slice continues by adding stride to the index until all dimensions
+     * are not less than end. Note that a stride can be negative, which causes a
+     * reverse slice.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be sliced.
+     * * 1: begin, a 1-D tensor of {@link OperandType::TENSOR_INT32}. The
+     *      starts of the dimensions of the input tensor to be sliced. The
+     *      length must be of rank(input0).
+     * * 2: end, a 1-D tensor of {@link OperandType::TENSOR_INT32}. The
+     *      ends of the dimensions of the input tensor to be sliced. The length
+     *      must be of rank(input0).
+     * * 3: strides, a 1-D tensor of {@link OperandType::TENSOR_INT32}. The
+     *      strides of the dimensions of the input tensor to be sliced. The
+     *      length must be of rank(input0). The entries must be non-zero.
+     * * 4: begin_mask, an {@link OperandType::INT32} scalar. If the ith bit
+     *      of begin_mask is set, begin[i] is ignored and the fullest possible
+     *      range in that dimension is used instead.
+     * * 5: end_mask, an {@link OperandType::INT32} scalar. If the ith bit of
+     *      end_mask is set, end[i] is ignored and the fullest possible range in
+     *      that dimension is used instead.
+     * * 6: shrink_axis_mask, an {@link OperandType::INT32} scalar. If the
+     *      ith bit of shrink_axis_mask is set, the ith dimension specification
+     *      shrinks the dimensionality by 1, taking on the value at index
+     *      begin[i]. In this case, the ith specification must define a
+     *      slice of size 1, e.g. begin[i] = x, end[i] = x + 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0 and rank (n - k),
+     *      where k is the number of bits set in shrink_axis_mask.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     *      If shrink_axis_mask is true for all input dimensions, the output
+     *      shape is [1].
+     */
+    STRIDED_SLICE = 35,
+    /**
+     * Element-wise subtraction of two tensors.
+     *
+     * Takes two input tensors of identical {@link OperandType} and compatible
+     * dimensions. The output is the result of subtracting the second input
+     * tensor from the first one, optionally modified by an activation function.
+     *
+     * Two dimensions are compatible when:
+     *     1. they are equal, or
+     *     2. one of them is 1
+     *
+     * The size of the output is the maximum size along each dimension of the
+     * input operands. It starts with the trailing dimensions, and works its way
+     * forward.
+     *
+     * Example:
+     *     input1.dimension =    {4, 1, 2}
+     *     input2.dimension = {5, 4, 3, 1}
+     *     output.dimension = {5, 4, 3, 2}
+     *
+     * Since HAL version 1.2, generic zero-sized input tensor is supported. Zero
+     * dimension is only compatible with 0 or 1. The size of the output
+     * dimension is zero if either of corresponding input dimension is zero.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     * * {@link OperandType::TENSOR_INT32} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the first input.
+     * * 1: A tensor of the same {@link OperandType}, and compatible dimensions
+     *      as input0.
+     * * 2: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     *      For a {@link OperandType::TENSOR_INT32} tensor,
+     *      the {@link FusedActivationFunc} must be "NONE".
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.
+     */
+    SUB = 36,
+    /**
+     * Transposes the input tensor, permuting the dimensions according to the
+     * perm tensor.
+     *
+     * The returned tensor's dimension i corresponds to the input dimension
+     * perm[i]. If perm is not given, it is set to (n-1...0), where n is the
+     * rank of the input tensor. Hence by default, this operation performs a
+     * regular matrix transpose on 2-D input Tensors.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16} (since HAL version 1.2)
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be transposed.
+     *      Since HAL version 1.2, this tensor may be zero-sized.
+     * * 1: An optional 1-D Tensor of {@link OperandType::TENSOR_INT32},
+     *      the permutation of the dimensions of the input tensor.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    TRANSPOSE = 37,
+    /**
+     * Computes the absolute value of a tensor, element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    ABS = 38,
+    /**
+     * Returns the index of the largest element along an axis.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: An n-D tensor specifying the input. Must be non-empty.
+     * * 1: An {@link OperandType::INT32} scalar specifying the axis to
+     *      reduce across. Negative index is used to specify axis from the
+     *      end (e.g. -1 for the last axis). Must be in the range [-n, n).
+     *
+     * Outputs:
+     * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor.
+     *      If input is 1-dimensional, the output shape is [1].
+     */
+    ARGMAX = 39,
+    /**
+     * Returns the index of the smallest element along an axis.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: An n-D tensor specifying the input. Must be non-empty.
+     * * 1: An {@link OperandType::INT32} scalar specifying the axis to
+     *      reduce across. Negative index is used to specify axis from the
+     *      end (e.g. -1 for the last axis). Must be in the range [-n, n).
+     *
+     * Outputs:
+     * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor.
+     *      If input is 1-dimensional, the output shape is [1].
+     */
+    ARGMIN = 40,
+    /**
+     * Transform axis-aligned bounding box proposals using bounding box deltas.
+     *
+     * Given the positions of bounding box proposals and the corresponding
+     * bounding box deltas for each class, return the refined bounding box
+     * regions. The resulting bounding boxes are cliped against the edges of
+     * the image.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT16_ASYMM}
+     *
+     * Inputs:
+     * * 0: A 2-D Tensor of shape [num_rois, 4], specifying the locations of the
+     *      bounding box proposals, each line with format [x1, y1, x2, y2].
+     *      For tensor of type {@link OperandType::TENSOR_QUANT16_ASYMM},
+     *      the zeroPoint must be 0 and the scale must be 0.125. Zero num_rois
+     *      is supported for this tensor.
+     * * 1: A 2-D Tensor of shape [num_rois, num_classes * 4], specifying the
+     *      bounding box delta for each region of interest and each class. The
+     *      bounding box deltas are organized in the following order
+     *      [dx, dy, dw, dh], where dx and dy is the relative correction factor
+     *      for the center position of the bounding box with respect to the width
+     *      and height, dw and dh is the log-scale relative correction factor
+     *      for the width and height. For input0 of type
+     *      {@link OperandType::TENSOR_QUANT16_ASYMM}, this tensor should be
+     *      of {@link OperandType::TENSOR_QUANT8_ASYMM} or
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}. Zero num_rois is
+     *      supported for this tensor.
+     * * 2: An 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [num_rois], specifying the batch index of each box. Boxes with
+     *      the same batch index are grouped together. Zero num_rois is
+     *      supported for this tensor.
+     * * 3: A 2-D Tensor of shape [batches, 2], specifying the information of
+     *      each image in the batch, each line with format
+     *      [image_height, image_width].
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0, with shape
+     *      [num_rois, num_classes * 4], specifying the coordinates of each
+     *      output bounding box for each class, with format [x1, y1, x2, y2].
+     *      For type of {@link OperandType::TENSOR_QUANT16_ASYMM}, the
+     *      scale must be 0.125 and the zero point must be 0.
+     */
+    AXIS_ALIGNED_BBOX_TRANSFORM = 41,
+    /**
+     * A recurrent neural network layer that applies an LSTM cell to a
+     * sequence of inputs in forward and backward directions.
+     *
+     * The op supports cross-linking via an auxiliary input. Regular cell feeds
+     * one input into the two RNN cells in the following way:
+     *
+     *       INPUT  (INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_LSTM   BW_LSTM |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
+     * An op with cross-linking takes two inputs and feeds them into the RNN
+     * cells in the following way:
+     *
+     *       AUX_INPUT   (AUX_INPUT_REVERSED)
+     *           |             |
+     *     INPUT | (INPUT_R'D.)|
+     *       |   |       |     |
+     *    -----------------------
+     *    |  \  /        \    / |
+     *    | FW_LSTM     BW_LSTM |
+     *    -----------------------
+     *         |           |
+     *      FW_OUT      BW_OUT
+     *
+     * The cross-linking mode is enabled iff auxiliary input and auxiliary
+     * weights are present. While stacking this op on top of itself, this
+     * allows to connect both forward and backward outputs from previous cell
+     * to the next cell's input.
+     *
+     * Since HAL version 1.3 parallel linking mode is supported. The mode is
+     * enabled if auxiliary input is present but auxiliary weights are omitted.
+     * In this case, the cell feeds inputs into the RNN in the following way:
+     *
+     *       INPUT (AUX_INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_LSTM   BW_LSTM |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
+     * While stacking this op on top of itself, this allows to connect both
+     * forward and backward outputs from previous cell to the next cell's
+     * corresponding inputs.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: 3, either time-major or batch-major.
+     *
+     * All input and output tensors must be of the same type.
+     *
+     * Inputs:
+     * * 0: The input.
+     *      A 3-D tensor of shape:
+     *        If time-major: [max_time, batch_size, input_size]
+     *        If batch-major: [batch_size, max_time, input_size]
+     *      where "max_time" is the number of timesteps (sequence length),
+     *      "batch_size" corresponds to the batching dimension, and
+     *      "input_size" is the size of the input.
+     * * 1: The forward input-to-input weights. Optional.
+     *      A 2-D tensor of shape [fw_num_units, input_size], where “fw_num_units”
+     *      corresponds to the number of forward cell units.
+     * * 2: The forward input-to-forget weights.
+     *      A 2-D tensor of shape [fw_num_units, input_size].
+     * * 3: The forward input-to-cell weights.
+     *      A 2-D tensor of shape [fw_num_units, input_size].
+     * * 4: The forward input-to-output weights.
+     *      A 2-D tensor of shape [fw_num_units, input_size].
+     * * 5: The forward recurrent-to-input weights. Optional.
+     *      A 2-D tensor of shape [fw_num_units, fw_output_size], where “fw_output_size”
+     *      corresponds to either the number of cell units (i.e., fw_num_units),
+     *      or the second dimension of the “fw_projection_weights”, if defined.
+     * * 6: The forward recurrent-to-forget weights.
+     *      A 2-D tensor of shape [fw_num_units, fw_output_size].
+     * * 7: The forward recurrent-to-cell weights.
+     *      A 2-D tensor of shape [fw_num_units, fw_output_size].
+     * * 8: The forward recurrent-to-output weights.
+     *      A 2-D tensor of shape [fw_num_units, fw_output_size].
+     * * 9: The forward cell-to-input weights. Optional.
+     *      A 1-D tensor of shape [fw_num_units].
+     * * 10: The forward cell-to-forget weights. Optional.
+     *       A 1-D tensor of shape [fw_num_units].
+     * * 11: The forward cell-to-output weights. Optional.
+     *       A 1-D tensor of shape [fw_num_units].
+     * * 12: The forward input gate bias. Optional.
+     *       A 1-D tensor of shape [fw_num_units].
+     * * 13: The forward forget gate bias.
+     *       A 1-D tensor of shape [fw_num_units].
+     * * 14: The forward cell gate bias.
+     *       A 1-D tensor of shape [fw_num_units].
+     * * 15: The forward output gate bias.
+     *       A 1-D tensor of shape [fw_num_units].
+     * * 16: The forward projection weights. Optional.
+     *       A 2-D tensor of shape [fw_output_size, fw_num_units].
+     * * 17: The forward projection bias. Optional.
+     *       A 1-D tensor of shape [fw_output_size].
+     * * 18: The backward input-to-input weights. Optional.
+     *       A 2-D tensor of shape [bw_num_units, input_size], where “bw_num_units”
+     *       corresponds to the number of backward cell units.
+     * * 19: The backward input-to-forget weights.
+     *       A 2-D tensor of shape [bw_num_units, input_size].
+     * * 20: The backward input-to-cell weights.
+     *       A 2-D tensor of shape [bw_num_units, input_size].
+     * * 21: The backward input-to-output weights.
+     *       A 2-D tensor of shape [bw_num_units, input_size].
+     * * 22: The backward recurrent-to-input weights. Optional.
+     *       A 2-D tensor of shape [bw_num_units, bw_output_size], where “bw_output_size”
+     *       corresponds to either the number of cell units (i.e., “bw_num_units”),
+     *       or the second dimension of the “bw_projection_weights”, if defined.
+     * * 23: The backward recurrent-to-forget weights.
+     *       A 2-D tensor of shape [bw_num_units, bw_output_size].
+     * * 24: The backward recurrent-to-cell weights.
+     *       A 2-D tensor of shape [bw_num_units, bw_output_size].
+     * * 25: The backward recurrent-to-output weights.
+     *       A 2-D tensor of shape [bw_num_units, bw_output_size].
+     * * 26: The backward cell-to-input weights. Optional.
+     *       A 1-D tensor of shape [bw_num_units].
+     * * 27: The backward cell-to-forget weights. Optional.
+     *       A 1-D tensor of shape [bw_num_units].
+     * * 28: The backward cell-to-output weights. Optional.
+     *       A 1-D tensor of shape [bw_num_units].
+     * * 29: The backward input gate bias. Optional.
+     *       A 1-D tensor of shape [bw_num_units].
+     * * 30: The backward forget gate bias.
+     *       A 1-D tensor of shape [bw_num_units].
+     * * 31: The backward cell gate bias.
+     *       A 1-D tensor of shape [bw_num_units].
+     * * 32: The backward output gate bias.
+     *       A 1-D tensor of shape [bw_num_units].
+     * * 33: The backward projection weights. Optional.
+     *       A 2-D tensor of shape [bw_output_size, bw_num_units].
+     * * 34: The backward projection bias. Optional.
+     *       A 1-D tensor of shape [bw_output_size].
+     * * 35: The forward input activation state.
+     *       A 2-D tensor of shape [batch_size, bw_output_size].
+     * * 36: The forward input cell state.
+     *       A 2-D tensor of shape [batch_size, bw_num_units].
+     * * 37: The backward input activation state.
+     *       A 2-D tensor of shape [batch_size, bw_output_size].
+     * * 38: The backward input cell state.
+     *       A 2-D tensor of shape [batch_size, bw_num_units].
+     * * 39: The auxiliary input. Optional.
+     *       A 3-D tensor of shape [max_time, batch_size, aux_input_size],
+     *       where “batch_size” corresponds to the batching dimension, and
+     *       “aux_input_size” is the size of the auxiliary input. Optional. See
+     *       the docs above for the usage modes explanation.
+     * * 40: The forward auxiliary input-to-input weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 41: The forward auxiliary input-to-forget weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 42: The forward auxiliary input-to-cell weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 43: The forward auxiliary input-to-output weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 44: The backward auxiliary input-to-input weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
+     * * 45: The backward auxiliary input-to-forget weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
+     * * 46: The backward auxiliary input-to-cell weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
+     * * 47: The backward auxiliary input-to-output weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
+     * * 48: The activation function.
+     *       A value indicating the activation function:
+     *       <ul>
+     *       <li>0: None;
+     *       <li>1: Relu;
+     *       <li>3: Relu6;
+     *       <li>4: Tanh;
+     *       <li>6: Sigmoid.
+     *       </ul>
+     * * 49: The clipping threshold for the cell state, such
+     *       that values are bound within [-cell_clip, cell_clip]. If set to 0.0
+     *       then clipping is disabled.
+     *       If all the input tensors have type {@link OperandType::TENSOR_FLOAT32},
+     *       this scalar must be of the type {@link OperandType::FLOAT32},
+     *       otherwise if all the input tensors have the type
+     *       {@link OperandType::TENSOR_FLOAT16}, this scalar must be
+     *       of type {@link OperandType::FLOAT16}.
+     * * 50: The clipping threshold for the output from the
+     *       projection layer, such that values are bound within
+     *       [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     *       If all the input tensors have type {@link OperandType::TENSOR_FLOAT32},
+     *       this scalar must be of the type {@link OperandType::FLOAT32},
+     *       otherwise if all the input tensors have the type
+     *       {@link OperandType::TENSOR_FLOAT16}, this scalar must be
+     *       of type {@link OperandType::FLOAT16}.
+     * * 51: merge_outputs
+     *       An {@link OperandType::BOOL} scalar specifying if the outputs
+     *       from forward and backward cells should be merged.
+     * * 52: time_major
+     *       An {@link OperandType::BOOL} scalar specifying the shape format
+     *       of input and output tensors.
+     * * 53: The forward input layer normalization weights. Optional.
+     *       A 1-D tensor of shape [fw_num_units]. Used to rescale normalized inputs
+     *       to activation at input gate.
+     * * 54: The forward forget layer normalization weights. Optional.
+     *       A 1-D tensor of shape [fw_num_units]. Used to rescale normalized inputs
+     *       to activation at forget gate.
+     * * 55: The forward cell layer normalization weights. Optional.
+     *       A 1-D tensor of shape [fw_num_units]. Used to rescale normalized inputs
+     *       to activation at cell gate.
+     * * 56: The forward output layer normalization weights. Optional.
+     *       A 1-D tensor of shape [fw_num_units]. Used to rescale normalized inputs
+     *       to activation at output gate.
+     * * 57: The backward input layer normalization weights. Optional.
+     *       A 1-D tensor of shape [bw_num_units]. Used to rescale normalized inputs
+     *       to activation at input gate.
+     * * 58: The backward forget layer normalization weights. Optional.
+     *       A 1-D tensor of shape [bw_num_units]. Used to rescale normalized inputs
+     *       to activation at forget gate.
+     * * 59: The backward cell layer normalization weights. Optional.
+     *       A 1-D tensor of shape [bw_num_units]. Used to rescale normalized inputs
+     *       to activation at cell gate.
+     * * 60: The backward output layer normalization weights. Optional.
+     *       A 1-D tensor of shape [bw_num_units]. Used to rescale normalized inputs
+     *       to activation at output gate.
+     *
+     * Outputs:
+     * * 0: The forward output.
+     *      A 3-D tensor of shape:
+     *        If time-major and not merge_outputs:
+     *          [max_time, batch_size, fw_output_size]
+     *        If time-major and merge_outputs:
+     *          [max_time, batch_size, fw_output_size + bw_output_size]
+     *        If batch-major and not merge_outputs:
+     *          [batch_size, max_time, fw_output_size]
+     *        If batch-major and merge_outputs:
+     *          [batch_size, max_time, fw_output_size + bw_output_size]
+     * * 1: The backward output.  Unused if merge_outputs is true.
+     *      A 3-D tensor of shape:
+     *        If time-major: [max_time, batch_size, bw_output_size]
+     *        If batch-major: [batch_size, max_time, bw_output_size]
+     * * 2: The forward activation state output.
+     *      A 2-D tensor of shape [batch_size, fw_output_size] containing an
+     *      activation state from the last time step in the sequence. This
+     *      output is optional and can be omitted. If this output is present
+     *      then outputs 3-5 must be present as well.
+     *      Available since HAL version 1.3.
+     * * 3: The forward cell state output.
+     *      A tensor of shape [batch_size, fw_cell_size] containing a cell state
+     *      from the last time step in the sequence. This output is optional
+     *      and can be omitted. If this output is present
+     *      then outputs 2, 4, 5 must be present as well.
+     *      Available since HAL version 1.3.
+     * * 4: The backward activation state output.
+     *      A 2-D tensor of shape [batch_size, bw_output_size] containing an
+     *      activation state from the last time step in the sequence. This
+     *      output is optional and can be omitted. If this output is present
+     *      then outputs 2, 3, 5 must be present as well.
+     *      Available since HAL version 1.3.
+     * * 5: The backward cell state output.
+     *      A tensor of shape [batch_size, bw_cell_size] containing a cell state
+     *      from the last time step in the sequence. This output is optional
+     *      and can be omitted. If this output is present
+     *      then outputs 2-4 must be present as well.
+     *      Available since HAL version 1.3.
+     */
+    BIDIRECTIONAL_SEQUENCE_LSTM = 42,
+    /**
+     * A recurrent neural network layer that applies a basic RNN cell to a
+     * sequence of inputs in forward and backward directions.
+     *
+     * This Op unrolls the input along the sequence dimension, and implements
+     * the following operation for each element in the sequence s =
+     * 1...sequence_length:
+     *   fw_outputs[s] = fw_state = activation(inputs[s] * fw_input_weights’ +
+     *          fw_state * fw_recurrent_weights’ + fw_bias)
+     *
+     * And for each element in sequence t = sequence_length : 1
+     *   bw_outputs[t] = bw_state = activation(inputs[t] * bw_input_weights’ +
+     *          bw_state * bw_recurrent_weights’ + bw_bias)
+     *
+     * Where:
+     * * “{fw,bw}_input_weights” is a weight matrix that multiplies the inputs;
+     * * “{fw,bw}_recurrent_weights” is a weight matrix that multiplies the
+     *    current “state” which itself is the output from the previous time step
+     *    computation;
+     * * “{fw,bw}_bias” is a bias vector (added to each output vector in the
+     *    batch);
+     * * “activation” is the function passed as the “fused_activation_function”
+     *   argument (if not “NONE”).
+     *
+     * The op supports cross-linking via an auxiliary input. Regular cell feeds
+     * one input into the two RNN cells in the following way:
+     *
+     *       INPUT  (INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_RNN     BW_RNN |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
+     * An op with cross-linking takes two inputs and feeds them into the RNN
+     * cells in the following way:
+     *
+     *       AUX_INPUT   (AUX_INPUT_REVERSED)
+     *           |             |
+     *     INPUT | (INPUT_R'D.)|
+     *       |   |       |     |
+     *    -----------------------
+     *    |  \  /        \    / |
+     *    | FW_RNN       BW_RNN |
+     *    -----------------------
+     *         |           |
+     *      FW_OUT      BW_OUT
+     *
+     * The cross-linking mode is enabled iff auxiliary input and auxiliary
+     * weights are present. While stacking this op on top of itself, this
+     * allows to connect both forward and backward outputs from previous cell
+     * to the next cell's input.
+     *
+     * Since HAL version 1.3 parallel linking mode is supported. The mode is
+     * enabled if auxiliary input is present but auxiliary weights are omitted.
+     * In this case, the cell feeds inputs into the RNN in the following way:
+     *
+     *       INPUT (AUX_INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_RNN     BW_RNN |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
+     * While stacking this op on top of itself, this allows to connect both
+     * forward and backward outputs from previous cell to the next cell's
+     * corresponding inputs.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * The input tensors must all be the same type.
+     *
+     * Inputs:
+     * * 0: input.
+     *      A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
+     *      it is set to true, then the input has a shape [maxTime, batchSize,
+     *      inputSize], otherwise the input has a shape [batchSize, maxTime,
+     *      inputSize].
+     * * 1: fwWeights.
+     *      A 2-D tensor of shape [fwNumUnits, inputSize].
+     * * 2: fwRecurrentWeights.
+     *      A 2-D tensor of shape [fwNumUnits, fwNumUnits].
+     * * 3: fwBias.
+     *      A 1-D tensor of shape [fwNumUnits].
+     * * 4: fwHiddenState.
+     *      A 2-D tensor of shape [batchSize, fwNumUnits]. Specifies a hidden
+     *      state input for the first time step of the computation.
+     * * 5: bwWeights.
+     *      A 2-D tensor of shape [bwNumUnits, inputSize].
+     * * 6: bwRecurrentWeights.
+     *      A 2-D tensor of shape [bwNumUnits, bwNumUnits].
+     * * 7: bwBias.
+     *      A 1-D tensor of shape [bwNumUnits].
+     * * 8: bwHiddenState
+     *      A 2-D tensor of shape [batchSize, bwNumUnits]. Specifies a hidden
+     *      state input for the first time step of the computation.
+     * * 9: auxInput.
+     *      A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
+     *      it is set to true, then the input has a shape [maxTime, batchSize,
+     *      auxInputSize], otherwise the input has a shape [batchSize, maxTime,
+     *      auxInputSize]. Can be omitted. See the docs above for the usage
+     *      modes explanation.
+     * * 10:fwAuxWeights.
+     *      A 2-D tensor of shape [fwNumUnits, auxInputSize]. Can be omitted.
+     *      See the docs above for the usage modes explanation.
+     * * 11:bwAuxWeights.
+     *      A 2-D tensor of shape [bwNumUnits, auxInputSize]. Can be omitted.
+     *      See the docs above for the usage modes explanation.
+     * * 12:fusedActivationFunction.
+     *      A {@link FusedActivationFunc} value indicating the activation function. If
+     *      “NONE” is specified then it results in a linear activation.
+     * * 13:timeMajor
+     *      An {@link OperandType::BOOL} scalar specifying the shape format
+     *      of input and output tensors.
+     * * 14:mergeOutputs
+     *      An {@link OperandType::BOOL} scalar specifying if the outputs
+     *      from forward and backward cells are separate (if set to false) or
+     *      concatenated (if set to true).
+     * Outputs:
+     * * 0: fwOutput.
+     *      A 3-D tensor. The first two dimensions of the shape are defined by
+     *      the input 6 (timeMajor) and the third dimension is defined by the
+     *      input 14 (mergeOutputs). If timeMajor is set to true, then the first
+     *      two dimensions are [maxTime, batchSize], otherwise they are set to
+     *      [batchSize, maxTime]. If mergeOutputs is set to true, then the third
+     *      dimension is equal to (fwNumUnits + bwNumUnits), otherwise it is set
+     *      to fwNumUnits.
+     * * 1: bwOutput.
+     *      A 3-D tensor. If the input 14 (mergeOutputs) is set to true, then
+     *      this tensor is not produced. The shape is defined by the input 6
+     *      (timeMajor). If it is set to true, then the shape is set to
+     *      [maxTime, batchSize, bwNumUnits], otherwise the shape is set to
+     *      [batchSize, maxTime, bwNumUnits].
+     * * 2: The forward hidden state output.
+     *      A 2-D tensor of shape [batchSize, fwNumUnits] containing a hidden
+     *      state from the last time step in the sequence. This output is
+     *      optional and can be omitted. If this output is present then output
+     *      3 must be present as well.
+     *      Available since HAL version 1.3.
+     * * 3: The backward hidden state output.
+     *      A 2-D tensor of shape [batchSize, bwNumUnits] containing a hidden
+     *      state from the last time step in the sequence. This output is
+     *      optional and can be omitted. If this output is present then output
+     *      2 must be present as well.
+     *      Available since HAL version 1.3.
+     */
+    BIDIRECTIONAL_SEQUENCE_RNN = 43,
+    /**
+     * Greedily selects a subset of bounding boxes in descending order of score.
+     *
+     * This op applies NMS algorithm to each class. In each loop of execution,
+     * the box with maximum score gets selected and removed from the pending set.
+     * The scores of the rest of boxes are lowered according to the
+     * intersection-over-union (IOU) overlapping with the previously selected
+     * boxes and a specified NMS kernel method. Any boxes with score less
+     * than a threshold are removed from the pending set.
+     *
+     * Three NMS kernels are supported:
+     * * Hard:     score_new = score_old * (1 if IoU < threshold else 0)
+     * * Linear:   score_new = score_old * (1 if IoU < threshold else 1 - IoU)
+     * * Gaussian: score_new = score_old * exp(- IoU^2 / sigma)
+     *
+     * Axis-aligned bounding boxes are represented by its upper-left corner
+     * coordinate (x1,y1) and lower-right corner coordinate (x2,y2). A valid
+     * bounding box should satisfy x1 <= x2 and y1 <= y2.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Inputs:
+     * * 0: A 2-D Tensor of shape [num_rois, num_classes], specifying the score
+     *      of each bounding box proposal. The boxes are grouped by batches in the
+     *      first dimension. Zero num_rois is supported for this tensor.
+     * * 1: A 2-D Tensor specifying the bounding boxes of shape
+     *      [num_rois, num_classes * 4], organized in the order [x1, y1, x2, y2].
+     *      The boxes are grouped by batches in the first dimension. The sequential
+     *      order of the boxes corresponds with input0. For input0 of type
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM}, this tensor should be of
+     *      {@link OperandType::TENSOR_QUANT16_ASYMM}, with zeroPoint of 0 and
+     *      scale of 0.125.
+     *      For input0 of type {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      this tensor should be of {@link OperandType::TENSOR_QUANT16_ASYMM},
+     *      with zeroPoint of -128 and scale of 0.125.
+     *      Zero num_rois is supported for this tensor.
+     * * 2: A 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [num_rois], specifying the batch index of each box. Boxes with
+     *      the same batch index are grouped together.
+     * * 3: An {@link OperandType::FLOAT32} scalar, score_threshold. Boxes
+     *      with scores lower than the threshold are filtered before sending
+     *      to the NMS algorithm.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the maximum
+     *      number of selected bounding boxes for each image. Set to a negative
+     *      value for unlimited number of output bounding boxes.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the NMS
+     *      kernel method, options are 0:hard, 1:linear, 2:gaussian.
+     * * 6: An {@link OperandType::FLOAT32} scalar, specifying the IoU
+     *      threshold in hard and linear NMS kernel. This field is ignored if
+     *      gaussian kernel is selected.
+     * * 7: An {@link OperandType::FLOAT32} scalar, specifying the sigma in
+     *      gaussian NMS kernel. This field is ignored if gaussian kernel is
+     *      not selected.
+     * * 8: An {@link OperandType::FLOAT32} scalar, nms_score_threshold.
+     *      Boxes with scores lower than the threshold are dropped during the
+     *      score updating phase in soft NMS.
+     *
+     * Outputs:
+     * * 0: A 1-D Tensor of the same {@link OperandType} as input0, with shape
+     *      [num_output_rois], specifying the score of each output box. The boxes
+     *      are grouped by batches, but the sequential order in each batch is not
+     *      guaranteed. For type of {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      guaranteed. For type of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      or {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the scale and zero point must be the same as input0.
+     * * 1: A 2-D Tensor of the same {@link OperandType} as input1, with shape
+     *      [num_output_rois, 4], specifying the coordinates of each
+     *      output bounding box with the same format as input1. The sequential
+     *      order of the boxes corresponds with output0. For type of
+     *      {@link OperandType::TENSOR_QUANT16_ASYMM}, the scale must be
+     *      0.125 and the zero point must be 0.
+     * * 2: A 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [num_output_rois], specifying the class of each output box. The
+     *      sequential order of the boxes corresponds with output0.
+     * * 3: A 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [num_output_rois], specifying the batch index of each box. Boxes
+     *      with the same batch index are grouped together.
+     */
+    BOX_WITH_NMS_LIMIT = 44,
+    /**
+     * Casts a tensor to a type.
+     *
+     * This operation ignores the scale and zeroPoint of quanized tensors,
+     * e.g. it treats a {@link OperandType::TENSOR_QUANT8_ASYMM} input
+     * as a tensor of uint8 values.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * Since HAL version 1.3, casting tensors of the following
+     * {@link OperandType} to the same {@link OperandType} is supported:
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT16_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT16_SYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     * * {@link OperandType::TENSOR_QUANT8_SYMM}
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: A tensor with the same shape as input0.
+     */
+    CAST = 45,
+    /**
+     * Shuffle the channels of the input tensor.
+     *
+     * Given an input tensor and a integer value of num_groups, CHANNEL_SHUFFLE
+     * divide the channel dimension into num_groups groups, and reorganize the
+     * channels by grouping channels with the same index in each group.
+     *
+     * Along the channel dimension, the output is calculated using this formula:
+     *
+     *     output_channel[k * num_groups + g] = input_channel[g * group_size + k]
+     *
+     * where group_size = num_channels / num_groups
+     *
+     * The number of channels must be divisible by num_groups.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be shuffled.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the number of
+     *      groups.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the dimension
+     *      channel shuffle would be performed on. Negative index is used to
+     *      specify axis from the end (e.g. -1 for the last axis). Must be in
+     *      the range [-n, n).
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} and same shape as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    CHANNEL_SHUFFLE = 46,
+    /**
+     * Apply postprocessing steps to bounding box detections.
+     *
+     * Bounding box detections are generated by applying transformation on a set
+     * of predefined anchors with the bounding box deltas from bounding box
+     * regression. A final step of hard NMS is applied to limit the number of
+     * returned boxes.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Inputs:
+     * * 0: A 3-D Tensor of shape [batches, num_anchors, num_classes], specifying
+     *      the score of each anchor with each class. Class 0 for each
+     *      [batches, num_anchors, 0] is background and will be ignored.
+     * * 1: A 3-D Tensor of shape [batches, num_anchors, length_box_encoding], with
+     *      the first four values in length_box_encoding specifying the bounding
+     *      box deltas. The box deltas are encoded in the order of [dy, dx, dh, dw],
+     *      where dy and dx is the linear-scale relative correction factor for the
+     *      center position of the bounding box with respect to the width and height,
+     *      dh and dw is the log-scale relative correction factor for the width and
+     *      height. All the entries in length_box_encoding beyond the first four
+     *      values are ignored in this operation.
+     * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each
+     *      predefined anchor, with format [ctr_y, ctr_x, h, w], where ctr_y and
+     *      ctr_x are the center position of the box, and h and w are the height
+     *      and the width.
+     * * 3: An {@link OperandType::FLOAT32} scalar, specifying the scaling
+     *      factor for dy in bounding box deltas.
+     * * 4: An {@link OperandType::FLOAT32} scalar, specifying the scaling
+     *      factor for dx in bounding box deltas.
+     * * 5: An {@link OperandType::FLOAT32} scalar, specifying the scaling
+     *      factor for dh in bounding box deltas.
+     * * 6: An {@link OperandType::FLOAT32} scalar, specifying the scaling
+     *      factor for dw in bounding box deltas.
+     * * 7: An {@link OperandType::BOOL} scalar, set to true to use regular
+     *      multi-class NMS algorithm that do NMS separately for each class,
+     *      set to false for a faster algorithm that only do one single NMS
+     *      using the highest class score..
+     * * 8: An {@link OperandType::INT32} scalar, max_num_detections, specifying
+     *      the maximum number of boxes for the output. Boxes with the lowest
+     *      scores are discarded to meet the limit.
+     * * 9: An {@link OperandType::INT32} scalar, only used when input7 is
+     *      set to false, specifying the maximum number of classes per detection.
+     * * 10: An {@link OperandType::INT32} scalar, only used when input7 is
+     *       set to true, specifying the maximum number of detections when
+     *       applying NMS algorithm for each single class.
+     * * 11: A scalar, score_threshold. Boxes with scores lower than the
+     *       threshold are filtered before sending to the NMS algorithm. The
+     *       scalar must be of {@link OperandType::FLOAT16} if input0 is of
+     *       {@link OperandType::TENSOR_FLOAT16} and of
+     *       {@link OperandType::FLOAT32} if input0 is of
+     *       {@link OperandType::TENSOR_FLOAT32}.
+     * * 12: A scalar, specifying the IoU threshold for hard NMS. The scalar
+     *       must be of {@link OperandType::FLOAT16} if input0 is of
+     *       {@link OperandType::TENSOR_FLOAT16} and of
+     *       {@link OperandType::FLOAT32} if input0 is of
+     *       {@link OperandType::TENSOR_FLOAT32}.
+     * * 13: An {@link OperandType::BOOL} scalar, set to true to include
+     *       background class in the list of label map for the output, set
+     *       to false to not include the background. When the background
+     *       class is included, it has label 0 and the output classes start
+     *       at 1 in the label map, otherwise, the output classes start at 0.
+     *
+     * Outputs:
+     * * 0: A 2-D tensor of the same {@link OperandType} as input0, with shape
+     *      [batches, max_num_detections], specifying the score of each output
+     *      detections.
+     * * 1: A 3-D tensor of shape [batches, max_num_detections, 4], specifying the
+     *      coordinates of each output bounding box, with format
+     *      [y1, x1, y2, x2].
+     * * 2: A 2-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [batches, max_num_detections], specifying the class label for each
+     *      output detection.
+     * * 3: An 1-D {@link OperandType::TENSOR_INT32} tensor, of shape [batches],
+     *      specifying the number of valid output detections for each batch.
+     */
+    DETECTION_POSTPROCESSING = 47,
+    /**
+     * For input tensors x and y, computes x == y elementwise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and dimensions compatible
+     *      with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    EQUAL = 48,
+    /**
+     * Computes exponential of x element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    EXP = 49,
+    /**
+     * Inserts a dimension of 1 into a tensor's shape.
+     *
+     * Given a tensor input, this operation inserts a dimension of 1 at the
+     * given dimension index of input's shape. The dimension index starts at
+     * zero; if you specify a negative dimension index, it is counted backward
+     * from the end.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: An n-D tensor.
+     * * 1: An {@link OperandType::INT32} scalar specifying the dimension
+     *      index to expand. Must be in the range [-(n + 1), (n + 1)).
+     *
+     * Outputs:
+     * * 0: An (n + 1)-D tensor with the same {@link OperandType} and data as
+     *      input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    EXPAND_DIMS = 50,
+    /**
+     * Gathers values along an axis.
+     *
+     * Produces an output tensor with shape
+     *     input0.dimension[:axis] + indices.dimension + input0.dimension[axis + 1:]
+     * where:
+     *     # Vector indices (output is rank(input0)).
+     *     output[a_0, ..., a_n, i, b_0, ..., b_n] =
+     *       input0[a_0, ..., a_n, indices[i], b_0, ..., b_n]
+     *
+     *     # Higher rank indices (output is rank(input0) + rank(indices) - 1).
+     *     output[a_0, ..., a_n, i, ..., j, b_0, ... b_n] =
+     *       input0[a_0, ..., a_n, indices[i, ..., j], b_0, ..., b_n]
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: An n-D tensor from which to gather values.
+     * * 1: An {@link OperandType::INT32} scalar specifying the axis.
+     *      Negative index is used to specify axis from the end
+     *      (e.g. -1 for the last axis). Must be in the range [-n, n).
+     * * 2: A k-D tensor {@link OperandType::TENSOR_INT32} of indices.
+     *      The values must be in the bounds of the corresponding dimensions
+     *      of input0.
+     *
+     * Outputs:
+     * * 0: An (n + k - 1)-D tensor with the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    GATHER = 51,
+    /**
+     * Generate aixs-aligned bounding box proposals.
+     *
+     * Bounding box proposals are generated by applying transformation on a set
+     * of predefined anchors with the bounding box deltas from bounding box
+     * regression. A final step of hard NMS is applied to limit the number of
+     * returned boxes.
+     *
+     * Axis-aligned bounding boxes are represented by its upper-left corner
+     * coordinate (x1,y1) and lower-right corner coordinate (x2,y2). A valid
+     * bounding box should satisfy x1 <= x2 and y1 <= y2.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Inputs:
+     * * 0: A 4-D Tensor specifying the score of each anchor at each
+     *      location. With "NHWC" data layout, the tensor shape is
+     *      [batches, height, width, num_anchors]. With "NCHW" data layout,
+     *      the tensor shape is [batches, num_anchors, height, width].
+     * * 1: A 4-D Tensor specifying the bounding box deltas. With "NHWC" data
+     *      layout, the tensor shape is [batches, height, width, num_anchors * 4].
+     *      With "NCHW" data layout, the tensor shape is
+     *      [batches, num_anchors * 4, height, width]. The box deltas are encoded
+     *      in the order of [dx, dy, dw, dh], where dx and dy is the linear-scale
+     *      relative correction factor for the center position of the bounding box
+     *      with respect to the width and height, dw and dh is the log-scale
+     *      relative correction factor for the width and height. The last
+     *      dimensions is the channel dimension.
+     * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each
+     *      predefined anchor, with format [x1, y1, x2, y2]. For input0 of type
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} or
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}, this tensor should be of
+     *      {@link OperandType::TENSOR_QUANT16_SYMM}, with scale of 0.125.
+     * * 3: A 2-D Tensor of shape [batches, 2], specifying the size of
+     *      each image in the batch, with format [image_height, image_width].
+     *      For input0 of type {@link OperandType::TENSOR_QUANT8_ASYMM} or
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}, this
+     *      tensor should be of {@link OperandType::TENSOR_QUANT16_SYMM}, with
+     *      scale of 0.125.
+     * * 4: An {@link OperandType::FLOAT32} scalar, specifying the ratio
+     *      from the height of original image to the height of feature map.
+     * * 5: An {@link OperandType::FLOAT32} scalar, specifying the ratio
+     *      from the width of original image to the width of feature map.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the maximum
+     *      number of boxes before going into the hard NMS algorithm. Boxes
+     *      with the lowest scores are discarded to meet the limit. Set to
+     *      a non-positive value for unlimited number.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the maximum
+     *      number of boxes returning from the hard NMS algorithm. Boxes
+     *      with the lowest scores are discarded to meet the limit. Set to
+     *      a non-positive value for unlimited number.
+     * * 8: An {@link OperandType::FLOAT32} scalar, specifying the IoU
+     *      threshold for hard NMS.
+     * * 9: An {@link OperandType::FLOAT32} scalar, min_size. Boxes with
+     *      height or width lower than the absolute threshold are filtered out.
+     * * 10: An {@link OperandType::BOOL} scalar, set to true to specify
+     *       NCHW data layout for input0 and input1. Set to false for NHWC.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0, of shape
+     *      [num_output_rois], specifying the score of each output box.
+     *      The boxes are grouped by batches, but the sequential order in
+     *      each batch is not guaranteed. For type of
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} or
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}, the scale and zero
+     *      point must be the same as input0.
+     * * 1: A tensor of the same {@link OperandType} as input3, of shape
+     *      [num_output_rois, 4], specifying the coordinates of each output
+     *      bounding box for each class, with format [x1, y1, x2, y2].
+     *      The sequential order of the boxes corresponds with output0.
+     *      For type of {@link OperandType::TENSOR_QUANT16_ASYMM}, the
+     *      scale must be 0.125 and the zero point must be 0.
+     * * 2: A 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [num_output_rois], specifying the batch index of each box. Boxes
+     *      with the same batch index are grouped together.
+     */
+    GENERATE_PROPOSALS = 52,
+    /**
+     * For input tensors x and y, computes x > y elementwise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and dimensions compatible
+     *      with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    GREATER = 53,
+    /**
+     * For input tensors x and y, computes x >= y elementwise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and dimensions compatible
+     *      with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    GREATER_EQUAL = 54,
+    /**
+     * Performs a grouped 2-D convolution operation.
+     *
+     * Given an input tensor of shape [batches, height, width, depth_in] and a
+     * filter tensor of shape [depth_out, filter_height, filter_width, depth_group]
+     * containing depth_out convolutional filters of depth depth_group, GROUPED_CONV
+     * applies a group of different filters to each input channel group, then
+     * concatenates the results together.
+     *
+     * Specifically, the input channels are divided into num_groups groups, each with
+     * depth depth_group, i.e. depth_in = num_groups * depth_group. The convolutional
+     * filters are also divided into num_groups groups, i.e. depth_out is divisible
+     * by num_groups. GROUPED_CONV applies each group of filters to the corresponding
+     * input channel group, and the result are concatenated together.
+     *
+     * The output dimensions are functions of the filter dimensions, stride, and
+     * padding.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[b, i, j, g * channel_multiplier + q] =
+     *         sum_{di, dj, dk} (
+     *             input[b, strides[1] * i + di, strides[2] * j + dj,
+     *                   g * depth_group + dk] *
+     *             filter[g * channel_multiplier + q, di, dj, dk]
+     *         ) + bias[channel]
+     *
+     * where channel_multiplier = depth_out / num_groups
+     *
+     * Supported tensor {@link OperandType} configurations:
+     * * 16 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT16} for input, filter, output, and bias.
+     *
+     * * 32 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT32} for input, filter, output, and bias.
+     *
+     * * Quantized:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * * Quantized signed (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * * Quantized with symmetric per channel quantization for the filter:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     *
+     * Both explicit padding and implicit padding are supported.
+     *
+     * Inputs (explicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input, where depth_in = num_groups * depth_group.
+     * * 1: A 4-D tensor, of shape
+     *      [depth_out, filter_height, filter_width, depth_group], specifying
+     *      the filter, where depth_out must be divisible by num_groups.  For
+     *      tensor of type {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
+     *      the channel dimension (channelDim at
+     *      {@link SymmPerChannelQuantParams}) must be set to 0.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32} or
+     *      {@link OperandType::TENSOR_FLOAT16}, the bias must be of the same type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint
+     *      of 0 and bias_scale == input_scale * filter_scale. For filter tensor
+     *      of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}, the bias
+     *      should be of {@link OperandType::TENSOR_INT32}, with zeroPoint of
+     *      0 and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the left, in the ‘width’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the right, in the ‘width’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the top, in the ‘height’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the bottom, in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 8: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 9: An {@link OperandType::INT32} scalar, specifying the number of
+     *      groups.
+     * * 10: An {@link OperandType::INT32} scalar, and has to be one of the
+     *       {@link FusedActivationFunc} values. Specifies the activation to
+     *       invoke on the result.
+     * * 11: An {@link OperandType::BOOL} scalar, set to true to specify
+     *       NCHW data layout for input0 and output0. Set to false for NHWC.
+     *
+     * Inputs (implicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input, where depth_in = num_groups * depth_group.
+     * * 1: A 4-D tensor, of shape
+     *      [depth_out, filter_height, filter_width, depth_group], specifying
+     *      the filter, where depth_out must be divisible by num_groups.  For
+     *      tensor of type {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
+     *      the channel dimension (SymmPerChannelQuantParams::channelDim)
+     *      must be set to 0.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32} or
+     *      {@link OperandType::TENSOR_FLOAT16}, the bias must be of the same
+     *      {@link OperandType::TENSOR_FLOAT16}, the bias must be of the same type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      the bias should be of {@link OperandType::TENSOR_INT32}, with zeroPoint
+     *      of 0 and bias_scale == input_scale * filter_scale. For filter tensor
+     *      of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}, the bias
+     *      should be of {@link OperandType::TENSOR_INT32}, with zeroPoint of
+     *      0 and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::INT32} scalar, specifying the implicit
+     *      padding scheme, has to be one of the
+     *      following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the number of
+     *      groups.
+     * * 7: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 8: An {@link OperandType::BOOL} scalar, set to true to specify
+     *      NCHW data layout for input0 and output0. Set to false for NHWC.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, out_height, out_width, depth_out].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.
+     */
+    GROUPED_CONV_2D = 55,
+    /**
+     * Localize the maximum keypoints from heatmaps.
+     *
+     * This operation approximates the accurate maximum keypoint scores and
+     * indices after bicubic upscaling by using Taylor expansion up to the
+     * quadratic term.
+     *
+     * The bounding box is represented by its upper-left corner coordinate
+     * (x1,y1) and lower-right corner coordinate (x2,y2) in the original image.
+     * A valid bounding box should satisfy x1 <= x2 and y1 <= y2.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     *
+     * Inputs:
+     * * 0: A 4-D Tensor of shape
+     *      [num_boxes, heatmap_size, heatmap_size, num_keypoints],
+     *      specifying the heatmaps, the height and width of heatmaps should
+     *      be the same, and must be greater than or equal to 2.
+     * * 1: A 2-D Tensor of shape [num_boxes, 4], specifying the bounding boxes,
+     *      each with format [x1, y1, x2, y2]. For input0 of type
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM}, this tensor should
+     *      be of {@link OperandType::TENSOR_QUANT16_ASYMM}, with zeroPoint
+     *      of 0 and scale of 0.125.
+     *      For input0 of type
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}, this tensor
+     *      should be of {@link OperandType::TENSOR_QUANT16_ASYMM}, with
+     *      zeroPoint of -128 and scale of 0.125.
+     * * 2: An {@link OperandType::BOOL} scalar, set to true to specify
+     *      NCHW data layout for input0. Set to false for NHWC.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0, with shape
+     *      [num_boxes, num_keypoints], specifying score of the keypoints.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} or
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint can be different from input0 scale and zeroPoint.
+     * * 1: A tensor of the same {@link OperandType} as input1, with shape
+     *      [num_boxes, num_keypoints, 2], specifying the location of
+     *      the keypoints, the second dimension is organized as
+     *      [keypoint_x, keypoint_y].
+     *      For type of {@link OperandType::TENSOR_QUANT16_ASYMM}, the
+     *      scale must be 0.125 and the zero point must be 0.
+     */
+    HEATMAP_MAX_KEYPOINT = 56,
+    /**
+     * Applies instance normalization to the input tensor.
+     *
+     * The values in the output tensor are computed as:
+     *
+     *     output[b, h, w, c] =
+     *         (input[b, h, w, c] - mean[b, c]) * gamma /
+     *         sqrt(var[b, c] + epsilon) + beta
+     *
+     * Where the mean and variance are computed across the spatial dimensions:
+     *
+     *     mean[b, c] =
+     *         sum_{h, w}(input[b, h, w, c]) / sum(1)
+     *
+     *     var[b, c] =
+     *         sum_{h, w}(pow(input[b, h, w, c] - mean[b, c], 2)) / sum(1)
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be normalized.
+     * * 1: A scalar, specifying gamma, the scale applied to the normalized
+     *      tensor. The scalar must be of {@link OperandType::FLOAT16} if
+     *      input0 is of {@link OperandType::TENSOR_FLOAT16} and of
+     *      {@link OperandType::FLOAT32} if input0 is of
+     *      {@link OperandType::TENSOR_FLOAT32}.
+     * * 2: A scalar, specifying beta, the offset applied to the normalized
+     *      tensor. The scalar must be of {@link OperandType::FLOAT16} if
+     *      input0 is of {@link OperandType::TENSOR_FLOAT16} and of
+     *      {@link OperandType::FLOAT32} if input0 is of
+     *      {@link OperandType::TENSOR_FLOAT32}.
+     * * 3: A scalar, specifying epsilon, the small value added to variance to
+     *      avoid dividing by zero. The scalar must be of {@link OperandType::FLOAT16} if
+     *      input0 is of {@link OperandType::TENSOR_FLOAT16} and of
+     *      {@link OperandType::FLOAT32} if input0 is of
+     *      {@link OperandType::TENSOR_FLOAT32}.
+     * * 4: An {@link OperandType::BOOL} scalar, set to true to specify
+     *      NCHW data layout for input0 and output0. Set to false for NHWC.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} and same shape as input0.
+     */
+    INSTANCE_NORMALIZATION = 57,
+    /**
+     * For input tensors x and y, computes x < y elementwise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and dimensions compatible
+     *      with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    LESS = 58,
+    /**
+     * For input tensors x and y, computes x <= y elementwise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and dimensions compatible
+     *      with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    LESS_EQUAL = 59,
+    /**
+     * Computes natural logarithm of x element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    LOG = 60,
+    /**
+     * Returns the truth value of x AND y element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     * * 1: A tensor of {@link OperandType::TENSOR_BOOL8} and dimensions
+     *      compatible with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    LOGICAL_AND = 61,
+    /**
+     * Computes the truth value of NOT x element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    LOGICAL_NOT = 62,
+    /**
+     * Returns the truth value of x OR y element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     * * 1: A tensor of {@link OperandType::TENSOR_BOOL8} and dimensions
+     *      compatible with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    LOGICAL_OR = 63,
+    /**
+     * Computes the log softmax activations given logits.
+     *
+     * The output is calculated using this formula:
+     *
+     *     output = logits * beta - log(reduce_sum(exp(logits * beta), axis))
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor specifying the input logits.
+     * * 1: A scalar, specifying the positive scaling factor for the exponent,
+     *      beta.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT16}, the beta
+     *      value must be of {@link OperandType::FLOAT16}.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT32}, the beta
+     *      value must be of {@link OperandType::FLOAT32}.
+     * * 2: An {@link OperandType::INT32} scalar specifying the axis to
+     *      reduce across. Negative index is used to specify axis from the
+     *      end (e.g. -1 for the last axis). Must be in the range [-n, n).
+     *
+     * Outputs:
+     * * 0: The output tensor of the same {@link OperandType} and shape as
+     *      input0.
+     */
+    LOG_SOFTMAX = 64,
+    /**
+     * Returns the element-wise maximum of two tensors.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and compatible dimensions
+     *      with input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
+     *      the scales and zeroPoint can be different from input0 scale and zeroPoint.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
+     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.
+     */
+    MAXIMUM = 65,
+    /**
+     * Returns the element-wise minimum of two tensors.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and compatible dimensions
+     *      with input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
+     *      the scales and zeroPoint can be different from input0 scale and zeroPoint.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
+     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.
+     */
+    MINIMUM = 66,
+    /**
+     * Computes numerical negative value element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    NEG = 67,
+    /**
+     * For input tensors x and y, computes x != y elementwise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * This operation supports broadcasting.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     * * 1: A tensor of the same {@link OperandType} and dimensions compatible
+     *      with input0.
+     *
+     * Outputs:
+     * * 0: A tensor of {@link OperandType::TENSOR_BOOL8}.
+     */
+    NOT_EQUAL = 68,
+    /**
+     * Pads a tensor with the given constant value according to the specified
+     * paddings.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor, specifying the tensor to be padded.
+     * * 1: A 2-D Tensor of {@link OperandType::TENSOR_INT32}, the paddings
+     *      for each spatial dimension of the input tensor. The shape of the
+     *      tensor must be {rank(input0), 2}.
+     *      padding[i, 0] specifies the number of elements to be padded in the
+     *      front of dimension i.
+     *      padding[i, 1] specifies the number of elements to be padded after
+     *      the end of dimension i.
+     * * 2: An scalar specifying the value to use for padding input0.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT16}, the
+     *      pad value must be of {@link OperandType::FLOAT16}.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT32}, the
+     *      pad value must be of {@link OperandType::FLOAT32}.
+     *      For input tensor of {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the pad value must be of {@link OperandType::INT32}. The
+     *      scale and zeroPoint are assumed to be the same as in input0.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0. The
+     *      output tensor has the same rank as input0, and each
+     *      dimension of the output tensor has the same size as the
+     *      corresponding dimension of the input tensor plus the size
+     *      of the padding:
+     *          output0.dimension[i] =
+     *              padding[i, 0] + input0.dimension[i] + padding[i, 1]
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    PAD_V2 = 69,
+    /**
+     * Computes the power of one value to another.
+     *
+     * Given a tensor base and a tensor exponent, this operation computes
+     * base^exponent elementwise.
+     *
+     * This operations supports broadcasting. The size of the output is the
+     * maximum size along each dimension of the input operands. It starts with
+     * the trailing dimensions, and works its way forward.
+     *
+     * For example:
+     *     base.dimension     =    {4, 1, 2}
+     *     exponent.dimension = {5, 4, 3, 1}
+     *     output.dimension   = {5, 4, 3, 2}
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: A tensor specifying the base.
+     * * 1: A tensor specifying the exponent.
+     *
+     * Outputs:
+     * * 0: An output tensor.
+     */
+    POW = 70,
+    /**
+     * Parametric Rectified Linear Unit.
+     *
+     * It follows: f(x) = alpha * x for x < 0, f(x) = x for x >= 0, where alpha
+     * is a learned array with the same {@link OperandType} and compatible
+     * dimensions as input x.
+     *
+     * Two dimensions are compatible when:
+     *     1. they are equal, or
+     *     2. one of them is 1
+     *
+     * The size of the output is the maximum size along each dimension of the
+     * input operands. It starts with the trailing dimensions, and works its way
+     * forward.
+     *
+     * Example:
+     *     input.dimension  =    {4, 1, 2}
+     *     alpha.dimension  = {5, 4, 3, 1}
+     *     output.dimension = {5, 4, 3, 2}
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input.
+     * * 1: A tensor of the same {@link OperandType}, and compatible dimensions
+     *      as input0, specifying the alpha.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scales and zeroPoint can be different from input0 scale and zeroPoint.
+     */
+    PRELU = 71,
+    /**
+     * Quantizes the input tensor.
+     *
+     * The formula for {@link OperandType::TENSOR_QUANT8_ASYMM} output tensor is:
+     *
+     *     output = max(0, min(255, round(input / scale) + zeroPoint)
+     *
+     * The formula for {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} output
+     * tensor is:
+     *
+     *     output = max(-128, min(127, round(input / scale) + zeroPoint)
+     *
+     * Supported input tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported output tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: A tensor, may be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0, but with
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM} or.
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}.
+     */
+    QUANTIZE = 72,
+    /**
+     * A version of quantized LSTM, using 16 bit quantization for internal
+     * state.
+     *
+     * There is no projection layer, so cell state size is equal to the output
+     * size.
+     *
+     * Inputs:
+     * * 0: A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [numBatches, inputSize] specifying the input to the LSTM
+     *      cell. Tensor is quantized with a fixed quantization range of
+     *      [-1, 127/128] (scale = 1/128, zeroPoint = 128).
+     * * 1: The input-to-input weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, inputSize] specifying input-to-input part of
+     *      weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 2: The input-to-forget weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, inputSize] specifying input-to-forget part of
+     *      weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 3: The input-to-cell weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, inputSize] specifying input-to-cell part of
+     *      weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 4: The input-to-output weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, inputSize] specifying input-to-output part of
+     *      weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 5: The recurrent-to-input weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, outputSize] specifying recurrent-to-input part
+     *      of weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 6: The recurrent-to-forget weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, outputSize] specifying recurrent-to-forget
+     *      part of weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 7: The recurrent-to-cell weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, outputSize] specifying recurrent-to-cell part
+     *      of weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 8: The recurrent-to-output weights.
+     *      A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [outputSize, outputSize] specifying recurrent-to-output
+     *      part of weights for fully-connected layer inside the LSTM cell.
+     *      Quantization zero point and scale must be the same across all the
+     *      weights.
+     * * 9: The input gate bias.
+     *      A 1-D tensor of type {@link OperandType::TENSOR_INT32} and shape
+     *      [outputSize] specifying the bias for the fully-connected layer
+     *      inside the LSTM cell. Bias is quantized with scale being a product
+     *      of input and weights scales and zeroPoint equal to 0.
+     * * 10:The forget gate bias.
+     *      A 1-D tensor of type {@link OperandType::TENSOR_INT32} and shape
+     *      [outputSize] specifying the bias for the fully-connected layer
+     *      inside the LSTM cell. Bias is quantized with scale being a product
+     *      of input and weights scales and zeroPoint equal to 0.
+     * * 11:The cell bias.
+     *      A 1-D tensor of type {@link OperandType::TENSOR_INT32} and shape
+     *      [outputSize] specifying the bias for the fully-connected layer
+     *      inside the LSTM cell. Bias is quantized with scale being a product
+     *      of input and weights scales and zeroPoint equal to 0.
+     * * 12:The output gate bias.
+     *      A 1-D tensor of type {@link OperandType::TENSOR_INT32} and shape
+     *      [outputSize] specifying the bias for the fully-connected layer
+     *      inside the LSTM cell. Bias is quantized with scale being a product
+     *      of input and weights scales and zeroPoint equal to 0.
+     * * 13: A 2-D tensor of type {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       and shape [numBatches, outputSize] specifying the cell state from the
+     *       previous time step of the LSTM cell. It is quantized using a
+     *       quantization range of [-2^4, 2^4 * 32767/32768] (scale = 2^4 /
+     *       32768, zeroPoint = 0).
+     * * 14: A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *       and shape [numBathes, outputSize] specifying the output of the LSTM
+     *       cell from previous time-step. Tensor is quantized with a fixed
+     *       quantization range of [-1, 127/128] (scale = 1/128, zeroPoint =
+     *       128).
+     *
+     *
+     * Outputs:
+     * * 0: A 2-D tensor of type {@link OperandType::TENSOR_QUANT16_SYMM}
+     *      and shape [numBatches, outputSize] which contains a cell state from
+     *      the current time step. Tensor is quantized using a quantization
+     *      range of [-2^4, 2^4 * 32767/32768] (scale = 2^4 / 32768, zeroPoint =
+     *      0).
+     * * 1: A 2-D tensor of type {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and shape [numBathes, outputSize] which contains the output value.
+     *      Tensor is quantized with a fixed quantization range of [-1, 127/128]
+     *      (scale = 1/128, zeroPoint = 128).
+     */
+    QUANTIZED_16BIT_LSTM = 73,
+    /**
+     * Draws samples from a multinomial distribution.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Inputs:
+     * * 0: A 2-D tensor with shape [batches, classes], specifying the
+     *      unnormalized log-probabilities for all classes.
+     * * 1: A scalar {@link OperandType::INT32}, specifying the number of
+     *      independent samples to draw for each row slice.
+     * * 2: A 1-D {@link OperandType::TENSOR_INT32} tensor with shape [2],
+     *      specifying seeds used to initialize the random distribution. If both
+     *      provided seeds are 0, both will be randomly generated.
+     * Outputs:
+     * * 0: A 2-D {@link OperandType::TENSOR_INT32} tensor with shape
+     *      [batches, samples], containing the drawn samples.
+     */
+    RANDOM_MULTINOMIAL = 74,
+    /**
+     * Reduces a tensor by computing the "logical and" of elements along given
+     * dimensions.
+     *
+     * If keep_dims is true, the reduced dimensions are
+     * retained with length 1. Otherwise, the rank of the tensor is reduced by
+     * 1 for each entry in dimensions.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor.
+     * * 1: A 1-D tensor of {@link OperandType::TENSOR_INT32}. The dimensions
+     *      to reduce. Dimension values must be in the range [-n, n).
+     * * 2: An {@link OperandType::BOOL} scalar, keep_dims. If true,
+     *      retains reduced dimensions with length 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      If all dimensions are reduced and keep_dims is false, the output
+     *      shape is [1].
+     */
+    REDUCE_ALL = 75,
+    /**
+     * Reduces a tensor by computing the "logical or" of elements along given
+     * dimensions.
+     *
+     * If keep_dims is true, the reduced dimensions are
+     * retained with length 1. Otherwise, the rank of the tensor is reduced by
+     * 1 for each entry in dimensions.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_BOOL8}
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor.
+     * * 1: A 1-D tensor of {@link OperandType::TENSOR_INT32}. The dimensions
+     *      to reduce. Dimension values must be in the range [-n, n).
+     * * 2: An {@link OperandType::BOOL} scalar, keep_dims. If true,
+     *      retains reduced dimensions with length 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      If all dimensions are reduced and keep_dims is false, the output
+     *      shape is [1].
+     */
+    REDUCE_ANY = 76,
+    /**
+     * Reduces a tensor by computing the maximum of elements along given
+     * dimensions.
+     *
+     * If keep_dims is true, the reduced dimensions are
+     * retained with length 1. Otherwise, the rank of the tensor is reduced by
+     * 1 for each entry in dimensions.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor.
+     * * 1: A 1-D tensor of {@link OperandType::TENSOR_INT32}. The dimensions
+     *      to reduce. Dimension values must be in the range [-n, n).
+     * * 2: An {@link OperandType::BOOL} scalar, keep_dims. If true,
+     *      retains reduced dimensions with length 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      If all dimensions are reduced and keep_dims is false, the output
+     *      shape is [1].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    REDUCE_MAX = 77,
+    /**
+     * Reduces a tensor by computing the minimum of elements along given
+     * dimensions.
+     *
+     * If keep_dims is true, the reduced dimensions are
+     * retained with length 1. Otherwise, the rank of the tensor is reduced by
+     * 1 for each entry in dimensions.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor.
+     * * 1: A 1-D tensor of {@link OperandType::TENSOR_INT32}. The dimensions
+     *      to reduce. Dimension values must be in the range [-n, n).
+     * * 2: An {@link OperandType::BOOL} scalar, keep_dims. If true,
+     *      retains reduced dimensions with length 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      If all dimensions are reduced and keep_dims is false, the output
+     *      shape is [1].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    REDUCE_MIN = 78,
+    /**
+     * Reduces a tensor by multiplying elements along given dimensions.
+     *
+     * If keep_dims is true, the reduced dimensions are
+     * retained with length 1. Otherwise, the rank of the tensor is reduced by
+     * 1 for each entry in dimensions.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor.
+     * * 1: A 1-D tensor of {@link OperandType::TENSOR_INT32}. The dimensions
+     *      to reduce. Dimension values must be in the range [-n, n).
+     * * 2: An {@link OperandType::BOOL} scalar, keep_dims. If true,
+     *      retains reduced dimensions with length 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      If all dimensions are reduced and keep_dims is false, the output
+     *      shape is [1].
+     */
+    REDUCE_PROD = 79,
+    /**
+     * Reduces a tensor by summing elements along given dimensions.
+     *
+     * If keep_dims is true, the reduced dimensions are
+     * retained with length 1. Otherwise, the rank of the tensor is reduced by
+     * 1 for each entry in dimensions.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D tensor.
+     * * 1: A 1-D tensor of {@link OperandType::TENSOR_INT32}. The dimensions
+     *      to reduce. Dimension values must be in the range [-n, n).
+     * * 2: An {@link OperandType::BOOL} scalar, keep_dims. If true,
+     *      retains reduced dimensions with length 1.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0.
+     *      If all dimensions are reduced and keep_dims is false, the output
+     *      shape is [1].
+     */
+    REDUCE_SUM = 80,
+    /**
+     * Select and scale the feature map of each region of interest to a unified
+     * output size by average pooling sampling points from bilinear interpolation.
+     *
+     * The region of interest is represented by its upper-left corner coordinate
+     * (x1,y1) and lower-right corner coordinate (x2,y2) in the original image.
+     * A spatial scaling factor is applied to map into feature map coordinate.
+     * A valid region of interest should satisfy x1 <= x2 and y1 <= y2.
+     *
+     * No rounding is applied in this operation. The sampling points are unified
+     * distributed in the pooling bin and their values are calculated by bilinear
+     * interpolation.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     *
+     * Inputs:
+     * * 0: A 4-D tensor, specifying the feature map.
+     * * 1: A 2-D Tensor of shape [num_rois, 4], specifying the locations of
+     *      the regions of interest, each line with format [x1, y1, x2, y2].
+     *      For input0 of type {@link OperandType::TENSOR_QUANT8_ASYMM},
+     *      this tensor should be of {@link OperandType::TENSOR_QUANT16_ASYMM},
+     *      with zeroPoint of 0 and scale of 0.125. Zero num_rois is
+     *      supported for this tensor.
+     * * 2: An 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [num_rois], specifying the batch index of each box. Boxes with
+     *      the same batch index are grouped together. Zero num_rois is
+     *      supported for this tensor.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the output
+     *      height of the output tensor.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the output
+     *      width of the output tensor.
+     * * 5: An {@link OperandType::FLOAT32} scalar, specifying the ratio
+     *      from the height of original image to the height of feature map.
+     * * 6: An {@link OperandType::FLOAT32} scalar, specifying the ratio
+     *      from the width of original image to the width of feature map.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the number of
+     *      sampling points in height dimension used to compute the output.
+     *      Set to 0 for adaptive value of ceil(roi_height/out_height).
+     * * 8: An {@link OperandType::INT32} scalar, specifying the number of
+     *      sampling points in width dimension used to compute the output.
+     *      Set to 0 for adaptive value of ceil(roi_width/out_width).
+     * * 9: An {@link OperandType::BOOL} scalar, set to true to specify
+     *      NCHW data layout for input0 and output0. Set to false for NHWC.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0. The output
+     *      shape is [num_rois, out_height, out_width, depth].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint can be different from the input0 scale and zeroPoint.
+     */
+    ROI_ALIGN = 81,
+    /**
+     * Select and scale the feature map of each region of interest to a unified
+     * output size by max-pooling.
+     *
+     * The region of interest is represented by its upper-left corner coordinate
+     * (x1,y1) and lower-right corner coordinate (x2,y2) in the original image.
+     * A spatial scaling factor is applied to map into feature map coordinate.
+     * A valid region of interest should satisfy x1 <= x2 and y1 <= y2.
+     *
+     * Rounding is applied in this operation to ensure integer boundary for
+     * regions of interest and pooling bins.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     *
+     * Inputs:
+     * * 0: A 4-D tensor, specifying the feature map.
+     * * 1: A 2-D Tensor of shape [num_rois, 4], specifying the locations of
+     *      the regions of interest, each line with format [x1, y1, x2, y2].
+     *      For input0 of type {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      this tensor should be of {@link OperandType::TENSOR_QUANT16_ASYMM},
+     *      with zeroPoint of 0 and scale of 0.125.
+     * * 2: An 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
+     *      [num_rois], specifying the batch index of each box. Boxes with
+     *      the same batch index are grouped together.
+     * * 3: An {@link OperandType::INT32} scalar, specifying the output
+     *      height of the output tensor.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the output
+     *      width of the output tensor.
+     * * 5: An {@link OperandType::FLOAT32} scalar, specifying the ratio
+     *      from the height of original image to the height of feature map.
+     * * 6: An {@link OperandType::FLOAT32} scalar, specifying the ratio
+     *      from the width of original image to the width of feature map.
+     * * 7: An {@link OperandType::BOOL} scalar, set to true to specify
+     *      NCHW data layout for input0 and output0. Set to false for NHWC.
+     *
+     * Outputs:
+     * * 0: A tensor of the same {@link OperandType} as input0. The output
+     *      shape is [num_rois, out_height, out_width, depth].
+     *      For input0 of type {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    ROI_POOLING = 82,
+    /**
+     * Computes reciprocal of square root of x element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    RSQRT = 83,
+    /**
+     * Using a tensor of booleans c and input tensors x and y select values
+     * elementwise from both input tensors:
+     *
+     * O[i] = C[i] ? x[i] : y[i].
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: A tensor of type {@link OperandType::TENSOR_BOOL8} acting as a
+     *      mask that chooses, based on the value at each element, whether the
+     *      corresponding element in the output should be taken from input1 (if
+     *      true) or input2 (if false).
+     * * 1: An input tensor of the same shape as input0.
+     * * 2: An input tensor of the same shape and type as input1.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scales and zeroPoint can be different from input1 scale and zeroPoint.
+     *
+     * Outputs:
+     * * 0: A tensor of the same type and shape as input1 and input2.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,
+     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.
+     */
+    SELECT = 84,
+    /**
+     * Computes sin of x element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    SIN = 85,
+    /**
+     * Extracts a slice of specified size from the input tensor starting at a
+     * specified location.
+     *
+     * The starting location is specified as a 1-D tensor containing offsets
+     * for each dimension. The size is specified as a 1-D tensor containing
+     * either size of a slice along corresponding dimension or -1. In the latter
+     * case, all the remaining elements in dimension are included in the slice.
+     *
+     * A sum of begin offset and a size of a slice must not exceed size of a
+     * corresponding dimension.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: An n-D tensor to take slice from, may be zero-sized.
+     * * 1: A 1-D tensor of type {@link OperandType::TENSOR_INT32} specifying
+     *      the beginning indices of the slice in each dimension.
+     * * 2: A 1-D tensor of type {@link OperandType::TENSOR_INT32} specifying
+     *      the size of the slice in each dimension.
+     *
+     * Outputs:
+     * * 0: An n-D tensor of the same type as the input containing the slice.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      its scale and zeroPoint has to be same as the input0 scale and zeroPoint.
+     */
+    SLICE = 86,
+    /**
+     * Splits a tensor along a given axis into num_splits subtensors.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: An n-D tensor to split.
+     * * 1: An {@link OperandType::INT32} scalar specifying the axis along
+     *      which to split.
+     * * 2: An {@link OperandType::INT32} scalar indicating the number of
+     *      splits along given axis. Must evenly divide axis size.
+     *
+     * Outputs:
+     * * 0 ~ (num_splits - 1): Resulting subtensors.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    SPLIT = 87,
+    /**
+     * Computes square root of x element-wise.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape as input0.
+     */
+    SQRT = 88,
+    /**
+     * Constructs a tensor by tiling a given tensor.
+     *
+     * This operation creates a new tensor by replicating `input` `multiples`
+     * times. The output tensor's i-th dimension has `input.dims(i) * multiples[i]`
+     * elements, and the values of `input` are replicated `multiples[i]` times
+     * along the i-th dimension.
+     * For example, tiling `[a b c d]` by `[2]` produces `[a b c d a b c d]`.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: input, an n-D tensor specifying the input.
+     * * 1: multiples, a 1-D tensor of {@link OperandType::TENSOR_INT32}.
+     *      The length of multiples must be n.
+     *
+     * Outputs:
+     * * 0: A tiled tensor of the same {@link OperandType} and rank as `input`.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    TILE = 89,
+    /**
+     * Finds values and indices of the k largest entries for the last dimension.
+     *
+     * Resulting values in each dimensions are sorted in descending order. If
+     * two values are equal, the one with larger index appears first.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: from 1
+     *
+     * Inputs:
+     * * 0: input, an n-D tensor specifying the input.
+     * * 1: k, an {@link OperandType::INT32} scalar, specifying the number of
+     *      top elements to look for along the last dimension.
+     *
+     * Outputs:
+     * * 0: An n-D tensor of the same type as the input, containing the k
+     *      largest elements along each last dimensional slice.
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     * * 1: An n-D tensor of type {@link OperandType::TENSOR_INT32}
+     *      containing the indices of values within the last dimension of input.
+     */
+    TOPK_V2 = 90,
+    /**
+     * Performs the transpose of 2-D convolution operation.
+     *
+     * This operation is sometimes called "deconvolution" after Deconvolutional
+     * Networks, but is actually the transpose (gradient) of
+     * {@link OperandType::CONV_2D} rather than an actual deconvolution.
+     *
+     * The output dimensions are functions of the filter dimensions, stride, and
+     * padding.
+     *
+     * Supported tensor {@link OperandType} configurations:
+     * * 16 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT16} for input, filter, output, and bias.
+     *
+     * * 32 bit floating point:
+     * * * {@link OperandType::TENSOR_FLOAT32} for input, filter, output, and bias.
+     *
+     * * Quantized:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * * Quantized with symmetric per channel quantization for the filter:
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * Available since HAL version 1.3:
+     * * Quantized signed (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, filter, and output.
+     * * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
+     * * * input.scale * filter.scale).
+     *
+     * * Quantized signed with filter symmetric per channel quantization (since HAL version 1.3):
+     * * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} for input, and output.
+     * * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
+     * * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
+     * * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     *
+     * Both explicit padding and implicit padding are supported.
+     *
+     * Inputs (explicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     * * 1: A 4-D tensor, of shape
+     *      [depth_out, filter_height, filter_width, depth_in], specifying the
+     *      filter. For tensor of type
+     *      {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} the channel
+     *      dimension (SymmPerChannelQuantParams::channelDim) must be set to 0.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32} or
+     *      {@link OperandType::TENSOR_FLOAT16}, the bias must be of the
+     *      same type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the bias should be of {@link OperandType::TENSOR_INT32},
+     *      with zeroPoint of 0 and bias_scale == input_scale * filter_scale.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL},
+     *      the bias must be of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0
+     *      and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the left, in the ‘width’ dimension.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the right, in the ‘width’ dimension.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the top, in the ‘height’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the padding on
+     *      the bottom, in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 8: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 9: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 10: An {@link OperandType::BOOL} scalar, set to true to specify
+     *       NCHW data layout for input0 and output0. Set to false for NHWC.
+     *
+     * Inputs (implicit padding):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
+     *      specifying the input.
+     * * 1: A 4-D tensor, of shape
+     *      [depth_out, filter_height, filter_width, depth_in], specifying the
+     *      filter. For tensor of type
+     *      {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} the channel
+     *      dimension (SymmPerChannelQuantParams::channelDim) must be set to 0.
+     * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
+     *      tensor of type {@link OperandType::TENSOR_FLOAT32} or
+     *      {@link OperandType::TENSOR_FLOAT16}, the bias should be of the
+     *      same type.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}
+     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+     *      the bias should be of {@link OperandType::TENSOR_INT32},
+     *      with zeroPoint of 0 and bias_scale == input_scale * filter_scale.
+     *      For filter tensor of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL},
+     *      the bias must be of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0
+     *      and bias_scale of 0. The actual scale of each value 'i' is equal to
+     *      bias_scale[i] = input_scale * filter_scale[i].
+     * * 3: An {@link OperandType::TENSOR_INT32} tensor, specifying the output
+     *      tensor shape.
+     * * 4: An {@link OperandType::INT32} scalar, specifying the implicit
+     *      padding scheme, has to be one of the
+     *      following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
+     * * 5: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘width’ dimension.
+     * * 6: An {@link OperandType::INT32} scalar, specifying the stride when
+     *      walking through input in the ‘height’ dimension.
+     * * 7: An {@link OperandType::INT32} scalar, and has to be one of the
+     *      {@link FusedActivationFunc} values. Specifies the activation to
+     *      invoke on the result.
+     * * 8: An {@link OperandType::BOOL} scalar, set to true to specify
+     *      NCHW data layout for input0 and output0. Set to false for NHWC.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, out_height, out_width, depth_out].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.
+     */
+    TRANSPOSE_CONV_2D = 91,
+    /**
+     * A recurrent neural network specified by an LSTM cell.
+     *
+     * Performs (fully) dynamic unrolling of input.
+     *
+     * This Op unrolls the input along the time dimension, and implements the
+     * following operation for each element in the sequence
+     * s = 1...sequence_length:
+     *   outputs[s] = projection(state = activation(LSTMOp(inputs[s])))
+     *
+     * Where LSTMOp is the LSTM op as in {@link OperandType::LSTM},
+     * the "projection" is an optional projection layer from state and output
+     * and the “activation” is the function passed as the
+     * “fused_activation_function” argument (if not “NONE”).
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: 3, either time-major or batch-major.
+     *
+     * All input and output tensors must be of the same type.
+     *
+     * Inputs:
+     * * 0: The input (\f$x_t\f$).
+     *      A 3-D tensor of shape:
+     *        If time-major: [max_time, batch_size, input_size]
+     *        If batch-major: [batch_size, max_time, input_size]
+     *      where “max_time” is the number of timesteps (sequence length),
+     *      “batch_size” corresponds to the batching dimension, and
+     *      “input_size” is the size of the input.
+     * * 1: The input-to-input weights (\f$W_{xi}\f$). Optional.
+     *      A 2-D tensor of shape [num_units, input_size], where “num_units”
+     *      corresponds to the number of cell units.
+     * * 2: The input-to-forget weights (\f$W_{xf}\f$).
+     *      A 2-D tensor of shape [num_units, input_size].
+     * * 3: The input-to-cell weights (\f$W_{xc}\f$).
+     *      A 2-D tensor of shape [num_units, input_size].
+     * * 4: The input-to-output weights (\f$W_{xo}\f$).
+     *      A 2-D tensor of shape [num_units, input_size].
+     * * 5: The recurrent-to-input weights (\f$W_{hi}\f$). Optional.
+     *      A 2-D tensor of shape [num_units, output_size], where “output_size”
+     *      corresponds to either the number of cell units (i.e., “num_units”),
+     *      or the second dimension of the “projection_weights”, if defined.
+     * * 6: The recurrent-to-forget weights (\f$W_{hf}\f$).
+     *      A 2-D tensor of shape [num_units, output_size].
+     * * 7: The recurrent-to-cell weights (\f$W_{hc}\f$).
+     *      A 2-D tensor of shape [num_units, output_size].
+     * * 8: The recurrent-to-output weights (\f$W_{ho}\f$).
+     *      A 2-D tensor of shape [num_units, output_size].
+     * * 9: The cell-to-input weights (\f$W_{ci}\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 10:The cell-to-forget weights (\f$W_{cf}\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 11:The cell-to-output weights (\f$W_{co}\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 12:The input gate bias (\f$b_i\f$). Optional.
+     *      A 1-D tensor of shape [num_units].
+     * * 13:The forget gate bias (\f$b_f\f$).
+     *      A 1-D tensor of shape [num_units].
+     * * 14:The cell bias (\f$b_c\f$).
+     *      A 1-D tensor of shape [num_units].
+     * * 15:The output gate bias (\f$b_o\f$).
+     *      A 1-D tensor of shape [num_units].
+     * * 16:The projection weights (\f$W_{proj}\f$). Optional.
+     *      A 2-D tensor of shape [output_size, num_units].
+     * * 17:The projection bias (\f$b_{proj}\f$). Optional.
+     *      A 1-D tensor of shape [output_size].
+     * * 18:The output state (in) (\f$h_{t-1}\f$).
+     *      A 2-D tensor of shape [batch_size, output_size].
+     * * 19:The cell state (in) (\f$C_{t-1}\f$).
+     *      A 2-D tensor of shape [batch_size, num_units].
+     * * 20:The activation function (\f$g\f$).
+     *      A value indicating the activation function:
+     *      <ul>
+     *      <li>0: None;
+     *      <li>1: Relu;
+     *      <li>3: Relu6;
+     *      <li>4: Tanh;
+     *      <li>6: Sigmoid.
+     *      </ul>
+     * * 21:The clipping threshold (\f$t_{cell}\f$) for the cell state, such
+     *      that values are bound within [-cell_clip, cell_clip]. If set to 0.0
+     *      then clipping is disabled.
+     * * 22:The clipping threshold (\f$t_{proj}\f$) for the output from the
+     *      projection layer, such that values are bound within
+     *      [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     * * 23:Time-major if true, batch-major if false.
+     * * 24:The input layer normalization weights. Optional.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at input gate.
+     * * 25:The forget layer normalization weights. Optional.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at forget gate.
+     * * 26:The cell layer normalization weights. Optional.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at cell gate.
+     * * 27:The output layer normalization weights. Optional.
+     *      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
+     *      to activation at output gate.
+     *
+     * Outputs:
+     * * 0: The output (\f$o_t\f$).
+     *      A 3-D tensor of shape:
+     *        If time-major: [max_time, batch_size, output_size]
+     *        If batch-major: [batch_size, max_time, output_size]
+     * * 1: A tensor of shape [batch_size, output_size] containing a hidden
+     *      state from the last time step in the sequence. This output is
+     *      optional and can be omitted. If this output is present then
+     *      output #2 must be present as well.
+     *      Available since HAL version 1.3.
+     * * 2: A tensor of shape [batch_size, cell_size] containing a cell state
+     *      from the last time step in the sequence. This output is optional
+     *      and can be omitted.
+     *      Available since HAL version 1.3.
+     */
+    UNIDIRECTIONAL_SEQUENCE_LSTM = 92,
+    /**
+     * A recurrent neural network layer that applies a basic RNN cell to a
+     * sequence of inputs.
+     *
+     * This layer unrolls the input along the sequence dimension, and implements
+     * the following operation
+     * for each element in the sequence s = 1...sequence_length:
+     *   outputs[s] = state = activation(inputs[s] * input_weights’ + state *
+     *   recurrent_weights’ + bias)
+     *
+     * Where:
+     * * “input_weights” is a weight matrix that multiplies the inputs;
+     * * “recurrent_weights” is a weight matrix that multiplies the current
+     *    “state” which itself is the output from the previous time step
+     *    computation;
+     * * “bias” is a bias vector (added to each output vector in the batch);
+     * * “activation” is the function passed as the “fused_activation_function”
+     *   argument (if not “NONE”).
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * The input tensors must all be the same type.
+     *
+     * Inputs:
+     * * 0: input.
+     *      A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
+     *      it is set to 1, then the input has a shape [maxTime, batchSize,
+     *      inputSize], otherwise the input has a shape [batchSize, maxTime,
+     *      inputSize].
+     * * 1: weights.
+     *      A 2-D tensor of shape [numUnits, inputSize].
+     * * 2: recurrent_weights.
+     *      A 2-D tensor of shape [numUnits, numUnits].
+     * * 3: bias.
+     *      A 1-D tensor of shape [numUnits].
+     * * 4: hidden state
+     *      A 2-D tensor of shape [batchSize, numUnits]. Specifies a hidden
+     *      state input for the first time step of the computation.
+     * * 5: fusedActivationFunction.
+     *      A {@link FusedActivationFunc} value indicating the activation function. If
+     *      “NONE” is specified then it results in a linear activation.
+     * * 6: timeMajor
+     *      An {@link OperandType::INT32} scalar specifying the shape format
+     *      of input and output tensors. Must be set to either 0 or 1.
+     * Outputs:
+     * * 0: output.
+     *      A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
+     *      it is set to 1, then the output has a shape [maxTime, batchSize,
+     *      numUnits], otherwise the output has a shape [batchSize, maxTime,
+     *      numUnits].
+     * * 1: A tensor of shape [batchSize, numUnits] containing hidden state
+     *      from the last time step in the sequence. This output is optional
+     *      and can be omitted.
+     *      Available since HAL version 1.3.
+     */
+    UNIDIRECTIONAL_SEQUENCE_RNN = 93,
+    /**
+     * Resizes images to given size using the nearest neighbor interpretation.
+     *
+     * Resized images must be distorted if their output aspect ratio is not the
+     * same as input aspect ratio. The corner pixels of output may not be the
+     * same as corner pixels of input.
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)
+     *
+     * Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
+     * With the default data layout NHWC, the data is stored in the order of:
+     * [batch, height, width, channels]. Alternatively, the data layout could
+     * be NCHW, the data storage order of: [batch, channels, height, width].
+     *
+     * Both resizing by shape and resizing by scale are supported.
+     *
+     * Inputs (resizing by shape):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input. Zero batches is supported for this tensor.
+     * * 1: An {@link OperandType::INT32} scalar, specifying the output
+     *      width of the output tensor.
+     * * 2: An {@link OperandType::INT32} scalar, specifying the output
+     *      height of the output tensor.
+     * * 3: An {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     * * 4: Align corners. An optional {@link OperandType::BOOL}
+     *      scalar, default to false.  If True, the centers of the 4 corner
+     *      pixels of the input and output tensors are aligned, preserving the
+     *      values at the corner pixels.
+     *      Available since HAL version 1.3.
+     * * 5: Half pixel centers. An optional {@link OperandType::BOOL}
+     *      scalar, default to false. If True, the pixel centers are assumed to
+     *      be at (0.5, 0.5). This is the default behavior of image.resize in
+     *      TF 2.0. If this parameter is True, then align_corners parameter
+     *      must be False.
+     *      Available since HAL version 1.3.
+     *
+     * Inputs (resizing by scale):
+     * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
+     *      the input. Zero batches is supported for this tensor.
+     * * 1: A scalar, specifying width_scale, the scaling factor of the width
+     *      dimension from the input tensor to the output tensor. The output
+     *      width is calculated as new_width = floor(width * width_scale).
+     *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
+     *      of {@link OperandType::TENSOR_FLOAT16} and of
+     *      {@link OperandType::FLOAT32} otherwise.
+     * * 2: A scalar, specifying height_scale, the scaling factor of the height
+     *      dimension from the input tensor to the output tensor. The output
+     *      height is calculated as new_height = floor(height * height_scale).
+     *      The scalar must be of {@link OperandType::FLOAT16} if input0 is
+     *      of {@link OperandType::TENSOR_FLOAT16} and of
+     *      {@link OperandType::FLOAT32} otherwise.
+     * * 3: An {@link OperandType::BOOL} scalar, default to false.
+     *      Set to true to specify NCHW data layout for input0 and output0.
+     * * 4: Align corners. An optional {@link OperandType::BOOL}
+     *      scalar, default to false.  If True, the centers of the 4 corner
+     *      pixels of the input and output tensors are aligned, preserving the
+     *      values at the corner pixels.
+     *      Available since HAL version 1.3.
+     * * 5: Half pixel centers. An optional {@link OperandType::BOOL}
+     *      scalar, default to false. If True, the pixel centers are assumed to
+     *      be at (0.5, 0.5). This is the default behavior of image.resize in
+     *      TF 2.0. If this parameter is True, then align_corners parameter
+     *      must be False.
+     *      Available since HAL version 1.3.
+     *
+     * Outputs:
+     * * 0: The output 4-D tensor, of shape
+     *      [batches, new_height, new_width, depth].
+     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and
+     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,
+     *      the scale and zeroPoint must be the same as input0.
+     */
+    RESIZE_NEAREST_NEIGHBOR = 94,
+    /**
+     * Quantized version of {@link OperationType::LSTM}.
+     *
+     * The input and the output use asymmetric quantized types, while the rest
+     * use symmetric ones.
+     *
+     * Inputs:
+     * * 0: The input to the LSTM cell.
+     *      Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      Shape: [batchSize, inputSize]
+     * * 1: The input-to-input weights. Optional.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 2: The input-to-forget weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 3: The input-to-cell weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 4: The input-to-output weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 5: The recurrent-to-input weights. Optional.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 6: The recurrent-to-forget weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 7: The recurrent-to-cell weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 8: The recurrent-to-output weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 9: The cell-to-input weights (for peephole). Optional.
+     *      Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *      Shape: [numUnits]
+     * * 10: The cell-to-forget weights (for peephole). Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 11: The cell-to-output weights (for peephole). Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 12: The input gate bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Optional.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 13: The forget gate bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 14: The cell bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 15: The output gate bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 16: The projection weights. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *       Shape: [outputSize, numUnits]
+     * * 17: The projection bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Optional.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [outputSize]
+     * * 18: The output from the previous time step.
+     *       Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *       Shape: [batchSize, outputSize]
+     * * 19: The cell state from the previous time step.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [batchSize, numUnits]
+     * * 20: The input layer normalization weights. Used to rescale
+     *       normalized inputs to activation at input gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 21: The forget layer normalization weights. Used to
+     *       rescale normalized inputs to activation at forget gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 22: The cell layer normalization weights. Used to rescale
+     *       normalized inputs to activation at cell gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 23: The output layer normalization weights. Used to
+     *       rescale normalized inputs to activation at output gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 24: The cell clip. If provided the cell state is clipped
+     *       by this value prior to the cell output activation. Optional.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 25: The projection clip. If provided and projection is enabled,
+     *       this is used for clipping the projected values. Optional.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 26: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at input gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 27: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at forget gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 28: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at cell gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 29: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at output gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 30: The zero point of the hidden state, i.e. input to
+     *       projection.
+     *       Type: {@link OperandType::INT32}.
+     * * 31: The scale of the hidden state, i.e. input to
+     *       projection.
+     *       Type: {@link OperandType::FLOAT32}.
+     *
+     * Outputs:
+     * * 0: The output state (out).
+     *      Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      Shape: [batchSize, outputSize]
+     * * 1: The cell state (out).
+     *      Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *      Shape: [batchSize, numUnits]
+     * * 2: The output. This is effectively the same as the current
+     *      "output state (out)" value.
+     *      Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      Shape: [batchSize, outputSize]
+     */
+    QUANTIZED_LSTM = 95,
+    /**
+     * Executes one of the two referenced subgraphs as determined by a boolean
+     * value.
+     *
+     * The inputs and outputs of the two referenced subgraphs must agree with the
+     * signature of this operation. That is, if the operation has (3 + n) inputs
+     * and m outputs, both subgraphs must have n inputs and m outputs with the same
+     * types, ranks, dimensions, scales,
+     * zeroPoints, and extraParams as the corresponding operation
+     * inputs and outputs.
+     * All of the operands mentioned must have fully specified dimensions.
+     *
+     * Inputs:
+     * * 0: A value of type {@link OperandType::TENSOR_BOOL8} and shape [1]
+     *      that determines which of the two referenced subgraphs to execute.
+     *      The operand must have fully specified dimensions.
+     * * 1: A {@link OperandType::SUBGRAPH} reference to the subgraph to be
+     *      executed if the condition is true.
+     * * 2: A {@link OperandType::SUBGRAPH} reference to the subgraph to be
+     *      executed if the condition is false.
+     * * 3 ~ (n + 2): Inputs to be passed to the subgraph selected for execution.
+     *
+     * Outputs:
+     * * 0 ~ (m - 1): Outputs produced by the selected subgraph.
+     */
+    IF = 96,
+    /**
+     * Executes the body subgraph until the condition subgraph outputs false.
+     *
+     * The inputs to this operation are the condition subgraph, the body subgraph,
+     * and operand values for the first iteration of the loop. The values are
+     * implicitly split into three groups of input-output, state-only, and
+     * input-only values, as described below.
+     *
+     * The outputs of this operation are the final values of input-output
+     * operands.
+     *
+     * Both the condition and body subgraph receive (m + k + n) inputs.
+     * * The first m (m >= 1) inputs are input-output operands. For the first
+     *   iteration, these are initialized from the corresponding inputs of the
+     *   WHILE operation. In subsequent iterations, their values come from the
+     *   corresponding outputs of the body subgraph produced during the previous
+     *   iteration.
+     * * The next k (k >= 0) inputs are state-only operands. They are similar to
+     *   the input-output operands, except that their values are no longer
+     *   available after the loop terminates.
+     * * The last n (n >= 0) inputs are input-only operands. Their values come
+     *   from the corresponding inputs of the WHILE operation.
+     *
+     * The body subgraph produces (m + k) outputs.
+     * * The first m outputs are input-output operands. They become the outputs
+     *   of the WHILE operation when a termination condition is reached.
+     * * The last k outputs are state-only operands. Their values are no longer
+     *   available after the loop terminates.
+     *
+     * The numbers m, k, and n are inferred by the driver as follows:
+     *     m = (WHILE operation output count)
+     *     k = (body subgraph output count) - m
+     *     n = (body subgraph input count) - m - k
+     *
+     * The pseudo-code below illustrates the flow of a WHILE operation with
+     * inputs condition, body, initial_input_output, initial_state, input_only
+     * (m = 1, k = 1, n = 1):
+     *
+     *     input_output = initial_input_output
+     *     state = initial_state
+     *     while condition(input_output, state, input_only):
+     *         input_output, state = body(input_output, state, input_only)
+     *     return input_output
+     *
+     * Inputs:
+     * * 0: A {@link OperandType::SUBGRAPH} reference to the condition
+     *      subgraph. The subgraph must have (m + k + n) inputs with
+     *      the same types, ranks, dimensions,
+     *      scales, zeroPoints, and extraParams as the
+     *      corresponding inputs of the WHILE operation and exactly one output
+     *      of {@link OperandType::TENSOR_BOOL8} and shape [1].
+     *      All of the operands mentioned must have fully specified dimensions.
+     * * 1: A {@link OperandType::SUBGRAPH} reference to the body subgraph.
+     *      The subgraph must have (m + k + n) inputs and (m + k) outputs with
+     *      the same types, ranks, dimensions,
+     *      scales, zeroPoints, and extraParams as the
+     *      corresponding inputs and outputs of the WHILE operation.
+     *      All of the operands mentioned must have fully specified dimensions.
+     * * (m inputs): Initial values for input-output operands.
+     * * (k inputs): Initial values for state-only operands.
+     * * (n inputs): Values for input-only operands.
+     *
+     * Outputs:
+     * * 0 ~ (m - 1): Outputs produced by the loop.
+     */
+    WHILE = 97,
+    /**
+     * Computes exponential linear activation on the input tensor element-wise.
+     *
+     * The output is calculated using the following formula:
+     *
+     *     ELU(x) = max(0, x) + min(0, alpha * (exp(x) - 1))
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input. May be zero-sized.
+     * * 1: A scalar, specifying the alpha parameter.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT16},
+     *      the alpha value must be of {@link OperandType::FLOAT16}.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT32},
+     *      the alpha value must be of {@link OperandType::FLOAT32}.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape and type as input0.
+     */
+    ELU = 98,
+    /**
+     * Computes hard-swish activation on the input tensor element-wise.
+     *
+     * Hard swish activation is introduced in
+     * https://arxiv.org/pdf/1905.02244.pdf
+     *
+     * The output is calculated using the following formula:
+     *
+     *     h-swish(x) = x * max(0, min(6, (x + 3))) / 6
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input. May be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape and type as input0.
+     *      Scale and zero point of this tensor may be different from the input
+     *      tensor's parameters.
+     */
+    HARD_SWISH = 99,
+    /**
+     * Creates a tensor filled with a scalar value.
+     *
+     * Supported output tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: A 1-D tensor, specifying the desired output tensor shape.
+     * * 1: A scalar, specifying the value to fill the output tensors with.
+     *      For output tensor of {@link OperandType::TENSOR_FLOAT16},
+     *      the scalar must be of {@link OperandType::FLOAT16}.
+     *      For output tensor of {@link OperandType::TENSOR_FLOAT32},
+     *      the scalar must be of {@link OperandType::FLOAT32}.
+     *      For output tensor of {@link OperandType::TENSOR_INT32},
+     *      the scalar must be of {@link OperandType::INT32}.
+     *
+     * Outputs:
+     * * 0: The output tensor.
+     */
+    FILL = 100,
+    /**
+     * Returns the rank of a tensor.
+     *
+     * The rank of a tensor is the number of dimensions in it. Also known as
+     * "order", "degree", "ndims".
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT16_SYMM}
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
+     * * {@link OperandType::TENSOR_QUANT16_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_SYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *
+     * Supported tensor rank: from 1.
+     *
+     * Inputs:
+     * * 0: The input tensor.
+     *
+     * Outputs:
+     * * 0: A scalar of {@link OperandType::INT32}, specifying the rank
+     *      of the input tensor.
+     */
+    RANK = 101,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/OutputShape.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/OutputShape.aidl
new file mode 100644
index 0000000..f90a613
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/OutputShape.aidl
@@ -0,0 +1,32 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Describes the shape information of an output operand after execution.
+ */
+@VintfStability
+parcelable OutputShape {
+    /**
+     * Dimensions of the operand.
+     */
+    int[] dimensions;
+    /**
+     * Whether the provided buffer size is sufficient for the output.
+     */
+    boolean isSufficient;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/PerformanceInfo.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/PerformanceInfo.aidl
new file mode 100644
index 0000000..6915c67
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/PerformanceInfo.aidl
@@ -0,0 +1,36 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Performance information for the reference workload.
+ *
+ * Used by a driver to report its performance characteristics.
+ */
+@VintfStability
+parcelable PerformanceInfo {
+    /**
+     * Ratio of the time taken by the driver to execute the workload compared to the time the CPU
+     * would take for the same workload. A lower number is better.
+     */
+    float execTime;
+    /**
+     * Ratio of the energy used by the driver compared to what the CPU would use for doing the same
+     * workload. A lower number is better.
+     */
+    float powerUsage;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Priority.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Priority.aidl
new file mode 100644
index 0000000..7dbf8e9
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Priority.aidl
@@ -0,0 +1,28 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Priority given to a prepared model for execution.
+ */
+@VintfStability
+@Backing(type="int")
+enum Priority {
+    LOW,
+    MEDIUM,
+    HIGH,
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Request.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Request.aidl
new file mode 100644
index 0000000..dc138ba
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Request.aidl
@@ -0,0 +1,54 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.RequestArgument;
+import android.hardware.neuralnetworks.RequestMemoryPool;
+
+/**
+ * Inputs to be sent to and outputs to be retrieved from a prepared model.
+ *
+ * A Request serves two primary tasks:
+ * 1) Provides the input and output data to be used when executing the model.
+ * 2) Specifies any updates to the input operand metadata that were left unspecified at model
+ *    preparation time.
+ *
+ * An output must not overlap with any other output, with an input, or with an operand of lifetime
+ * CONSTANT_POOL.
+ */
+@VintfStability
+parcelable Request {
+    /**
+     * Input data and information to be used in the execution of a prepared model.
+     *
+     * The index of the input corresponds to the index in Model.main.inputIndexes.
+     *   E.g., input[i] corresponds to Model.main.inputIndexes[i].
+     */
+    RequestArgument[] inputs;
+    /**
+     * Output data and information to be used in the execution of a prepared model.
+     *
+     * The index of the output corresponds to the index in Model.main.outputIndexes.
+     *   E.g., output[i] corresponds to Model.main.outputIndexes[i].
+     */
+    RequestArgument[] outputs;
+    /**
+     * A collection of memory pools containing operand data for both the inputs and the outputs to a
+     * model.
+     */
+    RequestMemoryPool[] pools;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/RequestArgument.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/RequestArgument.aidl
new file mode 100644
index 0000000..8dc9252
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/RequestArgument.aidl
@@ -0,0 +1,52 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.DataLocation;
+
+/**
+ * Metadata information specifying the location of the input or output data and any updates to the
+ * input or output operand.
+ */
+@VintfStability
+parcelable RequestArgument {
+    /**
+     * If true, the argument does not have a value. This can be used for operations that take
+     * optional arguments. If true, the fields of location are set to 0 and the dimensions vector is
+     * left empty.
+     */
+    boolean hasNoValue;
+    /**
+     * The location within one of the memory pools passed in the Request.
+     */
+    DataLocation location;
+    /**
+     * Updated dimension information.
+     *
+     * If dimensions.size() > 0, dimension information was provided along with the argument. This
+     * can be the case for models that accept inputs of varying size. This can't change the rank,
+     * just the value of the dimensions that were unspecified in the model. If dimensions.size() >
+     * 0, then all dimensions must be specified here; and any dimension that was specified in the
+     * model must have the same value here.
+     *
+     * If the dimensions in the model are not fully specified, then they must be fully specified
+     * here, unless hasNoValue is set to true. If the dimensions in the model are fully specified,
+     * then either dimensions.size() may be 0, or the dimensions in the model must be identical to
+     * the dimensions here.
+     */
+    int[] dimensions;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/RequestMemoryPool.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/RequestMemoryPool.aidl
new file mode 100644
index 0000000..faca2fe
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/RequestMemoryPool.aidl
@@ -0,0 +1,35 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.Memory;
+
+/**
+ * A memory pool.
+ */
+@VintfStability
+union RequestMemoryPool {
+    /**
+     * Specifies a client-managed shared memory pool.
+     */
+    Memory pool;
+    /**
+     * Specifies a driver-managed buffer. It is the token returned from IDevice::allocate, and is
+     * specific to the IDevice object.
+     */
+    int token;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Subgraph.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Subgraph.aidl
new file mode 100644
index 0000000..2e9c450
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Subgraph.aidl
@@ -0,0 +1,50 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+import android.hardware.neuralnetworks.Operand;
+import android.hardware.neuralnetworks.Operation;
+
+/**
+ * An excerpt of the execution graph.
+ */
+@VintfStability
+parcelable Subgraph {
+    /**
+     * All operands included in the subgraph.
+     */
+    Operand[] operands;
+    /**
+     * All operations included in the subgraph.
+     *
+     * The operations are sorted into execution order. Every operand with lifetime SUBGRAPH_OUTPUT
+     * or TEMPORARY_VARIABLE must be written before it is read.
+     */
+    Operation[] operations;
+    /**
+     * Input indexes of the subgraph. There must be at least one.
+     *
+     * Each value corresponds to the index of the operand in "operands".
+     */
+    int[] inputIndexes;
+    /**
+     * Output indexes of the subgraph. There must be at least one.
+     *
+     * Each value corresponds to the index of the operand in "operands".
+     */
+    int[] outputIndexes;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/SymmPerChannelQuantParams.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/SymmPerChannelQuantParams.aidl
new file mode 100644
index 0000000..eb47df0
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/SymmPerChannelQuantParams.aidl
@@ -0,0 +1,32 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Parameters for TENSOR_QUANT8_SYMM_PER_CHANNEL operand.
+ */
+@VintfStability
+parcelable SymmPerChannelQuantParams {
+    /**
+     * Array of scaling values for each channel. Each value must be greater than zero.
+     */
+    float[] scales;
+    /**
+     * Index of the channel dimension
+     */
+    int channelDim;
+}
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/Timing.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/Timing.aidl
new file mode 100644
index 0000000..8130e08
--- /dev/null
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/Timing.aidl
@@ -0,0 +1,36 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks;
+
+/**
+ * Timing information measured during execution. Each time is a duration from the beginning of some
+ * task to the end of that task, including time when that task is not active (for example, preempted
+ * by some other task, or waiting for some resource to become available).
+ *
+ * Times are measured in nanoseconds. When a time is not available, it must be reported as -1.
+ */
+@VintfStability
+parcelable Timing {
+    /**
+     * Execution time on device (not driver, which runs on host processor).
+     */
+    long timeOnDevice;
+    /**
+     * Execution time in driver (including time on device).
+     */
+    long timeInDriver;
+}
diff --git a/neuralnetworks/aidl/utils/Android.bp b/neuralnetworks/aidl/utils/Android.bp
new file mode 100644
index 0000000..56017da
--- /dev/null
+++ b/neuralnetworks/aidl/utils/Android.bp
@@ -0,0 +1,32 @@
+//
+// Copyright (C) 2021 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_library_static {
+    name: "neuralnetworks_utils_hal_aidl",
+    defaults: ["neuralnetworks_utils_defaults"],
+    srcs: ["src/*"],
+    local_include_dirs: ["include/nnapi/hal/aidl/"],
+    export_include_dirs: ["include"],
+    static_libs: [
+        "neuralnetworks_types",
+        "neuralnetworks_utils_hal_common",
+    ],
+    shared_libs: [
+        "libhidlbase",
+        "android.hardware.neuralnetworks-V1-ndk_platform",
+        "libbinder_ndk",
+    ],
+}
diff --git a/neuralnetworks/aidl/utils/OWNERS b/neuralnetworks/aidl/utils/OWNERS
new file mode 100644
index 0000000..e4feee3
--- /dev/null
+++ b/neuralnetworks/aidl/utils/OWNERS
@@ -0,0 +1,11 @@
+# Neuralnetworks team
+butlermichael@google.com
+dgross@google.com
+galarragas@google.com
+jeanluc@google.com
+levp@google.com
+miaowang@google.com
+pszczepaniak@google.com
+slavash@google.com
+vddang@google.com
+xusongw@google.com
diff --git a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h
new file mode 100644
index 0000000..35de5be
--- /dev/null
+++ b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h
@@ -0,0 +1,134 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_CONVERSIONS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_CONVERSIONS_H
+
+#include <aidl/android/hardware/neuralnetworks/BufferDesc.h>
+#include <aidl/android/hardware/neuralnetworks/BufferRole.h>
+#include <aidl/android/hardware/neuralnetworks/Capabilities.h>
+#include <aidl/android/hardware/neuralnetworks/DataLocation.h>
+#include <aidl/android/hardware/neuralnetworks/DeviceType.h>
+#include <aidl/android/hardware/neuralnetworks/ErrorStatus.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionPreference.h>
+#include <aidl/android/hardware/neuralnetworks/Extension.h>
+#include <aidl/android/hardware/neuralnetworks/ExtensionNameAndPrefix.h>
+#include <aidl/android/hardware/neuralnetworks/ExtensionOperandTypeInformation.h>
+#include <aidl/android/hardware/neuralnetworks/Memory.h>
+#include <aidl/android/hardware/neuralnetworks/Model.h>
+#include <aidl/android/hardware/neuralnetworks/Operand.h>
+#include <aidl/android/hardware/neuralnetworks/OperandExtraParams.h>
+#include <aidl/android/hardware/neuralnetworks/OperandLifeTime.h>
+#include <aidl/android/hardware/neuralnetworks/OperandPerformance.h>
+#include <aidl/android/hardware/neuralnetworks/OperandType.h>
+#include <aidl/android/hardware/neuralnetworks/Operation.h>
+#include <aidl/android/hardware/neuralnetworks/OperationType.h>
+#include <aidl/android/hardware/neuralnetworks/OutputShape.h>
+#include <aidl/android/hardware/neuralnetworks/PerformanceInfo.h>
+#include <aidl/android/hardware/neuralnetworks/Priority.h>
+#include <aidl/android/hardware/neuralnetworks/Request.h>
+#include <aidl/android/hardware/neuralnetworks/RequestArgument.h>
+#include <aidl/android/hardware/neuralnetworks/RequestMemoryPool.h>
+#include <aidl/android/hardware/neuralnetworks/Subgraph.h>
+#include <aidl/android/hardware/neuralnetworks/SymmPerChannelQuantParams.h>
+#include <aidl/android/hardware/neuralnetworks/Timing.h>
+
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+
+#include <vector>
+
+namespace android::nn {
+
+GeneralResult<OperandType> unvalidatedConvert(const aidl_hal::OperandType& operandType);
+GeneralResult<OperationType> unvalidatedConvert(const aidl_hal::OperationType& operationType);
+GeneralResult<DeviceType> unvalidatedConvert(const aidl_hal::DeviceType& deviceType);
+GeneralResult<Priority> unvalidatedConvert(const aidl_hal::Priority& priority);
+GeneralResult<Capabilities> unvalidatedConvert(const aidl_hal::Capabilities& capabilities);
+GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
+        const aidl_hal::OperandPerformance& operandPerformance);
+GeneralResult<Capabilities::PerformanceInfo> unvalidatedConvert(
+        const aidl_hal::PerformanceInfo& performanceInfo);
+GeneralResult<DataLocation> unvalidatedConvert(const aidl_hal::DataLocation& location);
+GeneralResult<Operand> unvalidatedConvert(const aidl_hal::Operand& operand);
+GeneralResult<Operand::ExtraParams> unvalidatedConvert(
+        const std::optional<aidl_hal::OperandExtraParams>& optionalExtraParams);
+GeneralResult<Operand::LifeTime> unvalidatedConvert(
+        const aidl_hal::OperandLifeTime& operandLifeTime);
+GeneralResult<Operand::SymmPerChannelQuantParams> unvalidatedConvert(
+        const aidl_hal::SymmPerChannelQuantParams& symmPerChannelQuantParams);
+GeneralResult<Operation> unvalidatedConvert(const aidl_hal::Operation& operation);
+GeneralResult<Model> unvalidatedConvert(const aidl_hal::Model& model);
+GeneralResult<Model::ExtensionNameAndPrefix> unvalidatedConvert(
+        const aidl_hal::ExtensionNameAndPrefix& extensionNameAndPrefix);
+GeneralResult<Model::OperandValues> unvalidatedConvert(const std::vector<uint8_t>& operandValues);
+GeneralResult<Model::Subgraph> unvalidatedConvert(const aidl_hal::Subgraph& subgraph);
+GeneralResult<OutputShape> unvalidatedConvert(const aidl_hal::OutputShape& outputShape);
+GeneralResult<MeasureTiming> unvalidatedConvert(bool measureTiming);
+GeneralResult<Memory> unvalidatedConvert(const aidl_hal::Memory& memory);
+GeneralResult<Timing> unvalidatedConvert(const aidl_hal::Timing& timing);
+GeneralResult<BufferDesc> unvalidatedConvert(const aidl_hal::BufferDesc& bufferDesc);
+GeneralResult<BufferRole> unvalidatedConvert(const aidl_hal::BufferRole& bufferRole);
+GeneralResult<Request> unvalidatedConvert(const aidl_hal::Request& request);
+GeneralResult<Request::Argument> unvalidatedConvert(
+        const aidl_hal::RequestArgument& requestArgument);
+GeneralResult<Request::MemoryPool> unvalidatedConvert(
+        const aidl_hal::RequestMemoryPool& memoryPool);
+GeneralResult<ErrorStatus> unvalidatedConvert(const aidl_hal::ErrorStatus& errorStatus);
+GeneralResult<ExecutionPreference> unvalidatedConvert(
+        const aidl_hal::ExecutionPreference& executionPreference);
+GeneralResult<Extension> unvalidatedConvert(const aidl_hal::Extension& extension);
+GeneralResult<Extension::OperandTypeInformation> unvalidatedConvert(
+        const aidl_hal::ExtensionOperandTypeInformation& operandTypeInformation);
+GeneralResult<SharedHandle> unvalidatedConvert(
+        const ::aidl::android::hardware::common::NativeHandle& handle);
+
+GeneralResult<ExecutionPreference> convert(
+        const aidl_hal::ExecutionPreference& executionPreference);
+GeneralResult<Memory> convert(const aidl_hal::Memory& memory);
+GeneralResult<Model> convert(const aidl_hal::Model& model);
+GeneralResult<Operand> convert(const aidl_hal::Operand& operand);
+GeneralResult<OperandType> convert(const aidl_hal::OperandType& operandType);
+GeneralResult<Priority> convert(const aidl_hal::Priority& priority);
+GeneralResult<Request::MemoryPool> convert(const aidl_hal::RequestMemoryPool& memoryPool);
+GeneralResult<Request> convert(const aidl_hal::Request& request);
+
+GeneralResult<std::vector<Operation>> convert(const std::vector<aidl_hal::Operation>& outputShapes);
+GeneralResult<std::vector<Memory>> convert(const std::vector<aidl_hal::Memory>& memories);
+
+GeneralResult<std::vector<uint32_t>> toUnsigned(const std::vector<int32_t>& vec);
+
+}  // namespace android::nn
+
+namespace aidl::android::hardware::neuralnetworks::utils {
+
+namespace nn = ::android::nn;
+
+nn::GeneralResult<Memory> unvalidatedConvert(const nn::Memory& memory);
+nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape);
+nn::GeneralResult<ErrorStatus> unvalidatedConvert(const nn::ErrorStatus& errorStatus);
+
+nn::GeneralResult<Memory> convert(const nn::Memory& memory);
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
+nn::GeneralResult<std::vector<OutputShape>> convert(
+        const std::vector<nn::OutputShape>& outputShapes);
+
+nn::GeneralResult<std::vector<int32_t>> toSigned(const std::vector<uint32_t>& vec);
+
+}  // namespace aidl::android::hardware::neuralnetworks::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_CONVERSIONS_H
diff --git a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Utils.h b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Utils.h
new file mode 100644
index 0000000..79b511d
--- /dev/null
+++ b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Utils.h
@@ -0,0 +1,57 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_UTILS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_UTILS_H
+
+#include "nnapi/hal/aidl/Conversions.h"
+
+#include <android-base/logging.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/Validation.h>
+
+namespace aidl::android::hardware::neuralnetworks::utils {
+
+constexpr auto kDefaultPriority = Priority::MEDIUM;
+constexpr auto kVersion = nn::Version::ANDROID_S;
+
+template <typename Type>
+nn::Result<void> validate(const Type& halObject) {
+    const auto maybeCanonical = nn::convert(halObject);
+    if (!maybeCanonical.has_value()) {
+        return nn::error() << maybeCanonical.error().message;
+    }
+    return {};
+}
+
+template <typename Type>
+bool valid(const Type& halObject) {
+    const auto result = utils::validate(halObject);
+    if (!result.has_value()) {
+        LOG(ERROR) << result.error();
+    }
+    return result.has_value();
+}
+
+nn::GeneralResult<Memory> clone(const Memory& memory);
+nn::GeneralResult<Request> clone(const Request& request);
+nn::GeneralResult<RequestMemoryPool> clone(const RequestMemoryPool& requestPool);
+nn::GeneralResult<Model> clone(const Model& model);
+
+}  // namespace aidl::android::hardware::neuralnetworks::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_UTILS_H
diff --git a/neuralnetworks/aidl/utils/src/Assertions.cpp b/neuralnetworks/aidl/utils/src/Assertions.cpp
new file mode 100644
index 0000000..0e88091
--- /dev/null
+++ b/neuralnetworks/aidl/utils/src/Assertions.cpp
@@ -0,0 +1,269 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <aidl/android/hardware/neuralnetworks/DeviceType.h>
+#include <aidl/android/hardware/neuralnetworks/ErrorStatus.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionPreference.h>
+#include <aidl/android/hardware/neuralnetworks/FusedActivationFunc.h>
+#include <aidl/android/hardware/neuralnetworks/IDevice.h>
+#include <aidl/android/hardware/neuralnetworks/OperandLifeTime.h>
+#include <aidl/android/hardware/neuralnetworks/OperandType.h>
+#include <aidl/android/hardware/neuralnetworks/OperationType.h>
+#include <aidl/android/hardware/neuralnetworks/Priority.h>
+
+#include <ControlFlow.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/OperationTypes.h>
+#include <nnapi/Types.h>
+#include <type_traits>
+
+namespace {
+
+#define COMPARE_ENUMS_TYPES(lhsType, rhsType)                                                   \
+    static_assert(                                                                              \
+            std::is_same_v<                                                                     \
+                    std::underlying_type_t<::aidl::android::hardware::neuralnetworks::lhsType>, \
+                    std::underlying_type_t<::android::nn::rhsType>>,                            \
+            "::aidl::android::hardware::neuralnetworks::" #lhsType                              \
+            " does not have the same underlying type as ::android::nn::" #rhsType)
+
+COMPARE_ENUMS_TYPES(OperandType, OperandType);
+COMPARE_ENUMS_TYPES(OperationType, OperationType);
+COMPARE_ENUMS_TYPES(Priority, Priority);
+COMPARE_ENUMS_TYPES(OperandLifeTime, Operand::LifeTime);
+COMPARE_ENUMS_TYPES(ErrorStatus, ErrorStatus);
+
+#undef COMPARE_ENUMS_TYPES
+
+#define COMPARE_ENUMS_FULL(lhsSymbol, rhsSymbol, lhsType, rhsType)                               \
+    static_assert(                                                                               \
+            static_cast<                                                                         \
+                    std::underlying_type_t<::aidl::android::hardware::neuralnetworks::lhsType>>( \
+                    ::aidl::android::hardware::neuralnetworks::lhsType::lhsSymbol) ==            \
+                    static_cast<std::underlying_type_t<::android::nn::rhsType>>(                 \
+                            ::android::nn::rhsType::rhsSymbol),                                  \
+            "::aidl::android::hardware::neuralnetworks::" #lhsType "::" #lhsSymbol               \
+            " does not match ::android::nn::" #rhsType "::" #rhsSymbol)
+
+#define COMPARE_ENUMS(symbol) COMPARE_ENUMS_FULL(symbol, symbol, OperandType, OperandType)
+
+COMPARE_ENUMS(FLOAT32);
+COMPARE_ENUMS(INT32);
+COMPARE_ENUMS(UINT32);
+COMPARE_ENUMS(TENSOR_FLOAT32);
+COMPARE_ENUMS(TENSOR_INT32);
+COMPARE_ENUMS(TENSOR_QUANT8_ASYMM);
+COMPARE_ENUMS(BOOL);
+COMPARE_ENUMS(TENSOR_QUANT16_SYMM);
+COMPARE_ENUMS(TENSOR_FLOAT16);
+COMPARE_ENUMS(TENSOR_BOOL8);
+COMPARE_ENUMS(FLOAT16);
+COMPARE_ENUMS(TENSOR_QUANT8_SYMM_PER_CHANNEL);
+COMPARE_ENUMS(TENSOR_QUANT16_ASYMM);
+COMPARE_ENUMS(TENSOR_QUANT8_SYMM);
+COMPARE_ENUMS(TENSOR_QUANT8_ASYMM_SIGNED);
+COMPARE_ENUMS(SUBGRAPH);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(symbol) COMPARE_ENUMS_FULL(symbol, symbol, OperationType, OperationType)
+
+COMPARE_ENUMS(ADD);
+COMPARE_ENUMS(AVERAGE_POOL_2D);
+COMPARE_ENUMS(CONCATENATION);
+COMPARE_ENUMS(CONV_2D);
+COMPARE_ENUMS(DEPTHWISE_CONV_2D);
+COMPARE_ENUMS(DEPTH_TO_SPACE);
+COMPARE_ENUMS(DEQUANTIZE);
+COMPARE_ENUMS(EMBEDDING_LOOKUP);
+COMPARE_ENUMS(FLOOR);
+COMPARE_ENUMS(FULLY_CONNECTED);
+COMPARE_ENUMS(HASHTABLE_LOOKUP);
+COMPARE_ENUMS(L2_NORMALIZATION);
+COMPARE_ENUMS(L2_POOL_2D);
+COMPARE_ENUMS(LOCAL_RESPONSE_NORMALIZATION);
+COMPARE_ENUMS(LOGISTIC);
+COMPARE_ENUMS(LSH_PROJECTION);
+COMPARE_ENUMS(LSTM);
+COMPARE_ENUMS(MAX_POOL_2D);
+COMPARE_ENUMS(MUL);
+COMPARE_ENUMS(RELU);
+COMPARE_ENUMS(RELU1);
+COMPARE_ENUMS(RELU6);
+COMPARE_ENUMS(RESHAPE);
+COMPARE_ENUMS(RESIZE_BILINEAR);
+COMPARE_ENUMS(RNN);
+COMPARE_ENUMS(SOFTMAX);
+COMPARE_ENUMS(SPACE_TO_DEPTH);
+COMPARE_ENUMS(SVDF);
+COMPARE_ENUMS(TANH);
+COMPARE_ENUMS(BATCH_TO_SPACE_ND);
+COMPARE_ENUMS(DIV);
+COMPARE_ENUMS(MEAN);
+COMPARE_ENUMS(PAD);
+COMPARE_ENUMS(SPACE_TO_BATCH_ND);
+COMPARE_ENUMS(SQUEEZE);
+COMPARE_ENUMS(STRIDED_SLICE);
+COMPARE_ENUMS(SUB);
+COMPARE_ENUMS(TRANSPOSE);
+COMPARE_ENUMS(ABS);
+COMPARE_ENUMS(ARGMAX);
+COMPARE_ENUMS(ARGMIN);
+COMPARE_ENUMS(AXIS_ALIGNED_BBOX_TRANSFORM);
+COMPARE_ENUMS(BIDIRECTIONAL_SEQUENCE_LSTM);
+COMPARE_ENUMS(BIDIRECTIONAL_SEQUENCE_RNN);
+COMPARE_ENUMS(BOX_WITH_NMS_LIMIT);
+COMPARE_ENUMS(CAST);
+COMPARE_ENUMS(CHANNEL_SHUFFLE);
+COMPARE_ENUMS(DETECTION_POSTPROCESSING);
+COMPARE_ENUMS(EQUAL);
+COMPARE_ENUMS(EXP);
+COMPARE_ENUMS(EXPAND_DIMS);
+COMPARE_ENUMS(GATHER);
+COMPARE_ENUMS(GENERATE_PROPOSALS);
+COMPARE_ENUMS(GREATER);
+COMPARE_ENUMS(GREATER_EQUAL);
+COMPARE_ENUMS(GROUPED_CONV_2D);
+COMPARE_ENUMS(HEATMAP_MAX_KEYPOINT);
+COMPARE_ENUMS(INSTANCE_NORMALIZATION);
+COMPARE_ENUMS(LESS);
+COMPARE_ENUMS(LESS_EQUAL);
+COMPARE_ENUMS(LOG);
+COMPARE_ENUMS(LOGICAL_AND);
+COMPARE_ENUMS(LOGICAL_NOT);
+COMPARE_ENUMS(LOGICAL_OR);
+COMPARE_ENUMS(LOG_SOFTMAX);
+COMPARE_ENUMS(MAXIMUM);
+COMPARE_ENUMS(MINIMUM);
+COMPARE_ENUMS(NEG);
+COMPARE_ENUMS(NOT_EQUAL);
+COMPARE_ENUMS(PAD_V2);
+COMPARE_ENUMS(POW);
+COMPARE_ENUMS(PRELU);
+COMPARE_ENUMS(QUANTIZE);
+COMPARE_ENUMS(QUANTIZED_16BIT_LSTM);
+COMPARE_ENUMS(RANDOM_MULTINOMIAL);
+COMPARE_ENUMS(REDUCE_ALL);
+COMPARE_ENUMS(REDUCE_ANY);
+COMPARE_ENUMS(REDUCE_MAX);
+COMPARE_ENUMS(REDUCE_MIN);
+COMPARE_ENUMS(REDUCE_PROD);
+COMPARE_ENUMS(REDUCE_SUM);
+COMPARE_ENUMS(ROI_ALIGN);
+COMPARE_ENUMS(ROI_POOLING);
+COMPARE_ENUMS(RSQRT);
+COMPARE_ENUMS(SELECT);
+COMPARE_ENUMS(SIN);
+COMPARE_ENUMS(SLICE);
+COMPARE_ENUMS(SPLIT);
+COMPARE_ENUMS(SQRT);
+COMPARE_ENUMS(TILE);
+COMPARE_ENUMS(TOPK_V2);
+COMPARE_ENUMS(TRANSPOSE_CONV_2D);
+COMPARE_ENUMS(UNIDIRECTIONAL_SEQUENCE_LSTM);
+COMPARE_ENUMS(UNIDIRECTIONAL_SEQUENCE_RNN);
+COMPARE_ENUMS(RESIZE_NEAREST_NEIGHBOR);
+COMPARE_ENUMS(QUANTIZED_LSTM);
+COMPARE_ENUMS(IF);
+COMPARE_ENUMS(WHILE);
+COMPARE_ENUMS(ELU);
+COMPARE_ENUMS(HARD_SWISH);
+COMPARE_ENUMS(FILL);
+COMPARE_ENUMS(RANK);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(symbol) COMPARE_ENUMS_FULL(symbol, symbol, Priority, Priority)
+
+COMPARE_ENUMS(LOW);
+COMPARE_ENUMS(MEDIUM);
+COMPARE_ENUMS(HIGH);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(lhsSymbol, rhsSymbol) \
+    COMPARE_ENUMS_FULL(lhsSymbol, rhsSymbol, OperandLifeTime, Operand::LifeTime)
+
+COMPARE_ENUMS(TEMPORARY_VARIABLE, TEMPORARY_VARIABLE);
+COMPARE_ENUMS(SUBGRAPH_INPUT, SUBGRAPH_INPUT);
+COMPARE_ENUMS(SUBGRAPH_OUTPUT, SUBGRAPH_OUTPUT);
+COMPARE_ENUMS(CONSTANT_COPY, CONSTANT_COPY);
+COMPARE_ENUMS(CONSTANT_POOL, CONSTANT_REFERENCE);
+COMPARE_ENUMS(NO_VALUE, NO_VALUE);
+COMPARE_ENUMS(SUBGRAPH, SUBGRAPH);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(symbol) COMPARE_ENUMS_FULL(symbol, symbol, ErrorStatus, ErrorStatus)
+
+COMPARE_ENUMS(NONE);
+COMPARE_ENUMS(DEVICE_UNAVAILABLE);
+COMPARE_ENUMS(GENERAL_FAILURE);
+COMPARE_ENUMS(OUTPUT_INSUFFICIENT_SIZE);
+COMPARE_ENUMS(INVALID_ARGUMENT);
+COMPARE_ENUMS(MISSED_DEADLINE_TRANSIENT);
+COMPARE_ENUMS(MISSED_DEADLINE_PERSISTENT);
+COMPARE_ENUMS(RESOURCE_EXHAUSTED_TRANSIENT);
+COMPARE_ENUMS(RESOURCE_EXHAUSTED_PERSISTENT);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(symbol) \
+    COMPARE_ENUMS_FULL(symbol, symbol, ExecutionPreference, ExecutionPreference)
+
+COMPARE_ENUMS(LOW_POWER);
+COMPARE_ENUMS(FAST_SINGLE_ANSWER);
+COMPARE_ENUMS(SUSTAINED_SPEED);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(symbol) COMPARE_ENUMS_FULL(symbol, symbol, DeviceType, DeviceType)
+
+COMPARE_ENUMS(OTHER);
+COMPARE_ENUMS(CPU);
+COMPARE_ENUMS(GPU);
+COMPARE_ENUMS(ACCELERATOR);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(symbol) \
+    COMPARE_ENUMS_FULL(symbol, symbol, FusedActivationFunc, FusedActivationFunc)
+
+COMPARE_ENUMS(NONE);
+COMPARE_ENUMS(RELU);
+COMPARE_ENUMS(RELU1);
+COMPARE_ENUMS(RELU6);
+
+#undef COMPARE_ENUMS
+
+#undef COMPARE_ENUMS_FULL
+
+#define COMPARE_CONSTANTS(halSymbol, canonicalSymbol)                     \
+    static_assert(::aidl::android::hardware::neuralnetworks::halSymbol == \
+                  ::android::nn::canonicalSymbol);
+
+COMPARE_CONSTANTS(IDevice::BYTE_SIZE_OF_CACHE_TOKEN, kByteSizeOfCacheToken);
+COMPARE_CONSTANTS(IDevice::MAX_NUMBER_OF_CACHE_FILES, kMaxNumberOfCacheFiles);
+COMPARE_CONSTANTS(IDevice::EXTENSION_TYPE_HIGH_BITS_PREFIX, kExtensionPrefixBits - 1);
+COMPARE_CONSTANTS(IDevice::EXTENSION_TYPE_LOW_BITS_TYPE, kExtensionTypeBits);
+COMPARE_CONSTANTS(IPreparedModel::DEFAULT_LOOP_TIMEOUT_DURATION_NS,
+                  operation_while::kTimeoutNsDefault);
+COMPARE_CONSTANTS(IPreparedModel::MAXIMUM_LOOP_TIMEOUT_DURATION_NS,
+                  operation_while::kTimeoutNsMaximum);
+
+#undef COMPARE_CONSTANTS
+
+}  // anonymous namespace
diff --git a/neuralnetworks/aidl/utils/src/Conversions.cpp b/neuralnetworks/aidl/utils/src/Conversions.cpp
new file mode 100644
index 0000000..0e93b02
--- /dev/null
+++ b/neuralnetworks/aidl/utils/src/Conversions.cpp
@@ -0,0 +1,582 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Conversions.h"
+
+#include <aidl/android/hardware/common/NativeHandle.h>
+#include <android-base/logging.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/OperationTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/SharedMemory.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/Validation.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+
+#include <algorithm>
+#include <chrono>
+#include <functional>
+#include <iterator>
+#include <limits>
+#include <type_traits>
+#include <utility>
+
+#define VERIFY_NON_NEGATIVE(value) \
+    while (UNLIKELY(value < 0)) return NN_ERROR()
+
+namespace {
+
+template <typename Type>
+constexpr std::underlying_type_t<Type> underlyingType(Type value) {
+    return static_cast<std::underlying_type_t<Type>>(value);
+}
+
+constexpr auto kVersion = android::nn::Version::ANDROID_S;
+
+}  // namespace
+
+namespace android::nn {
+namespace {
+
+constexpr auto validOperandType(nn::OperandType operandType) {
+    switch (operandType) {
+        case nn::OperandType::FLOAT32:
+        case nn::OperandType::INT32:
+        case nn::OperandType::UINT32:
+        case nn::OperandType::TENSOR_FLOAT32:
+        case nn::OperandType::TENSOR_INT32:
+        case nn::OperandType::TENSOR_QUANT8_ASYMM:
+        case nn::OperandType::BOOL:
+        case nn::OperandType::TENSOR_QUANT16_SYMM:
+        case nn::OperandType::TENSOR_FLOAT16:
+        case nn::OperandType::TENSOR_BOOL8:
+        case nn::OperandType::FLOAT16:
+        case nn::OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
+        case nn::OperandType::TENSOR_QUANT16_ASYMM:
+        case nn::OperandType::TENSOR_QUANT8_SYMM:
+        case nn::OperandType::TENSOR_QUANT8_ASYMM_SIGNED:
+        case nn::OperandType::SUBGRAPH:
+            return true;
+        case nn::OperandType::OEM:
+        case nn::OperandType::TENSOR_OEM_BYTE:
+            return false;
+    }
+    return nn::isExtension(operandType);
+}
+
+template <typename Input>
+using UnvalidatedConvertOutput =
+        std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
+
+template <typename Type>
+GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvertVec(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> canonical;
+    canonical.reserve(arguments.size());
+    for (const auto& argument : arguments) {
+        canonical.push_back(NN_TRY(nn::unvalidatedConvert(argument)));
+    }
+    return canonical;
+}
+
+template <typename Type>
+GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvert(
+        const std::vector<Type>& arguments) {
+    return unvalidatedConvertVec(arguments);
+}
+
+template <typename Type>
+GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& halObject) {
+    auto canonical = NN_TRY(nn::unvalidatedConvert(halObject));
+    const auto maybeVersion = validate(canonical);
+    if (!maybeVersion.has_value()) {
+        return error() << maybeVersion.error();
+    }
+    const auto version = maybeVersion.value();
+    if (version > kVersion) {
+        return NN_ERROR() << "Insufficient version: " << version << " vs required " << kVersion;
+    }
+    return canonical;
+}
+
+template <typename Type>
+GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> canonical;
+    canonical.reserve(arguments.size());
+    for (const auto& argument : arguments) {
+        canonical.push_back(NN_TRY(validatedConvert(argument)));
+    }
+    return canonical;
+}
+
+}  // anonymous namespace
+
+GeneralResult<OperandType> unvalidatedConvert(const aidl_hal::OperandType& operandType) {
+    VERIFY_NON_NEGATIVE(underlyingType(operandType)) << "Negative operand types are not allowed.";
+    return static_cast<OperandType>(operandType);
+}
+
+GeneralResult<OperationType> unvalidatedConvert(const aidl_hal::OperationType& operationType) {
+    VERIFY_NON_NEGATIVE(underlyingType(operationType))
+            << "Negative operation types are not allowed.";
+    return static_cast<OperationType>(operationType);
+}
+
+GeneralResult<DeviceType> unvalidatedConvert(const aidl_hal::DeviceType& deviceType) {
+    return static_cast<DeviceType>(deviceType);
+}
+
+GeneralResult<Priority> unvalidatedConvert(const aidl_hal::Priority& priority) {
+    return static_cast<Priority>(priority);
+}
+
+GeneralResult<Capabilities> unvalidatedConvert(const aidl_hal::Capabilities& capabilities) {
+    const bool validOperandTypes = std::all_of(
+            capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
+            [](const aidl_hal::OperandPerformance& operandPerformance) {
+                const auto maybeType = unvalidatedConvert(operandPerformance.type);
+                return !maybeType.has_value() ? false : validOperandType(maybeType.value());
+            });
+    if (!validOperandTypes) {
+        return NN_ERROR() << "Invalid OperandType when unvalidatedConverting OperandPerformance in "
+                             "Capabilities";
+    }
+
+    auto operandPerformance = NN_TRY(unvalidatedConvert(capabilities.operandPerformance));
+    auto table = NN_TRY(hal::utils::makeGeneralFailure(
+            Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)),
+            nn::ErrorStatus::GENERAL_FAILURE));
+
+    return Capabilities{
+            .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
+                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
+            .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
+                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
+            .operandPerformance = std::move(table),
+            .ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance)),
+            .whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance)),
+    };
+}
+
+GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
+        const aidl_hal::OperandPerformance& operandPerformance) {
+    return Capabilities::OperandPerformance{
+            .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
+            .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
+    };
+}
+
+GeneralResult<Capabilities::PerformanceInfo> unvalidatedConvert(
+        const aidl_hal::PerformanceInfo& performanceInfo) {
+    return Capabilities::PerformanceInfo{
+            .execTime = performanceInfo.execTime,
+            .powerUsage = performanceInfo.powerUsage,
+    };
+}
+
+GeneralResult<DataLocation> unvalidatedConvert(const aidl_hal::DataLocation& location) {
+    VERIFY_NON_NEGATIVE(location.poolIndex) << "DataLocation: pool index must not be negative";
+    VERIFY_NON_NEGATIVE(location.offset) << "DataLocation: offset must not be negative";
+    VERIFY_NON_NEGATIVE(location.length) << "DataLocation: length must not be negative";
+    if (location.offset > std::numeric_limits<uint32_t>::max()) {
+        return NN_ERROR() << "DataLocation: offset must be <= std::numeric_limits<uint32_t>::max()";
+    }
+    if (location.length > std::numeric_limits<uint32_t>::max()) {
+        return NN_ERROR() << "DataLocation: length must be <= std::numeric_limits<uint32_t>::max()";
+    }
+    return DataLocation{
+            .poolIndex = static_cast<uint32_t>(location.poolIndex),
+            .offset = static_cast<uint32_t>(location.offset),
+            .length = static_cast<uint32_t>(location.length),
+    };
+}
+
+GeneralResult<Operation> unvalidatedConvert(const aidl_hal::Operation& operation) {
+    return Operation{
+            .type = NN_TRY(unvalidatedConvert(operation.type)),
+            .inputs = NN_TRY(toUnsigned(operation.inputs)),
+            .outputs = NN_TRY(toUnsigned(operation.outputs)),
+    };
+}
+
+GeneralResult<Operand::LifeTime> unvalidatedConvert(
+        const aidl_hal::OperandLifeTime& operandLifeTime) {
+    return static_cast<Operand::LifeTime>(operandLifeTime);
+}
+
+GeneralResult<Operand> unvalidatedConvert(const aidl_hal::Operand& operand) {
+    return Operand{
+            .type = NN_TRY(unvalidatedConvert(operand.type)),
+            .dimensions = NN_TRY(toUnsigned(operand.dimensions)),
+            .scale = operand.scale,
+            .zeroPoint = operand.zeroPoint,
+            .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),
+            .location = NN_TRY(unvalidatedConvert(operand.location)),
+            .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
+    };
+}
+
+GeneralResult<Operand::ExtraParams> unvalidatedConvert(
+        const std::optional<aidl_hal::OperandExtraParams>& optionalExtraParams) {
+    if (!optionalExtraParams.has_value()) {
+        return Operand::NoParams{};
+    }
+    const auto& extraParams = optionalExtraParams.value();
+    using Tag = aidl_hal::OperandExtraParams::Tag;
+    switch (extraParams.getTag()) {
+        case Tag::channelQuant:
+            return unvalidatedConvert(extraParams.get<Tag::channelQuant>());
+        case Tag::extension:
+            return extraParams.get<Tag::extension>();
+    }
+    return NN_ERROR() << "Unrecognized Operand::ExtraParams tag: "
+                      << underlyingType(extraParams.getTag());
+}
+
+GeneralResult<Operand::SymmPerChannelQuantParams> unvalidatedConvert(
+        const aidl_hal::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
+    VERIFY_NON_NEGATIVE(symmPerChannelQuantParams.channelDim)
+            << "Per-channel quantization channel dimension must not be negative.";
+    return Operand::SymmPerChannelQuantParams{
+            .scales = symmPerChannelQuantParams.scales,
+            .channelDim = static_cast<uint32_t>(symmPerChannelQuantParams.channelDim),
+    };
+}
+
+GeneralResult<Model> unvalidatedConvert(const aidl_hal::Model& model) {
+    return Model{
+            .main = NN_TRY(unvalidatedConvert(model.main)),
+            .referenced = NN_TRY(unvalidatedConvert(model.referenced)),
+            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
+            .pools = NN_TRY(unvalidatedConvert(model.pools)),
+            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
+            .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
+    };
+}
+
+GeneralResult<Model::Subgraph> unvalidatedConvert(const aidl_hal::Subgraph& subgraph) {
+    return Model::Subgraph{
+            .operands = NN_TRY(unvalidatedConvert(subgraph.operands)),
+            .operations = NN_TRY(unvalidatedConvert(subgraph.operations)),
+            .inputIndexes = NN_TRY(toUnsigned(subgraph.inputIndexes)),
+            .outputIndexes = NN_TRY(toUnsigned(subgraph.outputIndexes)),
+    };
+}
+
+GeneralResult<Model::ExtensionNameAndPrefix> unvalidatedConvert(
+        const aidl_hal::ExtensionNameAndPrefix& extensionNameAndPrefix) {
+    return Model::ExtensionNameAndPrefix{
+            .name = extensionNameAndPrefix.name,
+            .prefix = extensionNameAndPrefix.prefix,
+    };
+}
+
+GeneralResult<Extension> unvalidatedConvert(const aidl_hal::Extension& extension) {
+    return Extension{
+            .name = extension.name,
+            .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
+    };
+}
+
+GeneralResult<Extension::OperandTypeInformation> unvalidatedConvert(
+        const aidl_hal::ExtensionOperandTypeInformation& operandTypeInformation) {
+    VERIFY_NON_NEGATIVE(operandTypeInformation.byteSize)
+            << "Extension operand type byte size must not be negative";
+    return Extension::OperandTypeInformation{
+            .type = operandTypeInformation.type,
+            .isTensor = operandTypeInformation.isTensor,
+            .byteSize = static_cast<uint32_t>(operandTypeInformation.byteSize),
+    };
+}
+
+GeneralResult<OutputShape> unvalidatedConvert(const aidl_hal::OutputShape& outputShape) {
+    return OutputShape{
+            .dimensions = NN_TRY(toUnsigned(outputShape.dimensions)),
+            .isSufficient = outputShape.isSufficient,
+    };
+}
+
+GeneralResult<MeasureTiming> unvalidatedConvert(bool measureTiming) {
+    return measureTiming ? MeasureTiming::YES : MeasureTiming::NO;
+}
+
+GeneralResult<Memory> unvalidatedConvert(const aidl_hal::Memory& memory) {
+    VERIFY_NON_NEGATIVE(memory.size) << "Memory size must not be negative";
+    return Memory{
+            .handle = NN_TRY(unvalidatedConvert(memory.handle)),
+            .size = static_cast<uint32_t>(memory.size),
+            .name = memory.name,
+    };
+}
+
+GeneralResult<Model::OperandValues> unvalidatedConvert(const std::vector<uint8_t>& operandValues) {
+    return Model::OperandValues(operandValues.data(), operandValues.size());
+}
+
+GeneralResult<BufferDesc> unvalidatedConvert(const aidl_hal::BufferDesc& bufferDesc) {
+    return BufferDesc{.dimensions = NN_TRY(toUnsigned(bufferDesc.dimensions))};
+}
+
+GeneralResult<BufferRole> unvalidatedConvert(const aidl_hal::BufferRole& bufferRole) {
+    VERIFY_NON_NEGATIVE(bufferRole.modelIndex) << "BufferRole: modelIndex must not be negative";
+    VERIFY_NON_NEGATIVE(bufferRole.ioIndex) << "BufferRole: ioIndex must not be negative";
+    return BufferRole{
+            .modelIndex = static_cast<uint32_t>(bufferRole.modelIndex),
+            .ioIndex = static_cast<uint32_t>(bufferRole.ioIndex),
+            .frequency = bufferRole.frequency,
+    };
+}
+
+GeneralResult<Request> unvalidatedConvert(const aidl_hal::Request& request) {
+    return Request{
+            .inputs = NN_TRY(unvalidatedConvert(request.inputs)),
+            .outputs = NN_TRY(unvalidatedConvert(request.outputs)),
+            .pools = NN_TRY(unvalidatedConvert(request.pools)),
+    };
+}
+
+GeneralResult<Request::Argument> unvalidatedConvert(const aidl_hal::RequestArgument& argument) {
+    const auto lifetime = argument.hasNoValue ? Request::Argument::LifeTime::NO_VALUE
+                                              : Request::Argument::LifeTime::POOL;
+    return Request::Argument{
+            .lifetime = lifetime,
+            .location = NN_TRY(unvalidatedConvert(argument.location)),
+            .dimensions = NN_TRY(toUnsigned(argument.dimensions)),
+    };
+}
+
+GeneralResult<Request::MemoryPool> unvalidatedConvert(
+        const aidl_hal::RequestMemoryPool& memoryPool) {
+    using Tag = aidl_hal::RequestMemoryPool::Tag;
+    switch (memoryPool.getTag()) {
+        case Tag::pool:
+            return unvalidatedConvert(memoryPool.get<Tag::pool>());
+        case Tag::token: {
+            const auto token = memoryPool.get<Tag::token>();
+            VERIFY_NON_NEGATIVE(token) << "Memory pool token must not be negative";
+            return static_cast<Request::MemoryDomainToken>(token);
+        }
+    }
+    return NN_ERROR() << "Invalid Request::MemoryPool tag " << underlyingType(memoryPool.getTag());
+}
+
+GeneralResult<ErrorStatus> unvalidatedConvert(const aidl_hal::ErrorStatus& status) {
+    switch (status) {
+        case aidl_hal::ErrorStatus::NONE:
+        case aidl_hal::ErrorStatus::DEVICE_UNAVAILABLE:
+        case aidl_hal::ErrorStatus::GENERAL_FAILURE:
+        case aidl_hal::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE:
+        case aidl_hal::ErrorStatus::INVALID_ARGUMENT:
+        case aidl_hal::ErrorStatus::MISSED_DEADLINE_TRANSIENT:
+        case aidl_hal::ErrorStatus::MISSED_DEADLINE_PERSISTENT:
+        case aidl_hal::ErrorStatus::RESOURCE_EXHAUSTED_TRANSIENT:
+        case aidl_hal::ErrorStatus::RESOURCE_EXHAUSTED_PERSISTENT:
+            return static_cast<ErrorStatus>(status);
+    }
+    return NN_ERROR() << "Invalid ErrorStatus " << underlyingType(status);
+}
+
+GeneralResult<ExecutionPreference> unvalidatedConvert(
+        const aidl_hal::ExecutionPreference& executionPreference) {
+    return static_cast<ExecutionPreference>(executionPreference);
+}
+
+GeneralResult<SharedHandle> unvalidatedConvert(
+        const ::aidl::android::hardware::common::NativeHandle& aidlNativeHandle) {
+    std::vector<base::unique_fd> fds;
+    fds.reserve(aidlNativeHandle.fds.size());
+    for (const auto& fd : aidlNativeHandle.fds) {
+        int dupFd = dup(fd.get());
+        if (dupFd == -1) {
+            // TODO(b/120417090): is ANEURALNETWORKS_UNEXPECTED_NULL the correct error to return
+            // here?
+            return NN_ERROR() << "Failed to dup the fd";
+        }
+        fds.emplace_back(dupFd);
+    }
+
+    return std::make_shared<const Handle>(Handle{
+            .fds = std::move(fds),
+            .ints = aidlNativeHandle.ints,
+    });
+}
+
+GeneralResult<ExecutionPreference> convert(
+        const aidl_hal::ExecutionPreference& executionPreference) {
+    return validatedConvert(executionPreference);
+}
+
+GeneralResult<Memory> convert(const aidl_hal::Memory& operand) {
+    return validatedConvert(operand);
+}
+
+GeneralResult<Model> convert(const aidl_hal::Model& model) {
+    return validatedConvert(model);
+}
+
+GeneralResult<Operand> convert(const aidl_hal::Operand& operand) {
+    return unvalidatedConvert(operand);
+}
+
+GeneralResult<OperandType> convert(const aidl_hal::OperandType& operandType) {
+    return unvalidatedConvert(operandType);
+}
+
+GeneralResult<Priority> convert(const aidl_hal::Priority& priority) {
+    return validatedConvert(priority);
+}
+
+GeneralResult<Request::MemoryPool> convert(const aidl_hal::RequestMemoryPool& memoryPool) {
+    return unvalidatedConvert(memoryPool);
+}
+
+GeneralResult<Request> convert(const aidl_hal::Request& request) {
+    return validatedConvert(request);
+}
+
+GeneralResult<std::vector<Operation>> convert(const std::vector<aidl_hal::Operation>& operations) {
+    return unvalidatedConvert(operations);
+}
+
+GeneralResult<std::vector<Memory>> convert(const std::vector<aidl_hal::Memory>& memories) {
+    return validatedConvert(memories);
+}
+
+GeneralResult<std::vector<uint32_t>> toUnsigned(const std::vector<int32_t>& vec) {
+    if (!std::all_of(vec.begin(), vec.end(), [](int32_t v) { return v >= 0; })) {
+        return NN_ERROR() << "Negative value passed to conversion from signed to unsigned";
+    }
+    return std::vector<uint32_t>(vec.begin(), vec.end());
+}
+
+}  // namespace android::nn
+
+namespace aidl::android::hardware::neuralnetworks::utils {
+namespace {
+
+template <typename Input>
+using UnvalidatedConvertOutput =
+        std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
+
+template <typename Type>
+nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvertVec(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> halObject(arguments.size());
+    for (size_t i = 0; i < arguments.size(); ++i) {
+        halObject[i] = NN_TRY(unvalidatedConvert(arguments[i]));
+    }
+    return halObject;
+}
+
+template <typename Type>
+nn::GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& canonical) {
+    const auto maybeVersion = nn::validate(canonical);
+    if (!maybeVersion.has_value()) {
+        return nn::error() << maybeVersion.error();
+    }
+    const auto version = maybeVersion.value();
+    if (version > kVersion) {
+        return NN_ERROR() << "Insufficient version: " << version << " vs required " << kVersion;
+    }
+    return utils::unvalidatedConvert(canonical);
+}
+
+template <typename Type>
+nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> halObject(arguments.size());
+    for (size_t i = 0; i < arguments.size(); ++i) {
+        halObject[i] = NN_TRY(validatedConvert(arguments[i]));
+    }
+    return halObject;
+}
+
+}  // namespace
+
+nn::GeneralResult<common::NativeHandle> unvalidatedConvert(const nn::SharedHandle& sharedHandle) {
+    common::NativeHandle aidlNativeHandle;
+    aidlNativeHandle.fds.reserve(sharedHandle->fds.size());
+    for (const auto& fd : sharedHandle->fds) {
+        int dupFd = dup(fd.get());
+        if (dupFd == -1) {
+            // TODO(b/120417090): is ANEURALNETWORKS_UNEXPECTED_NULL the correct error to return
+            // here?
+            return NN_ERROR() << "Failed to dup the fd";
+        }
+        aidlNativeHandle.fds.emplace_back(dupFd);
+    }
+    aidlNativeHandle.ints = sharedHandle->ints;
+    return aidlNativeHandle;
+}
+
+nn::GeneralResult<Memory> unvalidatedConvert(const nn::Memory& memory) {
+    if (memory.size > std::numeric_limits<int64_t>::max()) {
+        return NN_ERROR() << "Memory size doesn't fit into int64_t.";
+    }
+    return Memory{
+            .handle = NN_TRY(unvalidatedConvert(memory.handle)),
+            .size = static_cast<int64_t>(memory.size),
+            .name = memory.name,
+    };
+}
+
+nn::GeneralResult<ErrorStatus> unvalidatedConvert(const nn::ErrorStatus& errorStatus) {
+    switch (errorStatus) {
+        case nn::ErrorStatus::NONE:
+        case nn::ErrorStatus::DEVICE_UNAVAILABLE:
+        case nn::ErrorStatus::GENERAL_FAILURE:
+        case nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE:
+        case nn::ErrorStatus::INVALID_ARGUMENT:
+        case nn::ErrorStatus::MISSED_DEADLINE_TRANSIENT:
+        case nn::ErrorStatus::MISSED_DEADLINE_PERSISTENT:
+        case nn::ErrorStatus::RESOURCE_EXHAUSTED_TRANSIENT:
+        case nn::ErrorStatus::RESOURCE_EXHAUSTED_PERSISTENT:
+            return static_cast<ErrorStatus>(errorStatus);
+        default:
+            return ErrorStatus::GENERAL_FAILURE;
+    }
+}
+
+nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape) {
+    return OutputShape{.dimensions = NN_TRY(toSigned(outputShape.dimensions)),
+                       .isSufficient = outputShape.isSufficient};
+}
+
+nn::GeneralResult<Memory> convert(const nn::Memory& memory) {
+    return validatedConvert(memory);
+}
+
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
+    return validatedConvert(errorStatus);
+}
+
+nn::GeneralResult<std::vector<OutputShape>> convert(
+        const std::vector<nn::OutputShape>& outputShapes) {
+    return validatedConvert(outputShapes);
+}
+
+nn::GeneralResult<std::vector<int32_t>> toSigned(const std::vector<uint32_t>& vec) {
+    if (!std::all_of(vec.begin(), vec.end(),
+                     [](uint32_t v) { return v <= std::numeric_limits<int32_t>::max(); })) {
+        return NN_ERROR() << "Vector contains a value that doesn't fit into int32_t.";
+    }
+    return std::vector<int32_t>(vec.begin(), vec.end());
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/aidl/utils/src/Utils.cpp b/neuralnetworks/aidl/utils/src/Utils.cpp
new file mode 100644
index 0000000..8d00e59
--- /dev/null
+++ b/neuralnetworks/aidl/utils/src/Utils.cpp
@@ -0,0 +1,95 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Utils.h"
+
+#include <nnapi/Result.h>
+
+namespace aidl::android::hardware::neuralnetworks::utils {
+namespace {
+
+using ::android::nn::GeneralResult;
+
+template <typename Type>
+nn::GeneralResult<std::vector<Type>> cloneVec(const std::vector<Type>& arguments) {
+    std::vector<Type> clonedObjects;
+    clonedObjects.reserve(arguments.size());
+    for (const auto& argument : arguments) {
+        clonedObjects.push_back(NN_TRY(clone(argument)));
+    }
+    return clonedObjects;
+}
+
+template <typename Type>
+GeneralResult<std::vector<Type>> clone(const std::vector<Type>& arguments) {
+    return cloneVec(arguments);
+}
+
+}  // namespace
+
+GeneralResult<Memory> clone(const Memory& memory) {
+    common::NativeHandle nativeHandle;
+    nativeHandle.ints = memory.handle.ints;
+    nativeHandle.fds.reserve(memory.handle.fds.size());
+    for (const auto& fd : memory.handle.fds) {
+        const int newFd = dup(fd.get());
+        if (newFd < 0) {
+            return NN_ERROR() << "Couldn't dup a file descriptor";
+        }
+        nativeHandle.fds.emplace_back(newFd);
+    }
+    return Memory{
+            .handle = std::move(nativeHandle),
+            .size = memory.size,
+            .name = memory.name,
+    };
+}
+
+GeneralResult<RequestMemoryPool> clone(const RequestMemoryPool& requestPool) {
+    using Tag = RequestMemoryPool::Tag;
+    switch (requestPool.getTag()) {
+        case Tag::pool:
+            return RequestMemoryPool::make<Tag::pool>(NN_TRY(clone(requestPool.get<Tag::pool>())));
+        case Tag::token:
+            return RequestMemoryPool::make<Tag::token>(requestPool.get<Tag::token>());
+    }
+    // Using explicit type conversion because std::variant inside the RequestMemoryPool confuses the
+    // compiler.
+    return (NN_ERROR() << "Unrecognized request pool tag: " << requestPool.getTag())
+            .
+            operator GeneralResult<RequestMemoryPool>();
+}
+
+GeneralResult<Request> clone(const Request& request) {
+    return Request{
+            .inputs = request.inputs,
+            .outputs = request.outputs,
+            .pools = NN_TRY(clone(request.pools)),
+    };
+}
+
+GeneralResult<Model> clone(const Model& model) {
+    return Model{
+            .main = model.main,
+            .referenced = model.referenced,
+            .operandValues = model.operandValues,
+            .pools = NN_TRY(clone(model.pools)),
+            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
+            .extensionNameToPrefix = model.extensionNameToPrefix,
+    };
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/aidl/vts/OWNERS b/neuralnetworks/aidl/vts/OWNERS
new file mode 100644
index 0000000..6719a5b
--- /dev/null
+++ b/neuralnetworks/aidl/vts/OWNERS
@@ -0,0 +1,12 @@
+# Neuralnetworks team
+butlermichael@google.com
+dgross@google.com
+jeanluc@google.com
+levp@google.com
+miaowang@google.com
+mikie@google.com
+mks@google.com
+pszczepaniak@google.com
+slavash@google.com
+vddang@google.com
+xusongw@google.com
diff --git a/neuralnetworks/aidl/vts/functional/Android.bp b/neuralnetworks/aidl/vts/functional/Android.bp
new file mode 100644
index 0000000..aa7afbf
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/Android.bp
@@ -0,0 +1,68 @@
+//
+// Copyright (C) 2021 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_test {
+    name: "VtsHalNeuralnetworksTargetTest",
+    defaults: [
+        "neuralnetworks_vts_functional_defaults",
+        "use_libaidlvintf_gtest_helper_static",
+    ],
+    srcs: [
+        "BasicTests.cpp",
+        "Callbacks.cpp",
+        "CompilationCachingTests.cpp",
+        "GeneratedTestHarness.cpp",
+        "MemoryDomainTests.cpp",
+        "QualityOfServiceTests.cpp",
+        "TestAssertions.cpp",
+        "TestMain.cpp",
+        "Utils.cpp",
+        "ValidateModel.cpp",
+        "ValidateRequest.cpp",
+        "VtsHalNeuralnetworks.cpp",
+    ],
+    shared_libs: [
+        "libbinder_ndk",
+        "libnativewindow",
+        "libvndksupport",
+    ],
+    static_libs: [
+        "android.hardware.common-V2-ndk_platform",
+        "android.hardware.neuralnetworks-V1-ndk_platform",
+        "android.hidl.allocator@1.0",
+        "android.hidl.memory@1.0",
+        "libgmock",
+        "libhidlmemory",
+        "libneuralnetworks_generated_test_harness",
+        "libneuralnetworks_utils",
+        "libsync",
+        "neuralnetworks_utils_hal_aidl",
+    ],
+    whole_static_libs: [
+        "neuralnetworks_generated_V1_0_example",
+        "neuralnetworks_generated_V1_1_example",
+        "neuralnetworks_generated_V1_2_example",
+        "neuralnetworks_generated_V1_3_example",
+    ],
+    header_libs: [
+        "libbase_headers",
+        "libneuralnetworks_headers",
+    ],
+    test_suites: [
+        "general-tests",
+        "vts",
+    ],
+}
diff --git a/neuralnetworks/aidl/vts/functional/AndroidTest.xml b/neuralnetworks/aidl/vts/functional/AndroidTest.xml
new file mode 100644
index 0000000..384d420
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/AndroidTest.xml
@@ -0,0 +1,33 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Copyright (C) 2020 The Android Open Source Project
+
+     Licensed under the Apache License, Version 2.0 (the "License");
+     you may not use this file except in compliance with the License.
+     You may obtain a copy of the License at
+
+          http://www.apache.org/licenses/LICENSE-2.0
+
+     Unless required by applicable law or agreed to in writing, software
+     distributed under the License is distributed on an "AS IS" BASIS,
+     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+     See the License for the specific language governing permissions and
+     limitations under the License.
+-->
+<configuration description="Runs VtsHalNeuralnetworksTargetTest.">
+    <option name="test-suite-tag" value="apct" />
+    <option name="test-suite-tag" value="apct-native" />
+
+    <target_preparer class="com.android.tradefed.targetprep.RootTargetPreparer">
+    </target_preparer>
+
+    <target_preparer class="com.android.tradefed.targetprep.PushFilePreparer">
+        <option name="cleanup" value="true" />
+        <option name="push" value="VtsHalNeuralnetworksTargetTest->/data/local/tmp/VtsHalNeuralnetworksTargetTest" />
+    </target_preparer>
+
+    <test class="com.android.tradefed.testtype.GTest" >
+        <option name="native-test-device-path" value="/data/local/tmp" />
+        <option name="module-name" value="VtsHalNeuralnetworksTargetTest" />
+        <option name="native-test-timeout" value="20m" />
+    </test>
+</configuration>
diff --git a/neuralnetworks/aidl/vts/functional/BasicTests.cpp b/neuralnetworks/aidl/vts/functional/BasicTests.cpp
new file mode 100644
index 0000000..b2f4507
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/BasicTests.cpp
@@ -0,0 +1,193 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_aidl_hal_test"
+
+#include <aidl/android/hardware/neuralnetworks/Capabilities.h>
+#include <aidl/android/hardware/neuralnetworks/IDevice.h>
+#include <aidl/android/hardware/neuralnetworks/Operand.h>
+#include <aidl/android/hardware/neuralnetworks/OperandType.h>
+#include <aidl/android/hardware/neuralnetworks/Priority.h>
+#include <android/binder_interface_utils.h>
+
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using implementation::PreparedModelCallback;
+
+// create device test
+TEST_P(NeuralNetworksAidlTest, CreateDevice) {}
+
+// initialization
+TEST_P(NeuralNetworksAidlTest, GetCapabilitiesTest) {
+    Capabilities capabilities;
+    const auto retStatus = kDevice->getCapabilities(&capabilities);
+    ASSERT_TRUE(retStatus.isOk());
+
+    auto isPositive = [](const PerformanceInfo& perf) {
+        return perf.execTime > 0.0f && perf.powerUsage > 0.0f;
+    };
+
+    EXPECT_TRUE(isPositive(capabilities.relaxedFloat32toFloat16PerformanceScalar));
+    EXPECT_TRUE(isPositive(capabilities.relaxedFloat32toFloat16PerformanceTensor));
+    const auto& opPerf = capabilities.operandPerformance;
+    EXPECT_TRUE(
+            std::all_of(opPerf.begin(), opPerf.end(),
+                        [isPositive](const OperandPerformance& a) { return isPositive(a.info); }));
+    EXPECT_TRUE(std::is_sorted(opPerf.begin(), opPerf.end(),
+                               [](const OperandPerformance& a, const OperandPerformance& b) {
+                                   return a.type < b.type;
+                               }));
+    EXPECT_TRUE(std::all_of(opPerf.begin(), opPerf.end(), [](const OperandPerformance& a) {
+        return a.type != OperandType::SUBGRAPH;
+    }));
+    EXPECT_TRUE(isPositive(capabilities.ifPerformance));
+    EXPECT_TRUE(isPositive(capabilities.whilePerformance));
+}
+
+// detect cycle
+TEST_P(NeuralNetworksAidlTest, CycleTest) {
+    // opnd0 = TENSOR_FLOAT32            // model input
+    // opnd1 = TENSOR_FLOAT32            // model input
+    // opnd2 = INT32                     // model input
+    // opnd3 = ADD(opnd0, opnd4, opnd2)
+    // opnd4 = ADD(opnd1, opnd3, opnd2)
+    // opnd5 = ADD(opnd4, opnd0, opnd2)  // model output
+    //
+    //            +-----+
+    //            |     |
+    //            v     |
+    // 3 = ADD(0, 4, 2) |
+    // |                |
+    // +----------+     |
+    //            |     |
+    //            v     |
+    // 4 = ADD(1, 3, 2) |
+    // |                |
+    // +----------------+
+    // |
+    // |
+    // +-------+
+    //         |
+    //         v
+    // 5 = ADD(4, 0, 2)
+
+    const std::vector<Operand> operands = {
+            {
+                    // operands[0]
+                    .type = OperandType::TENSOR_FLOAT32,
+                    .dimensions = {1},
+                    .scale = 0.0f,
+                    .zeroPoint = 0,
+                    .lifetime = OperandLifeTime::SUBGRAPH_INPUT,
+                    .location = {.poolIndex = 0, .offset = 0, .length = 0},
+            },
+            {
+                    // operands[1]
+                    .type = OperandType::TENSOR_FLOAT32,
+                    .dimensions = {1},
+                    .scale = 0.0f,
+                    .zeroPoint = 0,
+                    .lifetime = OperandLifeTime::SUBGRAPH_INPUT,
+                    .location = {.poolIndex = 0, .offset = 0, .length = 0},
+            },
+            {
+                    // operands[2]
+                    .type = OperandType::INT32,
+                    .dimensions = {},
+                    .scale = 0.0f,
+                    .zeroPoint = 0,
+                    .lifetime = OperandLifeTime::SUBGRAPH_INPUT,
+                    .location = {.poolIndex = 0, .offset = 0, .length = 0},
+            },
+            {
+                    // operands[3]
+                    .type = OperandType::TENSOR_FLOAT32,
+                    .dimensions = {1},
+                    .scale = 0.0f,
+                    .zeroPoint = 0,
+                    .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+                    .location = {.poolIndex = 0, .offset = 0, .length = 0},
+            },
+            {
+                    // operands[4]
+                    .type = OperandType::TENSOR_FLOAT32,
+                    .dimensions = {1},
+                    .scale = 0.0f,
+                    .zeroPoint = 0,
+                    .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
+                    .location = {.poolIndex = 0, .offset = 0, .length = 0},
+            },
+            {
+                    // operands[5]
+                    .type = OperandType::TENSOR_FLOAT32,
+                    .dimensions = {1},
+                    .scale = 0.0f,
+                    .zeroPoint = 0,
+                    .lifetime = OperandLifeTime::SUBGRAPH_OUTPUT,
+                    .location = {.poolIndex = 0, .offset = 0, .length = 0},
+            },
+    };
+
+    const std::vector<Operation> operations = {
+            {.type = OperationType::ADD, .inputs = {0, 4, 2}, .outputs = {3}},
+            {.type = OperationType::ADD, .inputs = {1, 3, 2}, .outputs = {4}},
+            {.type = OperationType::ADD, .inputs = {4, 0, 2}, .outputs = {5}},
+    };
+
+    Subgraph subgraph = {
+            .operands = operands,
+            .operations = operations,
+            .inputIndexes = {0, 1, 2},
+            .outputIndexes = {5},
+    };
+    const Model model = {
+            .main = std::move(subgraph),
+            .referenced = {},
+            .operandValues = {},
+            .pools = {},
+    };
+
+    // ensure that getSupportedOperations() checks model validity
+    std::vector<bool> supportedOps;
+    const auto supportedOpsStatus = kDevice->getSupportedOperations(model, &supportedOps);
+    ASSERT_FALSE(supportedOpsStatus.isOk());
+    ASSERT_EQ(supportedOpsStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+    ASSERT_EQ(static_cast<ErrorStatus>(supportedOpsStatus.getServiceSpecificError()),
+              ErrorStatus::INVALID_ARGUMENT);
+
+    // ensure that prepareModel() checks model validity
+    auto preparedModelCallback = ndk::SharedRefBase::make<PreparedModelCallback>();
+    auto prepareLaunchStatus =
+            kDevice->prepareModel(model, ExecutionPreference::FAST_SINGLE_ANSWER, kDefaultPriority,
+                                  kNoDeadline, {}, {}, kEmptyCacheToken, preparedModelCallback);
+    //     Note that preparation can fail for reasons other than an
+    //     invalid model (invalid model should result in
+    //     INVALID_ARGUMENT) -- for example, perhaps not all
+    //     operations are supported, or perhaps the device hit some
+    //     kind of capacity limit.
+    ASSERT_FALSE(prepareLaunchStatus.isOk());
+    EXPECT_EQ(prepareLaunchStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+    EXPECT_NE(static_cast<ErrorStatus>(prepareLaunchStatus.getServiceSpecificError()),
+              ErrorStatus::NONE);
+
+    EXPECT_NE(preparedModelCallback->getStatus(), ErrorStatus::NONE);
+    EXPECT_EQ(preparedModelCallback->getPreparedModel(), nullptr);
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/Callbacks.cpp b/neuralnetworks/aidl/vts/functional/Callbacks.cpp
new file mode 100644
index 0000000..ca2bb48
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/Callbacks.cpp
@@ -0,0 +1,59 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "Callbacks"
+
+#include "Callbacks.h"
+
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <limits>
+
+namespace aidl::android::hardware::neuralnetworks::implementation {
+
+ndk::ScopedAStatus PreparedModelCallback::notify(
+        ErrorStatus errorStatus, const std::shared_ptr<IPreparedModel>& preparedModel) {
+    {
+        std::lock_guard<std::mutex> hold(mMutex);
+        // quick-return if object has already been notified
+        if (mNotified) {
+            return ndk::ScopedAStatus::ok();
+        }
+        // store results and mark as notified
+        mErrorStatus = errorStatus;
+        mPreparedModel = preparedModel;
+        mNotified = true;
+    }
+    mCondition.notify_all();
+    return ndk::ScopedAStatus::ok();
+}
+
+void PreparedModelCallback::wait() const {
+    std::unique_lock<std::mutex> lock(mMutex);
+    mCondition.wait(lock, [this] { return mNotified; });
+}
+
+ErrorStatus PreparedModelCallback::getStatus() const {
+    wait();
+    return mErrorStatus;
+}
+
+std::shared_ptr<IPreparedModel> PreparedModelCallback::getPreparedModel() const {
+    wait();
+    return mPreparedModel;
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::implementation
diff --git a/neuralnetworks/aidl/vts/functional/Callbacks.h b/neuralnetworks/aidl/vts/functional/Callbacks.h
new file mode 100644
index 0000000..0eb4d5f
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/Callbacks.h
@@ -0,0 +1,131 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_AIDL_CALLBACKS_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_AIDL_CALLBACKS_H
+
+#include <android-base/thread_annotations.h>
+#include <condition_variable>
+#include <mutex>
+
+#include <aidl/android/hardware/neuralnetworks/BnPreparedModelCallback.h>
+#include <aidl/android/hardware/neuralnetworks/ErrorStatus.h>
+#include <aidl/android/hardware/neuralnetworks/IPreparedModel.h>
+
+/*
+ * The Callback classes are used internally by the NeuralNetworks runtime to
+ * synchronize between different threads. An asynchronous task is launched
+ * paired with a callback object. When a client thread requires the output being
+ * generated by the asynchronous task, the client thread can wait for the result
+ * and be blocked until it has completed. Any wait may safely be called
+ * concurrently, even on the same callback object. When the asynchronous task
+ * has finished its workload, it must immediately call "notify". If the
+ * asynchronous task has failed to launch, the function that tried to launch the
+ * asynchronous task must immediately call "notify". This "notify" call
+ * awakens any client threads waiting on the callback object.
+ *
+ * These classes exist to enable synchronization across AIDL. When
+ * synchronization is only required in the same process, consider using
+ * std::future, std::mutex, std::condition_variable, or std::experimental::latch
+ * instead.
+ */
+
+namespace aidl::android::hardware::neuralnetworks::implementation {
+
+/**
+ * The PreparedModelCallback class is used to receive the error status of
+ * preparing a model as well as the prepared model from a task executing
+ * asynchronously with respect to the runtime. If a calling thread calls wait
+ * or get* on a PreparedModelCallback object and the corresponding asynchronous
+ * task has not finished preparing the model, the calling thread will block
+ * until the asynchronous task has called notify.
+ *
+ * If the callback object is notified more than once, only the results of the
+ * first call to notify are used, and the results from subsequent calls are
+ * discarded.
+ *
+ * This callback object is passed as an argument to IDevice::prepareModel*.
+ */
+class PreparedModelCallback : public BnPreparedModelCallback {
+  public:
+    /**
+     * IPreparedModelCallback::notify marks the callback object with the return
+     * status of the asynchronous model preparation along with the prepared
+     * model, and allows all prior and future wait calls on the
+     * PreparedModelCallback object to proceed.
+     *
+     * IPreparedModelCallback::notify must be called on a given PreparedModelCallback object.
+     *
+     * If the callback object is notified more than once, only the results of
+     * the first call to notify are used, and the results from subsequent calls
+     * are discarded.
+     *
+     * @param status Error status returned from asynchronously preparing the
+     *     model; will be:
+     *     - NONE if the asynchronous preparation was successful
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if the input model is invalid
+     * @param preparedModel Returned model that has been prepared for execution,
+     *     nullptr if the model was unable to be prepared.
+     */
+    ndk::ScopedAStatus notify(ErrorStatus status,
+                              const std::shared_ptr<IPreparedModel>& preparedModel) override;
+
+    /**
+     * PreparedModelCallback::wait blocks until notify has been called on the
+     * callback object.
+     */
+    void wait() const;
+
+    /**
+     * Retrieves the error status returned from the asynchronous task launched
+     * by IDevice::prepareModel*. If IDevice::prepareModel* has not finished
+     * asynchronously preparing the model, this call will block until the
+     * asynchronous task notifies the object.
+     *
+     * @return status Error status returned from asynchronously preparing the
+     *     model; will be:
+     *     - NONE if the asynchronous preparation was successful
+     *     - DEVICE_UNAVAILABLE if driver is offline or busy
+     *     - GENERAL_FAILURE if there is an unspecified error
+     *     - INVALID_ARGUMENT if the input model is invalid
+     */
+    ErrorStatus getStatus() const;
+
+    /**
+     * Retrieves the model that has been prepared for execution from the
+     * asynchronous task launched by IDevice::prepareModel*. If
+     * IDevice::prepareModel* has not finished asynchronously preparing the
+     * model, this call will block until the asynchronous task notifies the
+     * object.
+     *
+     * @return preparedModel Returned model that has been prepared for
+     *     execution, nullptr if the model was unable to be prepared.
+     */
+    std::shared_ptr<IPreparedModel> getPreparedModel() const;
+
+  private:
+    mutable std::mutex mMutex;
+    mutable std::condition_variable mCondition;
+    bool mNotified GUARDED_BY(mMutex) = false;
+    ErrorStatus mErrorStatus = ErrorStatus::GENERAL_FAILURE;
+    std::shared_ptr<IPreparedModel> mPreparedModel;
+};
+
+}  // namespace aidl::android::hardware::neuralnetworks::implementation
+
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_AIDL_CALLBACKS_H
diff --git a/neuralnetworks/aidl/vts/functional/CompilationCachingTests.cpp b/neuralnetworks/aidl/vts/functional/CompilationCachingTests.cpp
new file mode 100644
index 0000000..e0b529f
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/CompilationCachingTests.cpp
@@ -0,0 +1,1177 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_aidl_hal_test"
+
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <android/binder_interface_utils.h>
+#include <android/binder_status.h>
+#include <fcntl.h>
+#include <ftw.h>
+#include <gtest/gtest.h>
+#include <hidlmemory/mapping.h>
+#include <unistd.h>
+
+#include <cstdio>
+#include <cstdlib>
+#include <iterator>
+#include <random>
+#include <thread>
+
+#include "Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "MemoryUtils.h"
+#include "TestHarness.h"
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+// Forward declaration of the mobilenet generated test models in
+// frameworks/ml/nn/runtime/test/generated/.
+namespace generated_tests::mobilenet_224_gender_basic_fixed {
+const test_helper::TestModel& get_test_model();
+}  // namespace generated_tests::mobilenet_224_gender_basic_fixed
+
+namespace generated_tests::mobilenet_quantized {
+const test_helper::TestModel& get_test_model();
+}  // namespace generated_tests::mobilenet_quantized
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using namespace test_helper;
+using implementation::PreparedModelCallback;
+
+namespace float32_model {
+
+constexpr auto get_test_model = generated_tests::mobilenet_224_gender_basic_fixed::get_test_model;
+
+}  // namespace float32_model
+
+namespace quant8_model {
+
+constexpr auto get_test_model = generated_tests::mobilenet_quantized::get_test_model;
+
+}  // namespace quant8_model
+
+namespace {
+
+enum class AccessMode { READ_WRITE, READ_ONLY, WRITE_ONLY };
+
+// Creates cache handles based on provided file groups.
+// The outer vector corresponds to handles and the inner vector is for fds held by each handle.
+void createCacheFds(const std::vector<std::string>& files, const std::vector<AccessMode>& mode,
+                    std::vector<ndk::ScopedFileDescriptor>* fds) {
+    fds->clear();
+    fds->reserve(files.size());
+    for (uint32_t i = 0; i < files.size(); i++) {
+        const auto& file = files[i];
+        int fd;
+        if (mode[i] == AccessMode::READ_ONLY) {
+            fd = open(file.c_str(), O_RDONLY);
+        } else if (mode[i] == AccessMode::WRITE_ONLY) {
+            fd = open(file.c_str(), O_WRONLY | O_CREAT, S_IRUSR | S_IWUSR);
+        } else if (mode[i] == AccessMode::READ_WRITE) {
+            fd = open(file.c_str(), O_RDWR | O_CREAT, S_IRUSR | S_IWUSR);
+        } else {
+            FAIL();
+        }
+        ASSERT_GE(fd, 0);
+        fds->emplace_back(fd);
+    }
+}
+
+void createCacheFds(const std::vector<std::string>& files, AccessMode mode,
+                    std::vector<ndk::ScopedFileDescriptor>* fds) {
+    createCacheFds(files, std::vector<AccessMode>(files.size(), mode), fds);
+}
+
+// Create a chain of broadcast operations. The second operand is always constant tensor [1].
+// For simplicity, activation scalar is shared. The second operand is not shared
+// in the model to let driver maintain a non-trivial size of constant data and the corresponding
+// data locations in cache.
+//
+//                --------- activation --------
+//                ↓      ↓      ↓             ↓
+// E.g. input -> ADD -> ADD -> ADD -> ... -> ADD -> output
+//                ↑      ↑      ↑             ↑
+//               [1]    [1]    [1]           [1]
+//
+// This function assumes the operation is either ADD or MUL.
+template <typename CppType, TestOperandType operandType>
+TestModel createLargeTestModelImpl(TestOperationType op, uint32_t len) {
+    EXPECT_TRUE(op == TestOperationType::ADD || op == TestOperationType::MUL);
+
+    // Model operations and operands.
+    std::vector<TestOperation> operations(len);
+    std::vector<TestOperand> operands(len * 2 + 2);
+
+    // The activation scalar, value = 0.
+    operands[0] = {
+            .type = TestOperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = len,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+            .data = TestBuffer::createFromVector<int32_t>({0}),
+    };
+
+    // The buffer value of the constant second operand. The logical value is always 1.0f.
+    CppType bufferValue;
+    // The scale of the first and second operand.
+    float scale1, scale2;
+    if (operandType == TestOperandType::TENSOR_FLOAT32) {
+        bufferValue = 1.0f;
+        scale1 = 0.0f;
+        scale2 = 0.0f;
+    } else if (op == TestOperationType::ADD) {
+        bufferValue = 1;
+        scale1 = 1.0f;
+        scale2 = 1.0f;
+    } else {
+        // To satisfy the constraint on quant8 MUL: input0.scale * input1.scale < output.scale,
+        // set input1 to have scale = 0.5f and bufferValue = 2, i.e. 1.0f in floating point.
+        bufferValue = 2;
+        scale1 = 1.0f;
+        scale2 = 0.5f;
+    }
+
+    for (uint32_t i = 0; i < len; i++) {
+        const uint32_t firstInputIndex = i * 2 + 1;
+        const uint32_t secondInputIndex = firstInputIndex + 1;
+        const uint32_t outputIndex = secondInputIndex + 1;
+
+        // The first operation input.
+        operands[firstInputIndex] = {
+                .type = operandType,
+                .dimensions = {1},
+                .numberOfConsumers = 1,
+                .scale = scale1,
+                .zeroPoint = 0,
+                .lifetime = (i == 0 ? TestOperandLifeTime::MODEL_INPUT
+                                    : TestOperandLifeTime::TEMPORARY_VARIABLE),
+                .data = (i == 0 ? TestBuffer::createFromVector<CppType>({1}) : TestBuffer()),
+        };
+
+        // The second operation input, value = 1.
+        operands[secondInputIndex] = {
+                .type = operandType,
+                .dimensions = {1},
+                .numberOfConsumers = 1,
+                .scale = scale2,
+                .zeroPoint = 0,
+                .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+                .data = TestBuffer::createFromVector<CppType>({bufferValue}),
+        };
+
+        // The operation. All operations share the same activation scalar.
+        // The output operand is created as an input in the next iteration of the loop, in the case
+        // of all but the last member of the chain; and after the loop as a model output, in the
+        // case of the last member of the chain.
+        operations[i] = {
+                .type = op,
+                .inputs = {firstInputIndex, secondInputIndex, /*activation scalar*/ 0},
+                .outputs = {outputIndex},
+        };
+    }
+
+    // For TestOperationType::ADD, output = 1 + 1 * len = len + 1
+    // For TestOperationType::MUL, output = 1 * 1 ^ len = 1
+    CppType outputResult = static_cast<CppType>(op == TestOperationType::ADD ? len + 1u : 1u);
+
+    // The model output.
+    operands.back() = {
+            .type = operandType,
+            .dimensions = {1},
+            .numberOfConsumers = 0,
+            .scale = scale1,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::MODEL_OUTPUT,
+            .data = TestBuffer::createFromVector<CppType>({outputResult}),
+    };
+
+    return {
+            .main = {.operands = std::move(operands),
+                     .operations = std::move(operations),
+                     .inputIndexes = {1},
+                     .outputIndexes = {len * 2 + 1}},
+            .isRelaxed = false,
+    };
+}
+
+}  // namespace
+
+// Tag for the compilation caching tests.
+class CompilationCachingTestBase : public testing::Test {
+  protected:
+    CompilationCachingTestBase(std::shared_ptr<IDevice> device, OperandType type)
+        : kDevice(std::move(device)), kOperandType(type) {}
+
+    void SetUp() override {
+        testing::Test::SetUp();
+        ASSERT_NE(kDevice.get(), nullptr);
+
+        // Create cache directory. The cache directory and a temporary cache file is always created
+        // to test the behavior of prepareModelFromCache, even when caching is not supported.
+        char cacheDirTemp[] = "/data/local/tmp/TestCompilationCachingXXXXXX";
+        char* cacheDir = mkdtemp(cacheDirTemp);
+        ASSERT_NE(cacheDir, nullptr);
+        mCacheDir = cacheDir;
+        mCacheDir.push_back('/');
+
+        NumberOfCacheFiles numCacheFiles;
+        const auto ret = kDevice->getNumberOfCacheFilesNeeded(&numCacheFiles);
+        ASSERT_TRUE(ret.isOk());
+
+        mNumModelCache = numCacheFiles.numModelCache;
+        mNumDataCache = numCacheFiles.numDataCache;
+        ASSERT_GE(mNumModelCache, 0) << "Invalid numModelCache: " << mNumModelCache;
+        ASSERT_GE(mNumDataCache, 0) << "Invalid numDataCache: " << mNumDataCache;
+        mIsCachingSupported = mNumModelCache > 0 || mNumDataCache > 0;
+
+        // Create empty cache files.
+        mTmpCache = mCacheDir + "tmp";
+        for (uint32_t i = 0; i < mNumModelCache; i++) {
+            mModelCache.push_back({mCacheDir + "model" + std::to_string(i)});
+        }
+        for (uint32_t i = 0; i < mNumDataCache; i++) {
+            mDataCache.push_back({mCacheDir + "data" + std::to_string(i)});
+        }
+        // Placeholder handles, use AccessMode::WRITE_ONLY for createCacheFds to create files.
+        std::vector<ndk::ScopedFileDescriptor> modelHandle, dataHandle, tmpHandle;
+        createCacheFds(mModelCache, AccessMode::WRITE_ONLY, &modelHandle);
+        createCacheFds(mDataCache, AccessMode::WRITE_ONLY, &dataHandle);
+        createCacheFds({mTmpCache}, AccessMode::WRITE_ONLY, &tmpHandle);
+
+        if (!mIsCachingSupported) {
+            LOG(INFO) << "NN VTS: Early termination of test because vendor service does not "
+                         "support compilation caching.";
+            std::cout << "[          ]   Early termination of test because vendor service does not "
+                         "support compilation caching."
+                      << std::endl;
+        }
+    }
+
+    void TearDown() override {
+        // If the test passes, remove the tmp directory.  Otherwise, keep it for debugging purposes.
+        if (!testing::Test::HasFailure()) {
+            // Recursively remove the cache directory specified by mCacheDir.
+            auto callback = [](const char* entry, const struct stat*, int, struct FTW*) {
+                return remove(entry);
+            };
+            nftw(mCacheDir.c_str(), callback, 128, FTW_DEPTH | FTW_MOUNT | FTW_PHYS);
+        }
+        testing::Test::TearDown();
+    }
+
+    // Model and examples creators. According to kOperandType, the following methods will return
+    // either float32 model/examples or the quant8 variant.
+    TestModel createTestModel() {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return float32_model::get_test_model();
+        } else {
+            return quant8_model::get_test_model();
+        }
+    }
+
+    TestModel createLargeTestModel(OperationType op, uint32_t len) {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return createLargeTestModelImpl<float, TestOperandType::TENSOR_FLOAT32>(
+                    static_cast<TestOperationType>(op), len);
+        } else {
+            return createLargeTestModelImpl<uint8_t, TestOperandType::TENSOR_QUANT8_ASYMM>(
+                    static_cast<TestOperationType>(op), len);
+        }
+    }
+
+    // See if the service can handle the model.
+    bool isModelFullySupported(const Model& model) {
+        std::vector<bool> supportedOps;
+        const auto supportedCall = kDevice->getSupportedOperations(model, &supportedOps);
+        EXPECT_TRUE(supportedCall.isOk());
+        EXPECT_EQ(supportedOps.size(), model.main.operations.size());
+        if (!supportedCall.isOk() || supportedOps.size() != model.main.operations.size()) {
+            return false;
+        }
+        return std::all_of(supportedOps.begin(), supportedOps.end(),
+                           [](bool valid) { return valid; });
+    }
+
+    void saveModelToCache(const Model& model,
+                          const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+                          const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+                          std::shared_ptr<IPreparedModel>* preparedModel = nullptr) {
+        if (preparedModel != nullptr) *preparedModel = nullptr;
+
+        // Launch prepare model.
+        std::shared_ptr<PreparedModelCallback> preparedModelCallback =
+                ndk::SharedRefBase::make<PreparedModelCallback>();
+        std::vector<uint8_t> cacheToken(std::begin(mToken), std::end(mToken));
+        const auto prepareLaunchStatus = kDevice->prepareModel(
+                model, ExecutionPreference::FAST_SINGLE_ANSWER, kDefaultPriority, kNoDeadline,
+                modelCache, dataCache, cacheToken, preparedModelCallback);
+        ASSERT_TRUE(prepareLaunchStatus.isOk());
+
+        // Retrieve prepared model.
+        preparedModelCallback->wait();
+        ASSERT_EQ(preparedModelCallback->getStatus(), ErrorStatus::NONE);
+        if (preparedModel != nullptr) {
+            *preparedModel = preparedModelCallback->getPreparedModel();
+        }
+    }
+
+    bool checkEarlyTermination(ErrorStatus status) {
+        if (status == ErrorStatus::GENERAL_FAILURE) {
+            LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
+                         "save the prepared model that it does not support.";
+            std::cout << "[          ]   Early termination of test because vendor service cannot "
+                         "save the prepared model that it does not support."
+                      << std::endl;
+            return true;
+        }
+        return false;
+    }
+
+    bool checkEarlyTermination(const Model& model) {
+        if (!isModelFullySupported(model)) {
+            LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
+                         "prepare model that it does not support.";
+            std::cout << "[          ]   Early termination of test because vendor service cannot "
+                         "prepare model that it does not support."
+                      << std::endl;
+            return true;
+        }
+        return false;
+    }
+
+    void prepareModelFromCache(const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+                               const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+                               std::shared_ptr<IPreparedModel>* preparedModel,
+                               ErrorStatus* status) {
+        // Launch prepare model from cache.
+        std::shared_ptr<PreparedModelCallback> preparedModelCallback =
+                ndk::SharedRefBase::make<PreparedModelCallback>();
+        std::vector<uint8_t> cacheToken(std::begin(mToken), std::end(mToken));
+        const auto prepareLaunchStatus = kDevice->prepareModelFromCache(
+                kNoDeadline, modelCache, dataCache, cacheToken, preparedModelCallback);
+        ASSERT_TRUE(prepareLaunchStatus.isOk() ||
+                    prepareLaunchStatus.getExceptionCode() == EX_SERVICE_SPECIFIC)
+                << "prepareLaunchStatus: " << prepareLaunchStatus.getDescription();
+        if (!prepareLaunchStatus.isOk()) {
+            *preparedModel = nullptr;
+            *status = static_cast<ErrorStatus>(prepareLaunchStatus.getServiceSpecificError());
+            return;
+        }
+
+        // Retrieve prepared model.
+        preparedModelCallback->wait();
+        *status = preparedModelCallback->getStatus();
+        *preparedModel = preparedModelCallback->getPreparedModel();
+    }
+
+    // Absolute path to the temporary cache directory.
+    std::string mCacheDir;
+
+    // Groups of file paths for model and data cache in the tmp cache directory, initialized with
+    // size = mNum{Model|Data}Cache. The outer vector corresponds to handles and the inner vector is
+    // for fds held by each handle.
+    std::vector<std::string> mModelCache;
+    std::vector<std::string> mDataCache;
+
+    // A separate temporary file path in the tmp cache directory.
+    std::string mTmpCache;
+
+    uint8_t mToken[static_cast<uint32_t>(IDevice::BYTE_SIZE_OF_CACHE_TOKEN)] = {};
+    uint32_t mNumModelCache;
+    uint32_t mNumDataCache;
+    uint32_t mIsCachingSupported;
+
+    const std::shared_ptr<IDevice> kDevice;
+    // The primary data type of the testModel.
+    const OperandType kOperandType;
+};
+
+using CompilationCachingTestParam = std::tuple<NamedDevice, OperandType>;
+
+// A parameterized fixture of CompilationCachingTestBase. Every test will run twice, with the first
+// pass running with float32 models and the second pass running with quant8 models.
+class CompilationCachingTest : public CompilationCachingTestBase,
+                               public testing::WithParamInterface<CompilationCachingTestParam> {
+  protected:
+    CompilationCachingTest()
+        : CompilationCachingTestBase(getData(std::get<NamedDevice>(GetParam())),
+                                     std::get<OperandType>(GetParam())) {}
+};
+
+TEST_P(CompilationCachingTest, CacheSavingAndRetrieval) {
+    // Create test HIDL model and compile.
+    const TestModel& testModel = createTestModel();
+    const Model model = createModel(testModel);
+    if (checkEarlyTermination(model)) return;
+    std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+
+    // Save the compilation to cache.
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(model, modelCache, dataCache);
+    }
+
+    // Retrieve preparedModel from cache.
+    {
+        preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (!mIsCachingSupported) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+            ASSERT_EQ(preparedModel, nullptr);
+            return;
+        } else if (checkEarlyTermination(status)) {
+            ASSERT_EQ(preparedModel, nullptr);
+            return;
+        } else {
+            ASSERT_EQ(status, ErrorStatus::NONE);
+            ASSERT_NE(preparedModel, nullptr);
+        }
+    }
+
+    // Execute and verify results.
+    EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+}
+
+TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
+    // Create test HIDL model and compile.
+    const TestModel& testModel = createTestModel();
+    const Model model = createModel(testModel);
+    if (checkEarlyTermination(model)) return;
+    std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+
+    // Save the compilation to cache.
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        uint8_t placeholderBytes[] = {0, 0};
+        // Write a placeholder integer to the cache.
+        // The driver should be able to handle non-empty cache and non-zero fd offset.
+        for (uint32_t i = 0; i < modelCache.size(); i++) {
+            ASSERT_EQ(write(modelCache[i].get(), &placeholderBytes, sizeof(placeholderBytes)),
+                      sizeof(placeholderBytes));
+        }
+        for (uint32_t i = 0; i < dataCache.size(); i++) {
+            ASSERT_EQ(write(dataCache[i].get(), &placeholderBytes, sizeof(placeholderBytes)),
+                      sizeof(placeholderBytes));
+        }
+        saveModelToCache(model, modelCache, dataCache);
+    }
+
+    // Retrieve preparedModel from cache.
+    {
+        preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        uint8_t placeholderByte = 0;
+        // Advance the offset of each handle by one byte.
+        // The driver should be able to handle non-zero fd offset.
+        for (uint32_t i = 0; i < modelCache.size(); i++) {
+            ASSERT_GE(read(modelCache[i].get(), &placeholderByte, 1), 0);
+        }
+        for (uint32_t i = 0; i < dataCache.size(); i++) {
+            ASSERT_GE(read(dataCache[i].get(), &placeholderByte, 1), 0);
+        }
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (!mIsCachingSupported) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+            ASSERT_EQ(preparedModel, nullptr);
+            return;
+        } else if (checkEarlyTermination(status)) {
+            ASSERT_EQ(preparedModel, nullptr);
+            return;
+        } else {
+            ASSERT_EQ(status, ErrorStatus::NONE);
+            ASSERT_NE(preparedModel, nullptr);
+        }
+    }
+
+    // Execute and verify results.
+    EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+}
+
+TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
+    // Create test HIDL model and compile.
+    const TestModel& testModel = createTestModel();
+    const Model model = createModel(testModel);
+    if (checkEarlyTermination(model)) return;
+
+    // Test with number of model cache files greater than mNumModelCache.
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        // Pass an additional cache file for model cache.
+        mModelCache.push_back({mTmpCache});
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mModelCache.pop_back();
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        saveModelToCache(model, modelCache, dataCache, &preparedModel);
+        ASSERT_NE(preparedModel, nullptr);
+        // Execute and verify results.
+        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+        // Check if prepareModelFromCache fails.
+        preparedModel = nullptr;
+        ErrorStatus status;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::INVALID_ARGUMENT) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Test with number of model cache files smaller than mNumModelCache.
+    if (mModelCache.size() > 0) {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        // Pop out the last cache file.
+        auto tmp = mModelCache.back();
+        mModelCache.pop_back();
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mModelCache.push_back(tmp);
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        saveModelToCache(model, modelCache, dataCache, &preparedModel);
+        ASSERT_NE(preparedModel, nullptr);
+        // Execute and verify results.
+        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+        // Check if prepareModelFromCache fails.
+        preparedModel = nullptr;
+        ErrorStatus status;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::INVALID_ARGUMENT) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Test with number of data cache files greater than mNumDataCache.
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        // Pass an additional cache file for data cache.
+        mDataCache.push_back({mTmpCache});
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mDataCache.pop_back();
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        saveModelToCache(model, modelCache, dataCache, &preparedModel);
+        ASSERT_NE(preparedModel, nullptr);
+        // Execute and verify results.
+        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+        // Check if prepareModelFromCache fails.
+        preparedModel = nullptr;
+        ErrorStatus status;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::INVALID_ARGUMENT) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Test with number of data cache files smaller than mNumDataCache.
+    if (mDataCache.size() > 0) {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        // Pop out the last cache file.
+        auto tmp = mDataCache.back();
+        mDataCache.pop_back();
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mDataCache.push_back(tmp);
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        saveModelToCache(model, modelCache, dataCache, &preparedModel);
+        ASSERT_NE(preparedModel, nullptr);
+        // Execute and verify results.
+        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+        // Check if prepareModelFromCache fails.
+        preparedModel = nullptr;
+        ErrorStatus status;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::INVALID_ARGUMENT) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+}
+
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
+    // Create test HIDL model and compile.
+    const TestModel& testModel = createTestModel();
+    const Model model = createModel(testModel);
+    if (checkEarlyTermination(model)) return;
+
+    // Save the compilation to cache.
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(model, modelCache, dataCache);
+    }
+
+    // Test with number of model cache files greater than mNumModelCache.
+    {
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        mModelCache.push_back({mTmpCache});
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mModelCache.pop_back();
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::GENERAL_FAILURE) {
+            ASSERT_EQ(status, ErrorStatus::INVALID_ARGUMENT);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Test with number of model cache files smaller than mNumModelCache.
+    if (mModelCache.size() > 0) {
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        auto tmp = mModelCache.back();
+        mModelCache.pop_back();
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mModelCache.push_back(tmp);
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::GENERAL_FAILURE) {
+            ASSERT_EQ(status, ErrorStatus::INVALID_ARGUMENT);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Test with number of data cache files greater than mNumDataCache.
+    {
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        mDataCache.push_back({mTmpCache});
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mDataCache.pop_back();
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::GENERAL_FAILURE) {
+            ASSERT_EQ(status, ErrorStatus::INVALID_ARGUMENT);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Test with number of data cache files smaller than mNumDataCache.
+    if (mDataCache.size() > 0) {
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        auto tmp = mDataCache.back();
+        mDataCache.pop_back();
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        mDataCache.push_back(tmp);
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::GENERAL_FAILURE) {
+            ASSERT_EQ(status, ErrorStatus::INVALID_ARGUMENT);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+}
+
+TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
+    // Create test HIDL model and compile.
+    const TestModel& testModel = createTestModel();
+    const Model model = createModel(testModel);
+    if (checkEarlyTermination(model)) return;
+    std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
+    std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);
+
+    // Go through each handle in model cache, test with invalid access mode.
+    for (uint32_t i = 0; i < mNumModelCache; i++) {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        modelCacheMode[i] = AccessMode::READ_ONLY;
+        createCacheFds(mModelCache, modelCacheMode, &modelCache);
+        createCacheFds(mDataCache, dataCacheMode, &dataCache);
+        modelCacheMode[i] = AccessMode::READ_WRITE;
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        saveModelToCache(model, modelCache, dataCache, &preparedModel);
+        ASSERT_NE(preparedModel, nullptr);
+        // Execute and verify results.
+        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+        // Check if prepareModelFromCache fails.
+        preparedModel = nullptr;
+        ErrorStatus status;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::INVALID_ARGUMENT) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Go through each handle in data cache, test with invalid access mode.
+    for (uint32_t i = 0; i < mNumDataCache; i++) {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        dataCacheMode[i] = AccessMode::READ_ONLY;
+        createCacheFds(mModelCache, modelCacheMode, &modelCache);
+        createCacheFds(mDataCache, dataCacheMode, &dataCache);
+        dataCacheMode[i] = AccessMode::READ_WRITE;
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        saveModelToCache(model, modelCache, dataCache, &preparedModel);
+        ASSERT_NE(preparedModel, nullptr);
+        // Execute and verify results.
+        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+        // Check if prepareModelFromCache fails.
+        preparedModel = nullptr;
+        ErrorStatus status;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        if (status != ErrorStatus::INVALID_ARGUMENT) {
+            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        }
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+}
+
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
+    // Create test HIDL model and compile.
+    const TestModel& testModel = createTestModel();
+    const Model model = createModel(testModel);
+    if (checkEarlyTermination(model)) return;
+    std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
+    std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);
+
+    // Save the compilation to cache.
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(model, modelCache, dataCache);
+    }
+
+    // Go through each handle in model cache, test with invalid access mode.
+    for (uint32_t i = 0; i < mNumModelCache; i++) {
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        modelCacheMode[i] = AccessMode::WRITE_ONLY;
+        createCacheFds(mModelCache, modelCacheMode, &modelCache);
+        createCacheFds(mDataCache, dataCacheMode, &dataCache);
+        modelCacheMode[i] = AccessMode::READ_WRITE;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+
+    // Go through each handle in data cache, test with invalid access mode.
+    for (uint32_t i = 0; i < mNumDataCache; i++) {
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        dataCacheMode[i] = AccessMode::WRITE_ONLY;
+        createCacheFds(mModelCache, modelCacheMode, &modelCache);
+        createCacheFds(mDataCache, dataCacheMode, &dataCache);
+        dataCacheMode[i] = AccessMode::READ_WRITE;
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+}
+
+// Copy file contents between files.
+// The vector sizes must match.
+static void copyCacheFiles(const std::vector<std::string>& from,
+                           const std::vector<std::string>& to) {
+    constexpr size_t kBufferSize = 1000000;
+    uint8_t buffer[kBufferSize];
+
+    ASSERT_EQ(from.size(), to.size());
+    for (uint32_t i = 0; i < from.size(); i++) {
+        int fromFd = open(from[i].c_str(), O_RDONLY);
+        int toFd = open(to[i].c_str(), O_WRONLY | O_CREAT, S_IRUSR | S_IWUSR);
+        ASSERT_GE(fromFd, 0);
+        ASSERT_GE(toFd, 0);
+
+        ssize_t readBytes;
+        while ((readBytes = read(fromFd, &buffer, kBufferSize)) > 0) {
+            ASSERT_EQ(write(toFd, &buffer, readBytes), readBytes);
+        }
+        ASSERT_GE(readBytes, 0);
+
+        close(fromFd);
+        close(toFd);
+    }
+}
+
+// Number of operations in the large test model.
+constexpr uint32_t kLargeModelSize = 100;
+constexpr uint32_t kNumIterationsTOCTOU = 100;
+
+TEST_P(CompilationCachingTest, SaveToCache_TOCTOU) {
+    if (!mIsCachingSupported) return;
+
+    // Create test models and check if fully supported by the service.
+    const TestModel testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+    const Model modelMul = createModel(testModelMul);
+    if (checkEarlyTermination(modelMul)) return;
+    const TestModel testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+    const Model modelAdd = createModel(testModelAdd);
+    if (checkEarlyTermination(modelAdd)) return;
+
+    // Save the modelMul compilation to cache.
+    auto modelCacheMul = mModelCache;
+    for (auto& cache : modelCacheMul) {
+        cache.append("_mul");
+    }
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(modelMul, modelCache, dataCache);
+    }
+
+    // Use a different token for modelAdd.
+    mToken[0]++;
+
+    // This test is probabilistic, so we run it multiple times.
+    for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
+        // Save the modelAdd compilation to cache.
+        {
+            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+
+            // Spawn a thread to copy the cache content concurrently while saving to cache.
+            std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
+            saveModelToCache(modelAdd, modelCache, dataCache);
+            thread.join();
+        }
+
+        // Retrieve preparedModel from cache.
+        {
+            std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+            ErrorStatus status;
+            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+
+            // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
+            // the prepared model must be executed with the correct result and not crash.
+            if (status != ErrorStatus::NONE) {
+                ASSERT_EQ(preparedModel, nullptr);
+            } else {
+                ASSERT_NE(preparedModel, nullptr);
+                EvaluatePreparedModel(kDevice, preparedModel, testModelAdd,
+                                      /*testKind=*/TestKind::GENERAL);
+            }
+        }
+    }
+}
+
+TEST_P(CompilationCachingTest, PrepareFromCache_TOCTOU) {
+    if (!mIsCachingSupported) return;
+
+    // Create test models and check if fully supported by the service.
+    const TestModel testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+    const Model modelMul = createModel(testModelMul);
+    if (checkEarlyTermination(modelMul)) return;
+    const TestModel testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+    const Model modelAdd = createModel(testModelAdd);
+    if (checkEarlyTermination(modelAdd)) return;
+
+    // Save the modelMul compilation to cache.
+    auto modelCacheMul = mModelCache;
+    for (auto& cache : modelCacheMul) {
+        cache.append("_mul");
+    }
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(modelMul, modelCache, dataCache);
+    }
+
+    // Use a different token for modelAdd.
+    mToken[0]++;
+
+    // This test is probabilistic, so we run it multiple times.
+    for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
+        // Save the modelAdd compilation to cache.
+        {
+            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            saveModelToCache(modelAdd, modelCache, dataCache);
+        }
+
+        // Retrieve preparedModel from cache.
+        {
+            std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+            ErrorStatus status;
+            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+
+            // Spawn a thread to copy the cache content concurrently while preparing from cache.
+            std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
+            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+            thread.join();
+
+            // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
+            // the prepared model must be executed with the correct result and not crash.
+            if (status != ErrorStatus::NONE) {
+                ASSERT_EQ(preparedModel, nullptr);
+            } else {
+                ASSERT_NE(preparedModel, nullptr);
+                EvaluatePreparedModel(kDevice, preparedModel, testModelAdd,
+                                      /*testKind=*/TestKind::GENERAL);
+            }
+        }
+    }
+}
+
+TEST_P(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
+    if (!mIsCachingSupported) return;
+
+    // Create test models and check if fully supported by the service.
+    const TestModel testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+    const Model modelMul = createModel(testModelMul);
+    if (checkEarlyTermination(modelMul)) return;
+    const TestModel testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+    const Model modelAdd = createModel(testModelAdd);
+    if (checkEarlyTermination(modelAdd)) return;
+
+    // Save the modelMul compilation to cache.
+    auto modelCacheMul = mModelCache;
+    for (auto& cache : modelCacheMul) {
+        cache.append("_mul");
+    }
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(modelMul, modelCache, dataCache);
+    }
+
+    // Use a different token for modelAdd.
+    mToken[0]++;
+
+    // Save the modelAdd compilation to cache.
+    {
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        saveModelToCache(modelAdd, modelCache, dataCache);
+    }
+
+    // Replace the model cache of modelAdd with modelMul.
+    copyCacheFiles(modelCacheMul, mModelCache);
+
+    // Retrieve the preparedModel from cache, expect failure.
+    {
+        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+        ErrorStatus status;
+        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+        ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+        ASSERT_EQ(preparedModel, nullptr);
+    }
+}
+
+// TODO(b/179270601): restore kNamedDeviceChoices.
+static const auto kOperandTypeChoices =
+        testing::Values(OperandType::TENSOR_FLOAT32, OperandType::TENSOR_QUANT8_ASYMM);
+
+std::string printCompilationCachingTest(
+        const testing::TestParamInfo<CompilationCachingTestParam>& info) {
+    const auto& [namedDevice, operandType] = info.param;
+    const std::string type = (operandType == OperandType::TENSOR_FLOAT32 ? "float32" : "quant8");
+    return gtestCompliantName(getName(namedDevice) + "_" + type);
+}
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(CompilationCachingTest);
+INSTANTIATE_TEST_SUITE_P(TestCompilationCaching, CompilationCachingTest,
+                         testing::Combine(testing::ValuesIn(getNamedDevices()),
+                                          kOperandTypeChoices),
+                         printCompilationCachingTest);
+
+using CompilationCachingSecurityTestParam = std::tuple<NamedDevice, OperandType, uint32_t>;
+
+class CompilationCachingSecurityTest
+    : public CompilationCachingTestBase,
+      public testing::WithParamInterface<CompilationCachingSecurityTestParam> {
+  protected:
+    CompilationCachingSecurityTest()
+        : CompilationCachingTestBase(getData(std::get<NamedDevice>(GetParam())),
+                                     std::get<OperandType>(GetParam())) {}
+
+    void SetUp() {
+        CompilationCachingTestBase::SetUp();
+        generator.seed(kSeed);
+    }
+
+    // Get a random integer within a closed range [lower, upper].
+    template <typename T>
+    T getRandomInt(T lower, T upper) {
+        std::uniform_int_distribution<T> dis(lower, upper);
+        return dis(generator);
+    }
+
+    // Randomly flip one single bit of the cache entry.
+    void flipOneBitOfCache(const std::string& filename, bool* skip) {
+        FILE* pFile = fopen(filename.c_str(), "r+");
+        ASSERT_EQ(fseek(pFile, 0, SEEK_END), 0);
+        long int fileSize = ftell(pFile);
+        if (fileSize == 0) {
+            fclose(pFile);
+            *skip = true;
+            return;
+        }
+        ASSERT_EQ(fseek(pFile, getRandomInt(0l, fileSize - 1), SEEK_SET), 0);
+        int readByte = fgetc(pFile);
+        ASSERT_NE(readByte, EOF);
+        ASSERT_EQ(fseek(pFile, -1, SEEK_CUR), 0);
+        ASSERT_NE(fputc(static_cast<uint8_t>(readByte) ^ (1U << getRandomInt(0, 7)), pFile), EOF);
+        fclose(pFile);
+        *skip = false;
+    }
+
+    // Randomly append bytes to the cache entry.
+    void appendBytesToCache(const std::string& filename, bool* skip) {
+        FILE* pFile = fopen(filename.c_str(), "a");
+        uint32_t appendLength = getRandomInt(1, 256);
+        for (uint32_t i = 0; i < appendLength; i++) {
+            ASSERT_NE(fputc(getRandomInt<uint8_t>(0, 255), pFile), EOF);
+        }
+        fclose(pFile);
+        *skip = false;
+    }
+
+    enum class ExpectedResult { GENERAL_FAILURE, NOT_CRASH };
+
+    // Test if the driver behaves as expected when given corrupted cache or token.
+    // The modifier will be invoked after save to cache but before prepare from cache.
+    // The modifier accepts one pointer argument "skip" as the returning value, indicating
+    // whether the test should be skipped or not.
+    void testCorruptedCache(ExpectedResult expected, std::function<void(bool*)> modifier) {
+        const TestModel& testModel = createTestModel();
+        const Model model = createModel(testModel);
+        if (checkEarlyTermination(model)) return;
+
+        // Save the compilation to cache.
+        {
+            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            saveModelToCache(model, modelCache, dataCache);
+        }
+
+        bool skip = false;
+        modifier(&skip);
+        if (skip) return;
+
+        // Retrieve preparedModel from cache.
+        {
+            std::shared_ptr<IPreparedModel> preparedModel = nullptr;
+            ErrorStatus status;
+            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
+            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
+            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
+            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+
+            switch (expected) {
+                case ExpectedResult::GENERAL_FAILURE:
+                    ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+                    ASSERT_EQ(preparedModel, nullptr);
+                    break;
+                case ExpectedResult::NOT_CRASH:
+                    ASSERT_EQ(preparedModel == nullptr, status != ErrorStatus::NONE);
+                    break;
+                default:
+                    FAIL();
+            }
+        }
+    }
+
+    const uint32_t kSeed = std::get<uint32_t>(GetParam());
+    std::mt19937 generator;
+};
+
+TEST_P(CompilationCachingSecurityTest, CorruptedModelCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumModelCache; i++) {
+        testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
+                           [this, i](bool* skip) { flipOneBitOfCache(mModelCache[i], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongLengthModelCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumModelCache; i++) {
+        testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
+                           [this, i](bool* skip) { appendBytesToCache(mModelCache[i], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, CorruptedDataCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumDataCache; i++) {
+        testCorruptedCache(ExpectedResult::NOT_CRASH,
+                           [this, i](bool* skip) { flipOneBitOfCache(mDataCache[i], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongLengthDataCache) {
+    if (!mIsCachingSupported) return;
+    for (uint32_t i = 0; i < mNumDataCache; i++) {
+        testCorruptedCache(ExpectedResult::NOT_CRASH,
+                           [this, i](bool* skip) { appendBytesToCache(mDataCache[i], skip); });
+    }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongToken) {
+    if (!mIsCachingSupported) return;
+    testCorruptedCache(ExpectedResult::GENERAL_FAILURE, [this](bool* skip) {
+        // Randomly flip one single bit in mToken.
+        uint32_t ind =
+                getRandomInt(0u, static_cast<uint32_t>(IDevice::BYTE_SIZE_OF_CACHE_TOKEN) - 1);
+        mToken[ind] ^= (1U << getRandomInt(0, 7));
+        *skip = false;
+    });
+}
+
+std::string printCompilationCachingSecurityTest(
+        const testing::TestParamInfo<CompilationCachingSecurityTestParam>& info) {
+    const auto& [namedDevice, operandType, seed] = info.param;
+    const std::string type = (operandType == OperandType::TENSOR_FLOAT32 ? "float32" : "quant8");
+    return gtestCompliantName(getName(namedDevice) + "_" + type + "_" + std::to_string(seed));
+}
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(CompilationCachingSecurityTest);
+INSTANTIATE_TEST_SUITE_P(TestCompilationCaching, CompilationCachingSecurityTest,
+                         testing::Combine(testing::ValuesIn(getNamedDevices()), kOperandTypeChoices,
+                                          testing::Range(0U, 10U)),
+                         printCompilationCachingSecurityTest);
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
new file mode 100644
index 0000000..86d5f3f
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
@@ -0,0 +1,925 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "GeneratedTestHarness.h"
+
+#include <aidl/android/hardware/neuralnetworks/ErrorStatus.h>
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <android/sync.h>
+#include <gtest/gtest.h>
+
+#include <algorithm>
+#include <chrono>
+#include <iostream>
+#include <iterator>
+#include <numeric>
+#include <vector>
+
+#include <MemoryUtils.h>
+#include <android/binder_status.h>
+#include <nnapi/Result.h>
+#include <nnapi/SharedMemory.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/aidl/Conversions.h>
+#include <nnapi/hal/aidl/Utils.h>
+
+#include "Callbacks.h"
+#include "TestHarness.h"
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+namespace nn = ::android::nn;
+using namespace test_helper;
+using implementation::PreparedModelCallback;
+
+namespace {
+
+enum class OutputType { FULLY_SPECIFIED, UNSPECIFIED, INSUFFICIENT, MISSED_DEADLINE };
+
+struct TestConfig {
+    Executor executor;
+    bool measureTiming;
+    OutputType outputType;
+    MemoryType memoryType;
+    // `reportSkipping` indicates if a test should print an info message in case
+    // it is skipped. The field is set to true by default and is set to false in
+    // quantization coupling tests to suppress skipping a test
+    bool reportSkipping;
+    TestConfig(Executor executor, bool measureTiming, OutputType outputType, MemoryType memoryType)
+        : executor(executor),
+          measureTiming(measureTiming),
+          outputType(outputType),
+          memoryType(memoryType),
+          reportSkipping(true) {}
+    TestConfig(Executor executor, bool measureTiming, OutputType outputType, MemoryType memoryType,
+               bool reportSkipping)
+        : executor(executor),
+          measureTiming(measureTiming),
+          outputType(outputType),
+          memoryType(memoryType),
+          reportSkipping(reportSkipping) {}
+};
+
+enum class IOType { INPUT, OUTPUT };
+
+class DeviceMemoryAllocator {
+  public:
+    DeviceMemoryAllocator(const std::shared_ptr<IDevice>& device,
+                          const std::shared_ptr<IPreparedModel>& preparedModel,
+                          const TestModel& testModel)
+        : kDevice(device), kPreparedModel(preparedModel), kTestModel(testModel) {}
+
+    // Allocate device memory for a target input/output operand.
+    // Return {IBuffer object, token} if successful.
+    // Return {nullptr, 0} if device memory is not supported.
+    template <IOType ioType>
+    std::pair<std::shared_ptr<IBuffer>, int32_t> allocate(uint32_t index) {
+        std::pair<std::shared_ptr<IBuffer>, int32_t> buffer;
+        allocateInternal<ioType>(index, &buffer);
+        return buffer;
+    }
+
+  private:
+    template <IOType ioType>
+    void allocateInternal(int32_t index, std::pair<std::shared_ptr<IBuffer>, int32_t>* result) {
+        ASSERT_NE(result, nullptr);
+
+        // Prepare arguments.
+        BufferRole role = {.modelIndex = 0, .ioIndex = index, .frequency = 1.0f};
+        std::vector<BufferRole> inputRoles, outputRoles;
+        if constexpr (ioType == IOType::INPUT) {
+            inputRoles = {role};
+        } else {
+            outputRoles = {role};
+        }
+
+        // Allocate device memory.
+        DeviceBuffer buffer;
+        IPreparedModelParcel parcel;
+        parcel.preparedModel = kPreparedModel;
+        const auto ret = kDevice->allocate({}, {parcel}, inputRoles, outputRoles, &buffer);
+
+        // Check allocation results.
+        if (ret.isOk()) {
+            ASSERT_NE(buffer.buffer, nullptr);
+            ASSERT_GT(buffer.token, 0);
+        } else {
+            ASSERT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+            ASSERT_EQ(static_cast<ErrorStatus>(ret.getServiceSpecificError()),
+                      ErrorStatus::GENERAL_FAILURE);
+            buffer.buffer = nullptr;
+            buffer.token = 0;
+        }
+
+        // Initialize input data from TestBuffer.
+        if constexpr (ioType == IOType::INPUT) {
+            if (buffer.buffer != nullptr) {
+                // TestBuffer -> Shared memory.
+                const auto& testBuffer =
+                        kTestModel.main.operands[kTestModel.main.inputIndexes[index]].data;
+                ASSERT_GT(testBuffer.size(), 0);
+                const auto sharedMemory = nn::createSharedMemory(testBuffer.size()).value();
+                const auto memory = utils::convert(sharedMemory).value();
+                const auto mapping = nn::map(sharedMemory).value();
+                uint8_t* inputPtr = static_cast<uint8_t*>(std::get<void*>(mapping.pointer));
+                ASSERT_NE(inputPtr, nullptr);
+                const uint8_t* begin = testBuffer.get<uint8_t>();
+                const uint8_t* end = begin + testBuffer.size();
+                std::copy(begin, end, inputPtr);
+
+                // Shared memory -> IBuffer.
+                auto ret = buffer.buffer->copyFrom(memory, {});
+                ASSERT_TRUE(ret.isOk());
+            }
+        }
+        *result = {std::move(buffer.buffer), buffer.token};
+    }
+
+    const std::shared_ptr<IDevice> kDevice;
+    const std::shared_ptr<IPreparedModel> kPreparedModel;
+    const TestModel& kTestModel;
+};
+
+Subgraph createSubgraph(const TestSubgraph& testSubgraph, uint32_t* constCopySize,
+                        std::vector<const TestBuffer*>* constCopies, uint32_t* constRefSize,
+                        std::vector<const TestBuffer*>* constReferences) {
+    CHECK(constCopySize != nullptr);
+    CHECK(constCopies != nullptr);
+    CHECK(constRefSize != nullptr);
+    CHECK(constReferences != nullptr);
+
+    // Operands.
+    std::vector<Operand> operands(testSubgraph.operands.size());
+    for (uint32_t i = 0; i < testSubgraph.operands.size(); i++) {
+        const auto& op = testSubgraph.operands[i];
+
+        DataLocation loc = {};
+        if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) {
+            loc = {
+                    .poolIndex = 0,
+                    .offset = *constCopySize,
+                    .length = static_cast<int64_t>(op.data.size()),
+            };
+            constCopies->push_back(&op.data);
+            *constCopySize += op.data.alignedSize();
+        } else if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) {
+            loc = {
+                    .poolIndex = 0,
+                    .offset = *constRefSize,
+                    .length = static_cast<int64_t>(op.data.size()),
+            };
+            constReferences->push_back(&op.data);
+            *constRefSize += op.data.alignedSize();
+        } else if (op.lifetime == TestOperandLifeTime::SUBGRAPH) {
+            loc = {
+                    .poolIndex = 0,
+                    .offset = *op.data.get<uint32_t>(),
+                    .length = 0,
+            };
+        }
+
+        std::optional<OperandExtraParams> extraParams;
+        if (op.type == TestOperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL) {
+            using Tag = OperandExtraParams::Tag;
+            extraParams = OperandExtraParams::make<Tag::channelQuant>(SymmPerChannelQuantParams{
+                    .scales = op.channelQuant.scales,
+                    .channelDim = static_cast<int32_t>(op.channelQuant.channelDim)});
+        }
+
+        operands[i] = {.type = static_cast<OperandType>(op.type),
+                       .dimensions = utils::toSigned(op.dimensions).value(),
+                       .scale = op.scale,
+                       .zeroPoint = op.zeroPoint,
+                       .lifetime = static_cast<OperandLifeTime>(op.lifetime),
+                       .location = loc,
+                       .extraParams = std::move(extraParams)};
+    }
+
+    // Operations.
+    std::vector<Operation> operations(testSubgraph.operations.size());
+    std::transform(testSubgraph.operations.begin(), testSubgraph.operations.end(),
+                   operations.begin(), [](const TestOperation& op) -> Operation {
+                       return {.type = static_cast<OperationType>(op.type),
+                               .inputs = utils::toSigned(op.inputs).value(),
+                               .outputs = utils::toSigned(op.outputs).value()};
+                   });
+
+    return {.operands = std::move(operands),
+            .operations = std::move(operations),
+            .inputIndexes = utils::toSigned(testSubgraph.inputIndexes).value(),
+            .outputIndexes = utils::toSigned(testSubgraph.outputIndexes).value()};
+}
+
+void copyTestBuffers(const std::vector<const TestBuffer*>& buffers, uint8_t* output) {
+    uint32_t offset = 0;
+    for (const TestBuffer* buffer : buffers) {
+        const uint8_t* begin = buffer->get<uint8_t>();
+        const uint8_t* end = begin + buffer->size();
+        std::copy(begin, end, output + offset);
+        offset += buffer->alignedSize();
+    }
+}
+
+}  // namespace
+
+void waitForSyncFence(int syncFd) {
+    constexpr int kInfiniteTimeout = -1;
+    ASSERT_GT(syncFd, 0);
+    int r = sync_wait(syncFd, kInfiniteTimeout);
+    ASSERT_GE(r, 0);
+}
+
+Model createModel(const TestModel& testModel) {
+    uint32_t constCopySize = 0;
+    uint32_t constRefSize = 0;
+    std::vector<const TestBuffer*> constCopies;
+    std::vector<const TestBuffer*> constReferences;
+
+    Subgraph mainSubgraph = createSubgraph(testModel.main, &constCopySize, &constCopies,
+                                           &constRefSize, &constReferences);
+    std::vector<Subgraph> refSubgraphs(testModel.referenced.size());
+    std::transform(testModel.referenced.begin(), testModel.referenced.end(), refSubgraphs.begin(),
+                   [&constCopySize, &constCopies, &constRefSize,
+                    &constReferences](const TestSubgraph& testSubgraph) {
+                       return createSubgraph(testSubgraph, &constCopySize, &constCopies,
+                                             &constRefSize, &constReferences);
+                   });
+
+    // Constant copies.
+    std::vector<uint8_t> operandValues(constCopySize);
+    copyTestBuffers(constCopies, operandValues.data());
+
+    // Shared memory.
+    std::vector<nn::Memory> pools = {};
+    if (constRefSize > 0) {
+        const auto pool = nn::createSharedMemory(constRefSize).value();
+        pools.push_back(pool);
+
+        // load data
+        const auto mappedMemory = nn::map(pool).value();
+        uint8_t* mappedPtr = static_cast<uint8_t*>(std::get<void*>(mappedMemory.pointer));
+        CHECK(mappedPtr != nullptr);
+
+        copyTestBuffers(constReferences, mappedPtr);
+    }
+
+    std::vector<Memory> aidlPools;
+    aidlPools.reserve(pools.size());
+    for (auto& pool : pools) {
+        auto aidlPool = utils::convert(pool).value();
+        aidlPools.push_back(std::move(aidlPool));
+    }
+
+    return {.main = std::move(mainSubgraph),
+            .referenced = std::move(refSubgraphs),
+            .operandValues = std::move(operandValues),
+            .pools = std::move(aidlPools),
+            .relaxComputationFloat32toFloat16 = testModel.isRelaxed};
+}
+
+static bool isOutputSizeGreaterThanOne(const TestModel& testModel, uint32_t index) {
+    const auto byteSize = testModel.main.operands[testModel.main.outputIndexes[index]].data.size();
+    return byteSize > 1u;
+}
+
+static void makeOutputInsufficientSize(uint32_t outputIndex, Request* request) {
+    auto& length = request->outputs[outputIndex].location.length;
+    ASSERT_GT(length, 1u);
+    length -= 1u;
+}
+
+static void makeOutputDimensionsUnspecified(Model* model) {
+    for (auto i : model->main.outputIndexes) {
+        auto& dims = model->main.operands[i].dimensions;
+        std::fill(dims.begin(), dims.end(), 0);
+    }
+}
+
+// Manages the lifetime of memory resources used in an execution.
+class ExecutionContext {
+  public:
+    ExecutionContext(std::shared_ptr<IDevice> device, std::shared_ptr<IPreparedModel> preparedModel)
+        : kDevice(std::move(device)), kPreparedModel(std::move(preparedModel)) {}
+
+    std::optional<Request> createRequest(const TestModel& testModel, MemoryType memoryType);
+    std::vector<TestBuffer> getOutputBuffers(const TestModel& testModel,
+                                             const Request& request) const;
+
+  private:
+    // Get a TestBuffer with data copied from an IBuffer object.
+    void getBuffer(const std::shared_ptr<IBuffer>& buffer, size_t size,
+                   TestBuffer* testBuffer) const;
+
+    static constexpr uint32_t kInputPoolIndex = 0;
+    static constexpr uint32_t kOutputPoolIndex = 1;
+    static constexpr uint32_t kDeviceMemoryBeginIndex = 2;
+
+    const std::shared_ptr<IDevice> kDevice;
+    const std::shared_ptr<IPreparedModel> kPreparedModel;
+    std::unique_ptr<TestMemoryBase> mInputMemory, mOutputMemory;
+    std::vector<std::shared_ptr<IBuffer>> mBuffers;
+};
+
+std::optional<Request> ExecutionContext::createRequest(const TestModel& testModel,
+                                                       MemoryType memoryType) {
+    // Memory pools are organized as:
+    // - 0: Input shared memory pool
+    // - 1: Output shared memory pool
+    // - [2, 2+i): Input device memories
+    // - [2+i, 2+i+o): Output device memories
+    DeviceMemoryAllocator allocator(kDevice, kPreparedModel, testModel);
+    std::vector<int32_t> tokens;
+    mBuffers.clear();
+
+    // Model inputs.
+    std::vector<RequestArgument> inputs(testModel.main.inputIndexes.size());
+    size_t inputSize = 0;
+    for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
+        const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]];
+        if (op.data.size() == 0) {
+            // Omitted input.
+            inputs[i] = {.hasNoValue = true};
+            continue;
+        } else if (memoryType == MemoryType::DEVICE) {
+            SCOPED_TRACE("Input index = " + std::to_string(i));
+            auto [buffer, token] = allocator.allocate<IOType::INPUT>(i);
+            if (buffer != nullptr) {
+                DataLocation loc = {.poolIndex = static_cast<int32_t>(mBuffers.size() +
+                                                                      kDeviceMemoryBeginIndex)};
+                mBuffers.push_back(std::move(buffer));
+                tokens.push_back(token);
+                inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+                continue;
+            }
+        }
+
+        // Reserve shared memory for input.
+        DataLocation loc = {.poolIndex = kInputPoolIndex,
+                            .offset = static_cast<int64_t>(inputSize),
+                            .length = static_cast<int64_t>(op.data.size())};
+        inputSize += op.data.alignedSize();
+        inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+    }
+
+    // Model outputs.
+    std::vector<RequestArgument> outputs(testModel.main.outputIndexes.size());
+    size_t outputSize = 0;
+    for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) {
+        const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]];
+        if (memoryType == MemoryType::DEVICE) {
+            SCOPED_TRACE("Output index = " + std::to_string(i));
+            auto [buffer, token] = allocator.allocate<IOType::OUTPUT>(i);
+            if (buffer != nullptr) {
+                DataLocation loc = {.poolIndex = static_cast<int32_t>(mBuffers.size() +
+                                                                      kDeviceMemoryBeginIndex)};
+                mBuffers.push_back(std::move(buffer));
+                tokens.push_back(token);
+                outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+                continue;
+            }
+        }
+
+        // In the case of zero-sized output, we should at least provide a one-byte buffer.
+        // This is because zero-sized tensors are only supported internally to the driver, or
+        // reported in output shapes. It is illegal for the client to pre-specify a zero-sized
+        // tensor as model output. Otherwise, we will have two semantic conflicts:
+        // - "Zero dimension" conflicts with "unspecified dimension".
+        // - "Omitted operand buffer" conflicts with "zero-sized operand buffer".
+        size_t bufferSize = std::max<size_t>(op.data.size(), 1);
+
+        // Reserve shared memory for output.
+        DataLocation loc = {.poolIndex = kOutputPoolIndex,
+                            .offset = static_cast<int64_t>(outputSize),
+                            .length = static_cast<int64_t>(bufferSize)};
+        outputSize += op.data.size() == 0 ? TestBuffer::kAlignment : op.data.alignedSize();
+        outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+    }
+
+    if (memoryType == MemoryType::DEVICE && mBuffers.empty()) {
+        return std::nullopt;
+    }
+
+    // Memory pools.
+    if (memoryType == MemoryType::BLOB_AHWB) {
+        mInputMemory = TestBlobAHWB::create(std::max<size_t>(inputSize, 1));
+        mOutputMemory = TestBlobAHWB::create(std::max<size_t>(outputSize, 1));
+    } else {
+        mInputMemory = TestAshmem::create(std::max<size_t>(inputSize, 1));
+        mOutputMemory = TestAshmem::create(std::max<size_t>(outputSize, 1));
+    }
+    CHECK_NE(mInputMemory, nullptr);
+    CHECK_NE(mOutputMemory, nullptr);
+    std::vector<RequestMemoryPool> pools;
+    pools.reserve(kDeviceMemoryBeginIndex + mBuffers.size());
+
+    auto copiedInputMemory = utils::clone(*mInputMemory->getAidlMemory());
+    CHECK(copiedInputMemory.has_value()) << copiedInputMemory.error().message;
+    auto copiedOutputMemory = utils::clone(*mOutputMemory->getAidlMemory());
+    CHECK(copiedOutputMemory.has_value()) << copiedOutputMemory.error().message;
+
+    pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::pool>(
+            std::move(copiedInputMemory).value()));
+    pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::pool>(
+            std::move(copiedOutputMemory).value()));
+    for (const auto& token : tokens) {
+        pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::token>(token));
+    }
+
+    // Copy input data to the input shared memory pool.
+    uint8_t* inputPtr = mInputMemory->getPointer();
+    for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
+        if (!inputs[i].hasNoValue && inputs[i].location.poolIndex == kInputPoolIndex) {
+            const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]];
+            const uint8_t* begin = op.data.get<uint8_t>();
+            const uint8_t* end = begin + op.data.size();
+            std::copy(begin, end, inputPtr + inputs[i].location.offset);
+        }
+    }
+    return Request{
+            .inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)};
+}
+
+std::vector<TestBuffer> ExecutionContext::getOutputBuffers(const TestModel& testModel,
+                                                           const Request& request) const {
+    // Copy out output results.
+    uint8_t* outputPtr = mOutputMemory->getPointer();
+    std::vector<TestBuffer> outputBuffers;
+    for (uint32_t i = 0; i < request.outputs.size(); i++) {
+        const auto& outputLoc = request.outputs[i].location;
+        if (outputLoc.poolIndex == kOutputPoolIndex) {
+            outputBuffers.emplace_back(outputLoc.length, outputPtr + outputLoc.offset);
+        } else {
+            const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]];
+            if (op.data.size() == 0) {
+                outputBuffers.emplace_back(0, nullptr);
+            } else {
+                SCOPED_TRACE("Output index = " + std::to_string(i));
+                const uint32_t bufferIndex = outputLoc.poolIndex - kDeviceMemoryBeginIndex;
+                TestBuffer buffer;
+                getBuffer(mBuffers[bufferIndex], op.data.size(), &buffer);
+                outputBuffers.push_back(std::move(buffer));
+            }
+        }
+    }
+    return outputBuffers;
+}
+
+// Get a TestBuffer with data copied from an IBuffer object.
+void ExecutionContext::getBuffer(const std::shared_ptr<IBuffer>& buffer, size_t size,
+                                 TestBuffer* testBuffer) const {
+    // IBuffer -> Shared memory.
+    auto sharedMemory = nn::createSharedMemory(size).value();
+    auto aidlMemory = utils::convert(sharedMemory).value();
+    const auto ret = buffer->copyTo(aidlMemory);
+    ASSERT_TRUE(ret.isOk());
+
+    // Shared memory -> TestBuffer.
+    const auto outputMemory = nn::map(sharedMemory).value();
+    const uint8_t* outputPtr = std::visit(
+            [](auto* ptr) { return static_cast<const uint8_t*>(ptr); }, outputMemory.pointer);
+    ASSERT_NE(outputPtr, nullptr);
+    ASSERT_NE(testBuffer, nullptr);
+    *testBuffer = TestBuffer(size, outputPtr);
+}
+
+static bool hasZeroSizedOutput(const TestModel& testModel) {
+    return std::any_of(testModel.main.outputIndexes.begin(), testModel.main.outputIndexes.end(),
+                       [&testModel](uint32_t index) {
+                           return testModel.main.operands[index].data.size() == 0;
+                       });
+}
+
+void EvaluatePreparedModel(const std::shared_ptr<IDevice>& device,
+                           const std::shared_ptr<IPreparedModel>& preparedModel,
+                           const TestModel& testModel, const TestConfig& testConfig,
+                           bool* skipped = nullptr) {
+    if (skipped != nullptr) {
+        *skipped = false;
+    }
+    // If output0 does not have size larger than one byte, we can not test with insufficient buffer.
+    if (testConfig.outputType == OutputType::INSUFFICIENT &&
+        !isOutputSizeGreaterThanOne(testModel, 0)) {
+        return;
+    }
+
+    ExecutionContext context(device, preparedModel);
+    auto maybeRequest = context.createRequest(testModel, testConfig.memoryType);
+    // Skip if testing memory domain but no device memory has been allocated.
+    if (!maybeRequest.has_value()) {
+        return;
+    }
+
+    Request request = std::move(maybeRequest).value();
+
+    constexpr uint32_t kInsufficientOutputIndex = 0;
+    if (testConfig.outputType == OutputType::INSUFFICIENT) {
+        makeOutputInsufficientSize(kInsufficientOutputIndex, &request);
+    }
+
+    int64_t loopTimeoutDuration = kOmittedTimeoutDuration;
+    // OutputType::MISSED_DEADLINE is only used by
+    // TestKind::INTINITE_LOOP_TIMEOUT tests to verify that an infinite loop is
+    // aborted after a timeout.
+    if (testConfig.outputType == OutputType::MISSED_DEADLINE) {
+        // Override the default loop timeout duration with a small value to
+        // speed up test execution.
+        constexpr int64_t kMillisecond = 1'000'000;
+        loopTimeoutDuration = 1 * kMillisecond;
+    }
+
+    ErrorStatus executionStatus;
+    std::vector<OutputShape> outputShapes;
+    Timing timing = kNoTiming;
+    switch (testConfig.executor) {
+        case Executor::SYNC: {
+            SCOPED_TRACE("synchronous");
+
+            ExecutionResult executionResult;
+            // execute
+            const auto ret = preparedModel->executeSynchronously(request, testConfig.measureTiming,
+                                                                 kNoDeadline, loopTimeoutDuration,
+                                                                 &executionResult);
+            ASSERT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC)
+                    << ret.getDescription();
+            if (ret.isOk()) {
+                executionStatus = executionResult.outputSufficientSize
+                                          ? ErrorStatus::NONE
+                                          : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE;
+                outputShapes = std::move(executionResult.outputShapes);
+                timing = executionResult.timing;
+            } else {
+                executionStatus = static_cast<ErrorStatus>(ret.getServiceSpecificError());
+            }
+            break;
+        }
+        case Executor::FENCED: {
+            SCOPED_TRACE("fenced");
+            ErrorStatus result = ErrorStatus::NONE;
+            ndk::ScopedFileDescriptor syncFenceFd;
+            std::shared_ptr<IFencedExecutionCallback> fencedCallback;
+            auto ret = preparedModel->executeFenced(request, {}, testConfig.measureTiming,
+                                                    kNoDeadline, loopTimeoutDuration, kNoDuration,
+                                                    &syncFenceFd, &fencedCallback);
+            ASSERT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC)
+                    << ret.getDescription();
+            if (!ret.isOk()) {
+                result = static_cast<ErrorStatus>(ret.getServiceSpecificError());
+                executionStatus = result;
+            } else if (syncFenceFd.get() != -1) {
+                std::vector<ndk::ScopedFileDescriptor> waitFor;
+                auto dupFd = dup(syncFenceFd.get());
+                ASSERT_NE(dupFd, -1);
+                waitFor.emplace_back(dupFd);
+                // If a sync fence is returned, try start another run waiting for the sync fence.
+                ret = preparedModel->executeFenced(request, waitFor, testConfig.measureTiming,
+                                                   kNoDeadline, loopTimeoutDuration, kNoDuration,
+                                                   &syncFenceFd, &fencedCallback);
+                ASSERT_TRUE(ret.isOk());
+                waitForSyncFence(syncFenceFd.get());
+            }
+            if (result == ErrorStatus::NONE) {
+                ASSERT_NE(fencedCallback, nullptr);
+                Timing timingFenced;
+                auto ret =
+                        fencedCallback->getExecutionInfo(&timing, &timingFenced, &executionStatus);
+                ASSERT_TRUE(ret.isOk());
+            }
+            break;
+        }
+        default: {
+            FAIL() << "Unsupported execution mode for AIDL interface.";
+        }
+    }
+
+    if (testConfig.outputType != OutputType::FULLY_SPECIFIED &&
+        executionStatus == ErrorStatus::GENERAL_FAILURE) {
+        if (skipped != nullptr) {
+            *skipped = true;
+        }
+        if (!testConfig.reportSkipping) {
+            return;
+        }
+        LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
+                     "execute model that it does not support.";
+        std::cout << "[          ]   Early termination of test because vendor service cannot "
+                     "execute model that it does not support."
+                  << std::endl;
+        GTEST_SKIP();
+    }
+    if (!testConfig.measureTiming) {
+        EXPECT_EQ(timing, kNoTiming);
+    } else {
+        if (timing.timeOnDevice != -1 && timing.timeInDriver != -1) {
+            EXPECT_LE(timing.timeOnDevice, timing.timeInDriver);
+        }
+    }
+
+    switch (testConfig.outputType) {
+        case OutputType::FULLY_SPECIFIED:
+            if (testConfig.executor == Executor::FENCED && hasZeroSizedOutput(testModel)) {
+                // Executor::FENCED does not support zero-sized output.
+                ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus);
+                return;
+            }
+            // If the model output operands are fully specified, outputShapes must be either
+            // either empty, or have the same number of elements as the number of outputs.
+            ASSERT_EQ(ErrorStatus::NONE, executionStatus);
+            ASSERT_TRUE(outputShapes.size() == 0 ||
+                        outputShapes.size() == testModel.main.outputIndexes.size());
+            break;
+        case OutputType::UNSPECIFIED:
+            if (testConfig.executor == Executor::FENCED) {
+                // For Executor::FENCED, the output shape must be fully specified.
+                ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus);
+                return;
+            }
+            // If the model output operands are not fully specified, outputShapes must have
+            // the same number of elements as the number of outputs.
+            ASSERT_EQ(ErrorStatus::NONE, executionStatus);
+            ASSERT_EQ(outputShapes.size(), testModel.main.outputIndexes.size());
+            break;
+        case OutputType::INSUFFICIENT:
+            if (testConfig.executor == Executor::FENCED) {
+                // For Executor::FENCED, the output shape must be fully specified.
+                ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus);
+                return;
+            }
+            ASSERT_EQ(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, executionStatus);
+            ASSERT_EQ(outputShapes.size(), testModel.main.outputIndexes.size());
+            // Check that all returned output dimensions are at least as fully specified as the
+            // union of the information about the corresponding operand in the model and in the
+            // request. In this test, all model outputs have known rank with all dimensions
+            // unspecified, and no dimensional information is provided in the request.
+            for (uint32_t i = 0; i < outputShapes.size(); i++) {
+                ASSERT_EQ(outputShapes[i].isSufficient, i != kInsufficientOutputIndex);
+                const auto& actual = outputShapes[i].dimensions;
+                const auto& golden =
+                        testModel.main.operands[testModel.main.outputIndexes[i]].dimensions;
+                ASSERT_EQ(actual.size(), golden.size());
+                for (uint32_t j = 0; j < actual.size(); j++) {
+                    if (actual[j] == 0) continue;
+                    EXPECT_EQ(actual[j], golden[j]) << "index: " << j;
+                }
+            }
+            return;
+        case OutputType::MISSED_DEADLINE:
+            ASSERT_TRUE(executionStatus == ErrorStatus::MISSED_DEADLINE_TRANSIENT ||
+                        executionStatus == ErrorStatus::MISSED_DEADLINE_PERSISTENT)
+                    << "executionStatus = " << executionStatus;
+            return;
+    }
+
+    // Go through all outputs, check returned output shapes.
+    for (uint32_t i = 0; i < outputShapes.size(); i++) {
+        EXPECT_TRUE(outputShapes[i].isSufficient);
+        const auto& expect = testModel.main.operands[testModel.main.outputIndexes[i]].dimensions;
+        const auto unsignedActual = nn::toUnsigned(outputShapes[i].dimensions);
+        ASSERT_TRUE(unsignedActual.has_value());
+        const std::vector<uint32_t>& actual = unsignedActual.value();
+        EXPECT_EQ(expect, actual);
+    }
+
+    // Retrieve execution results.
+    const std::vector<TestBuffer> outputs = context.getOutputBuffers(testModel, request);
+
+    // We want "close-enough" results.
+    checkResults(testModel, outputs);
+}
+
+void EvaluatePreparedModel(const std::shared_ptr<IDevice>& device,
+                           const std::shared_ptr<IPreparedModel>& preparedModel,
+                           const TestModel& testModel, TestKind testKind) {
+    std::vector<OutputType> outputTypesList;
+    std::vector<bool> measureTimingList;
+    std::vector<Executor> executorList;
+    std::vector<MemoryType> memoryTypeList;
+
+    switch (testKind) {
+        case TestKind::GENERAL: {
+            outputTypesList = {OutputType::FULLY_SPECIFIED};
+            measureTimingList = {false, true};
+            executorList = {Executor::SYNC};
+            memoryTypeList = {MemoryType::ASHMEM};
+        } break;
+        case TestKind::DYNAMIC_SHAPE: {
+            outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};
+            measureTimingList = {false, true};
+            executorList = {Executor::SYNC, Executor::FENCED};
+            memoryTypeList = {MemoryType::ASHMEM};
+        } break;
+        case TestKind::MEMORY_DOMAIN: {
+            outputTypesList = {OutputType::FULLY_SPECIFIED};
+            measureTimingList = {false};
+            executorList = {Executor::SYNC, Executor::FENCED};
+            memoryTypeList = {MemoryType::BLOB_AHWB, MemoryType::DEVICE};
+        } break;
+        case TestKind::FENCED_COMPUTE: {
+            outputTypesList = {OutputType::FULLY_SPECIFIED};
+            measureTimingList = {false, true};
+            executorList = {Executor::FENCED};
+            memoryTypeList = {MemoryType::ASHMEM};
+        } break;
+        case TestKind::QUANTIZATION_COUPLING: {
+            LOG(FATAL) << "Wrong TestKind for EvaluatePreparedModel";
+            return;
+        } break;
+        case TestKind::INTINITE_LOOP_TIMEOUT: {
+            outputTypesList = {OutputType::MISSED_DEADLINE};
+            measureTimingList = {false, true};
+            executorList = {Executor::SYNC, Executor::FENCED};
+            memoryTypeList = {MemoryType::ASHMEM};
+        } break;
+    }
+
+    for (const OutputType outputType : outputTypesList) {
+        for (const bool measureTiming : measureTimingList) {
+            for (const Executor executor : executorList) {
+                for (const MemoryType memoryType : memoryTypeList) {
+                    const TestConfig testConfig(executor, measureTiming, outputType, memoryType);
+                    EvaluatePreparedModel(device, preparedModel, testModel, testConfig);
+                }
+            }
+        }
+    }
+}
+
+void EvaluatePreparedCoupledModels(const std::shared_ptr<IDevice>& device,
+                                   const std::shared_ptr<IPreparedModel>& preparedModel,
+                                   const TestModel& testModel,
+                                   const std::shared_ptr<IPreparedModel>& preparedCoupledModel,
+                                   const TestModel& coupledModel) {
+    const std::vector<OutputType> outputTypesList = {OutputType::FULLY_SPECIFIED};
+    const std::vector<bool> measureTimingList = {false, true};
+    const std::vector<Executor> executorList = {Executor::SYNC, Executor::FENCED};
+
+    for (const OutputType outputType : outputTypesList) {
+        for (const bool measureTiming : measureTimingList) {
+            for (const Executor executor : executorList) {
+                const TestConfig testConfig(executor, measureTiming, outputType, MemoryType::ASHMEM,
+                                            /*reportSkipping=*/false);
+                bool baseSkipped = false;
+                EvaluatePreparedModel(device, preparedModel, testModel, testConfig, &baseSkipped);
+                bool coupledSkipped = false;
+                EvaluatePreparedModel(device, preparedCoupledModel, coupledModel, testConfig,
+                                      &coupledSkipped);
+                ASSERT_EQ(baseSkipped, coupledSkipped);
+                if (baseSkipped) {
+                    LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
+                                 "execute model that it does not support.";
+                    std::cout << "[          ]   Early termination of test because vendor service "
+                                 "cannot "
+                                 "execute model that it does not support."
+                              << std::endl;
+                    GTEST_SKIP();
+                }
+            }
+        }
+    }
+}
+
+void Execute(const std::shared_ptr<IDevice>& device, const TestModel& testModel,
+             TestKind testKind) {
+    Model model = createModel(testModel);
+    if (testKind == TestKind::DYNAMIC_SHAPE) {
+        makeOutputDimensionsUnspecified(&model);
+    }
+
+    std::shared_ptr<IPreparedModel> preparedModel;
+    switch (testKind) {
+        case TestKind::GENERAL:
+        case TestKind::DYNAMIC_SHAPE:
+        case TestKind::MEMORY_DOMAIN:
+        case TestKind::FENCED_COMPUTE:
+        case TestKind::INTINITE_LOOP_TIMEOUT: {
+            createPreparedModel(device, model, &preparedModel);
+            if (preparedModel == nullptr) return;
+            EvaluatePreparedModel(device, preparedModel, testModel, testKind);
+        } break;
+        case TestKind::QUANTIZATION_COUPLING: {
+            ASSERT_TRUE(testModel.hasQuant8CoupledOperands());
+            createPreparedModel(device, model, &preparedModel,
+                                /*reportSkipping*/ false);
+            TestModel signedQuantizedModel = convertQuant8AsymmOperandsToSigned(testModel);
+            std::shared_ptr<IPreparedModel> preparedCoupledModel;
+            createPreparedModel(device, createModel(signedQuantizedModel), &preparedCoupledModel,
+                                /*reportSkipping*/ false);
+            // If we couldn't prepare a model with unsigned quantization, we must
+            // fail to prepare a model with signed quantization as well.
+            if (preparedModel == nullptr) {
+                ASSERT_EQ(preparedCoupledModel, nullptr);
+                // If we failed to prepare both of the models, we can safely skip
+                // the test.
+                LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
+                             "prepare model that it does not support.";
+                std::cout
+                        << "[          ]   Early termination of test because vendor service cannot "
+                           "prepare model that it does not support."
+                        << std::endl;
+                GTEST_SKIP();
+            }
+            ASSERT_NE(preparedCoupledModel, nullptr);
+            EvaluatePreparedCoupledModels(device, preparedModel, testModel, preparedCoupledModel,
+                                          signedQuantizedModel);
+        } break;
+    }
+}
+
+void GeneratedTestBase::SetUp() {
+    testing::TestWithParam<GeneratedTestParam>::SetUp();
+    ASSERT_NE(kDevice, nullptr);
+}
+
+std::vector<NamedModel> getNamedModels(const FilterFn& filter) {
+    return TestModelManager::get().getTestModels(filter);
+}
+
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter) {
+    return TestModelManager::get().getTestModels(filter);
+}
+
+std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info) {
+    const auto& [namedDevice, namedModel] = info.param;
+    return gtestCompliantName(getName(namedDevice) + "_" + getName(namedModel));
+}
+
+// Tag for the generated tests
+class GeneratedTest : public GeneratedTestBase {};
+
+// Tag for the dynamic output shape tests
+class DynamicOutputShapeTest : public GeneratedTest {};
+
+// Tag for the memory domain tests
+class MemoryDomainTest : public GeneratedTest {};
+
+// Tag for the fenced compute tests
+class FencedComputeTest : public GeneratedTest {};
+
+// Tag for the dynamic output shape tests
+class QuantizationCouplingTest : public GeneratedTest {};
+
+// Tag for the loop timeout tests
+class InfiniteLoopTimeoutTest : public GeneratedTest {};
+
+TEST_P(GeneratedTest, Test) {
+    Execute(kDevice, kTestModel, TestKind::GENERAL);
+}
+
+TEST_P(DynamicOutputShapeTest, Test) {
+    Execute(kDevice, kTestModel, TestKind::DYNAMIC_SHAPE);
+}
+
+TEST_P(MemoryDomainTest, Test) {
+    Execute(kDevice, kTestModel, TestKind::MEMORY_DOMAIN);
+}
+
+TEST_P(FencedComputeTest, Test) {
+    Execute(kDevice, kTestModel, TestKind::FENCED_COMPUTE);
+}
+
+TEST_P(QuantizationCouplingTest, Test) {
+    Execute(kDevice, kTestModel, TestKind::QUANTIZATION_COUPLING);
+}
+
+TEST_P(InfiniteLoopTimeoutTest, Test) {
+    Execute(kDevice, kTestModel, TestKind::INTINITE_LOOP_TIMEOUT);
+}
+
+INSTANTIATE_GENERATED_TEST(GeneratedTest,
+                           [](const TestModel& testModel) { return !testModel.expectFailure; });
+
+INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest, [](const TestModel& testModel) {
+    return !testModel.expectFailure && !testModel.hasScalarOutputs();
+});
+
+INSTANTIATE_GENERATED_TEST(MemoryDomainTest,
+                           [](const TestModel& testModel) { return !testModel.expectFailure; });
+
+INSTANTIATE_GENERATED_TEST(FencedComputeTest,
+                           [](const TestModel& testModel) { return !testModel.expectFailure; });
+
+INSTANTIATE_GENERATED_TEST(QuantizationCouplingTest, [](const TestModel& testModel) {
+    return !testModel.expectFailure && testModel.hasQuant8CoupledOperands() &&
+           testModel.main.operations.size() == 1;
+});
+
+INSTANTIATE_GENERATED_TEST(InfiniteLoopTimeoutTest, [](const TestModel& testModel) {
+    return testModel.isInfiniteLoopTimeoutTest();
+});
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.h b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.h
new file mode 100644
index 0000000..ad40f06
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.h
@@ -0,0 +1,88 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_AIDL_GENERATED_TEST_HARNESS_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_AIDL_GENERATED_TEST_HARNESS_H
+
+#include <functional>
+#include <vector>
+
+#include <TestHarness.h>
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using NamedModel = Named<const test_helper::TestModel*>;
+using GeneratedTestParam = std::tuple<NamedDevice, NamedModel>;
+
+class GeneratedTestBase : public testing::TestWithParam<GeneratedTestParam> {
+  protected:
+    void SetUp() override;
+    const std::shared_ptr<IDevice> kDevice = getData(std::get<NamedDevice>(GetParam()));
+    const test_helper::TestModel& kTestModel = *getData(std::get<NamedModel>(GetParam()));
+};
+
+using FilterFn = std::function<bool(const test_helper::TestModel&)>;
+std::vector<NamedModel> getNamedModels(const FilterFn& filter);
+
+using FilterNameFn = std::function<bool(const std::string&)>;
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter);
+
+std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info);
+
+#define INSTANTIATE_GENERATED_TEST(TestSuite, filter)                                     \
+    GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(TestSuite);                             \
+    INSTANTIATE_TEST_SUITE_P(TestGenerated, TestSuite,                                    \
+                             testing::Combine(testing::ValuesIn(getNamedDevices()),       \
+                                              testing::ValuesIn(getNamedModels(filter))), \
+                             printGeneratedTest)
+
+// Tag for the validation tests, instantiated in VtsHalNeuralnetworks.cpp.
+// TODO: Clean up the hierarchy for ValidationTest.
+class ValidationTest : public GeneratedTestBase {};
+
+Model createModel(const test_helper::TestModel& testModel);
+
+void PrepareModel(const std::shared_ptr<IDevice>& device, const Model& model,
+                  std::shared_ptr<IPreparedModel>* preparedModel);
+
+enum class TestKind {
+    // Runs a test model and compares the results to a golden data
+    GENERAL,
+    // Same as GENERAL but sets dimensions for the output tensors to zeros
+    DYNAMIC_SHAPE,
+    // Same as GENERAL but use device memories for inputs and outputs
+    MEMORY_DOMAIN,
+    // Same as GENERAL but use executeFenced for exeuction
+    FENCED_COMPUTE,
+    // Tests if quantized model with TENSOR_QUANT8_ASYMM produces the same result
+    // (OK/SKIPPED/FAILED) as the model with all such tensors converted to
+    // TENSOR_QUANT8_ASYMM_SIGNED.
+    QUANTIZATION_COUPLING,
+    // Runs a test model and verifies that MISSED_DEADLINE_* is returned.
+    INTINITE_LOOP_TIMEOUT
+};
+
+void EvaluatePreparedModel(const std::shared_ptr<IDevice>& device,
+                           const std::shared_ptr<IPreparedModel>& preparedModel,
+                           const test_helper::TestModel& testModel, TestKind testKind);
+
+void waitForSyncFence(int syncFd);
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
+
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_AIDL_GENERATED_TEST_HARNESS_H
diff --git a/neuralnetworks/aidl/vts/functional/LogTestCaseToLogcat.h b/neuralnetworks/aidl/vts/functional/LogTestCaseToLogcat.h
new file mode 100644
index 0000000..c9fd432
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/LogTestCaseToLogcat.h
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_AIDL_LOG_TEST_CASE_TO_LOGCAT_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_AIDL_LOG_TEST_CASE_TO_LOGCAT_H
+
+#include <android-base/logging.h>
+#include <gtest/gtest.h>
+
+namespace aidl::android::hardware::neuralnetworks {
+
+class LogTestCaseToLogcat : public ::testing::EmptyTestEventListener {
+  public:
+    void OnTestStart(const ::testing::TestInfo& test_info) override {
+        LOG(INFO) << "[Test Case] " << test_info.test_suite_name() << "." << test_info.name()
+                  << " BEGIN";
+    }
+
+    void OnTestEnd(const ::testing::TestInfo& test_info) override {
+        LOG(INFO) << "[Test Case] " << test_info.test_suite_name() << "." << test_info.name()
+                  << " END";
+    }
+};
+
+}  // namespace aidl::android::hardware::neuralnetworks
+
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_AIDL_LOG_TEST_CASE_TO_LOGCAT_H
diff --git a/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp b/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
new file mode 100644
index 0000000..a37a0ca
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
@@ -0,0 +1,1176 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_aidl_hal_test"
+
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <android/binder_interface_utils.h>
+#include <android/binder_status.h>
+#include <gtest/gtest.h>
+
+#include <LegacyUtils.h>
+#include <TestHarness.h>
+#include <Utils.h>
+#include <nnapi/SharedMemory.h>
+#include <nnapi/hal/aidl/Conversions.h>
+#include <nnapi/hal/aidl/Utils.h>
+
+#include "AidlHalInterfaces.h"
+#include "Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "MemoryUtils.h"
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using namespace test_helper;
+using implementation::PreparedModelCallback;
+
+namespace {
+
+// An AIDL driver is likely to support at least one of the following operand types.
+const std::vector<TestOperandType> kTestOperandTypeChoicesVector = {
+        TestOperandType::TENSOR_FLOAT32,
+        TestOperandType::TENSOR_FLOAT16,
+        TestOperandType::TENSOR_QUANT8_ASYMM,
+        TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+};
+const auto kTestOperandTypeChoices = testing::ValuesIn(kTestOperandTypeChoicesVector);
+// TODO(b/179270601): restore kNamedDeviceChoices
+
+bool isInChoices(TestOperandType type) {
+    return std::count(kTestOperandTypeChoicesVector.begin(), kTestOperandTypeChoicesVector.end(),
+                      type) > 0;
+}
+
+bool isFloat(TestOperandType type) {
+    CHECK(isInChoices(type));
+    return type == TestOperandType::TENSOR_FLOAT32 || type == TestOperandType::TENSOR_FLOAT16;
+}
+
+// Create placeholder buffers for model constants as well as inputs and outputs.
+// We only care about the size here because we will not check accuracy in validation tests.
+void createDummyData(TestModel* testModel) {
+    for (auto& operand : testModel->main.operands) {
+        if (operand.data != nullptr) continue;
+        switch (operand.lifetime) {
+            case TestOperandLifeTime::SUBGRAPH_INPUT:
+            case TestOperandLifeTime::SUBGRAPH_OUTPUT:
+            case TestOperandLifeTime::CONSTANT_COPY:
+            case TestOperandLifeTime::CONSTANT_REFERENCE: {
+                const uint32_t size = nn::nonExtensionOperandSizeOfData(
+                        static_cast<nn::OperandType>(operand.type), operand.dimensions);
+                operand.data = TestBuffer(size);
+            } break;
+            default:
+                break;
+        }
+    }
+}
+
+TestOperand createInt32Scalar(int32_t value) {
+    return {
+            .type = TestOperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+            .data = TestBuffer::createFromVector<int32_t>({value}),
+    };
+}
+
+// Construct a test model with multiple CONV_2D operations with the given operand as inputs.
+// The dimensions of the filters are chosen to ensure outputs has the same dimensions as inputs.
+// We choose CONV_2D operation because it is commonly supported by most drivers.
+TestModel createConvModel(const TestOperand& operand, uint32_t numOperations) {
+    CHECK(isInChoices(operand.type));
+
+    TestOperand weight = {.type = operand.type,
+                          .dimensions = {operand.dimensions[3], 3, 3, operand.dimensions[3]},
+                          .numberOfConsumers = 1,
+                          .scale = isFloat(operand.type) ? 0.0f : 1.0f,
+                          .zeroPoint = 0,
+                          .lifetime = TestOperandLifeTime::CONSTANT_COPY};
+
+    TestOperand bias = {
+            .type = isFloat(operand.type) ? operand.type : TestOperandType::TENSOR_INT32,
+            .dimensions = {operand.dimensions[3]},
+            .numberOfConsumers = 1,
+            .scale = operand.scale * weight.scale,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::CONSTANT_COPY};
+
+    TestOperand output = operand;
+    output.numberOfConsumers = 0;
+    output.lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT;
+
+    const std::vector<TestOperand> operands = {
+            operand,
+            std::move(weight),
+            std::move(bias),
+            createInt32Scalar(1),  // same padding
+            createInt32Scalar(1),  // width stride
+            createInt32Scalar(1),  // height stride
+            createInt32Scalar(0),  // activation = NONE
+            std::move(output),
+    };
+
+    TestModel model;
+    for (uint32_t i = 0; i < numOperations; i++) {
+        model.main.operands.insert(model.main.operands.end(), operands.begin(), operands.end());
+        const uint32_t inputIndex = operands.size() * i;
+        const uint32_t outputIndex = inputIndex + operands.size() - 1;
+        std::vector<uint32_t> inputs(operands.size() - 1);
+        std::iota(inputs.begin(), inputs.end(), inputIndex);
+        model.main.operations.push_back({.type = TestOperationType::CONV_2D,
+                                         .inputs = std::move(inputs),
+                                         .outputs = {outputIndex}});
+        model.main.inputIndexes.push_back(inputIndex);
+        model.main.outputIndexes.push_back(outputIndex);
+    }
+    createDummyData(&model);
+    return model;
+}
+
+// Construct a test model with a single ADD operation with the given operand as input0 and input1.
+// This is to cover additional cases that the CONV_2D model does not support, e.g. arbitrary input
+// operand rank, scalar input operand. We choose ADD operation because it is commonly supported by
+// most drivers.
+TestModel createSingleAddModel(const TestOperand& operand) {
+    CHECK(isInChoices(operand.type));
+
+    TestOperand act = {
+            .type = TestOperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+    };
+
+    TestOperand output = operand;
+    output.numberOfConsumers = 0;
+    output.lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT;
+
+    TestModel model = {
+            .main =
+                    {
+                            .operands =
+                                    {
+                                            operand,
+                                            operand,
+                                            std::move(act),
+                                            output,
+                                    },
+                            .operations = {{.type = TestOperationType::ADD,
+                                            .inputs = {0, 1, 2},
+                                            .outputs = {3}}},
+                            .inputIndexes = {0, 1, 2},
+                            .outputIndexes = {3},
+                    },
+    };
+    createDummyData(&model);
+    return model;
+}
+
+// A placeholder invalid IPreparedModel class for MemoryDomainAllocateTest.InvalidPreparedModel
+class InvalidPreparedModel : public BnPreparedModel {
+  public:
+    ndk::ScopedAStatus executeSynchronously(const Request&, bool, int64_t, int64_t,
+                                            ExecutionResult*) override {
+        return ndk::ScopedAStatus::fromServiceSpecificError(
+                static_cast<int32_t>(ErrorStatus::GENERAL_FAILURE));
+    }
+    ndk::ScopedAStatus executeFenced(const Request&, const std::vector<ndk::ScopedFileDescriptor>&,
+                                     bool, int64_t, int64_t, int64_t, ndk::ScopedFileDescriptor*,
+                                     std::shared_ptr<IFencedExecutionCallback>*) override {
+        return ndk::ScopedAStatus::fromServiceSpecificError(
+                static_cast<int32_t>(ErrorStatus::GENERAL_FAILURE));
+    }
+};
+
+template <typename... Args>
+std::vector<RequestMemoryPool> createRequestMemoryPools(const Args&... pools) {
+    std::vector<RequestMemoryPool> memoryPools;
+    memoryPools.reserve(sizeof...(Args));
+    // This fold operator calls push_back on each of the function arguments.
+    (memoryPools.push_back(utils::clone(pools).value()), ...);
+    return memoryPools;
+};
+
+}  // namespace
+
+class MemoryDomainTestBase : public testing::Test {
+  protected:
+    MemoryDomainTestBase(std::shared_ptr<IDevice> device, TestOperandType type)
+        : kDevice(std::move(device)),
+          kTestOperandType(type),
+          kTestOperand(kTestOperandMap.at(type)),
+          kTestOperandDataSize(nn::nonExtensionOperandSizeOfData(static_cast<nn::OperandType>(type),
+                                                                 kTestOperand.dimensions)) {}
+
+    void SetUp() override {
+        testing::Test::SetUp();
+        ASSERT_NE(kDevice, nullptr);
+    }
+
+    std::shared_ptr<IPreparedModel> createConvPreparedModel(const TestOperand& testOperand,
+                                                            uint32_t numOperations = 1) {
+        const TestModel testModel = createConvModel(testOperand, numOperations);
+        const Model model = createModel(testModel);
+        std::shared_ptr<IPreparedModel> preparedModel;
+        createPreparedModel(kDevice, model, &preparedModel, /*reportSkipping=*/false);
+        return preparedModel;
+    }
+
+    std::shared_ptr<IPreparedModel> createAddPreparedModel(const TestOperand& testOperand) {
+        const TestModel testModel = createSingleAddModel(testOperand);
+        const Model model = createModel(testModel);
+        std::shared_ptr<IPreparedModel> preparedModel;
+        createPreparedModel(kDevice, model, &preparedModel, /*reportSkipping=*/false);
+        return preparedModel;
+    }
+
+    static const std::map<TestOperandType, TestOperand> kTestOperandMap;
+
+    const std::shared_ptr<IDevice> kDevice;
+    const TestOperandType kTestOperandType;
+    const TestOperand& kTestOperand;
+    const uint32_t kTestOperandDataSize;
+};
+
+const std::map<TestOperandType, TestOperand> MemoryDomainTestBase::kTestOperandMap = {
+        {TestOperandType::TENSOR_FLOAT32,
+         {
+                 .type = TestOperandType::TENSOR_FLOAT32,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.0f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+        {TestOperandType::TENSOR_FLOAT16,
+         {
+                 .type = TestOperandType::TENSOR_FLOAT16,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.0f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+        {TestOperandType::TENSOR_QUANT8_ASYMM,
+         {
+                 .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.5f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+        {TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+         {
+                 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.5f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+};
+
+using MemoryDomainAllocateTestParam = std::tuple<NamedDevice, TestOperandType>;
+class MemoryDomainAllocateTest : public MemoryDomainTestBase,
+                                 public testing::WithParamInterface<MemoryDomainAllocateTestParam> {
+  protected:
+    MemoryDomainAllocateTest()
+        : MemoryDomainTestBase(getData(std::get<NamedDevice>(GetParam())),
+                               std::get<TestOperandType>(GetParam())) {}
+
+    struct AllocateTestArgs {
+        std::vector<int32_t> dimensions;
+        std::vector<std::shared_ptr<IPreparedModel>> preparedModels;
+        std::vector<BufferRole> inputRoles;
+        std::vector<BufferRole> outputRoles;
+    };
+
+    // Validation test for IDevice::allocate. The driver is expected to fail with INVALID_ARGUMENT,
+    // or GENERAL_FAILURE if memory domain is not supported.
+    void validateAllocate(AllocateTestArgs args) {
+        std::vector<IPreparedModelParcel> preparedModelParcels;
+        preparedModelParcels.reserve(args.preparedModels.size());
+        for (const auto& model : args.preparedModels) {
+            preparedModelParcels.push_back({.preparedModel = model});
+        }
+        DeviceBuffer buffer;
+        const auto ret =
+                kDevice->allocate({.dimensions = std::move(args.dimensions)}, preparedModelParcels,
+                                  args.inputRoles, args.outputRoles, &buffer);
+
+        ASSERT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+        ASSERT_TRUE(static_cast<ErrorStatus>(ret.getServiceSpecificError()) ==
+                            ErrorStatus::INVALID_ARGUMENT ||
+                    static_cast<ErrorStatus>(ret.getServiceSpecificError()) ==
+                            ErrorStatus::GENERAL_FAILURE);
+    }
+
+    void testConflictOperands(const std::shared_ptr<IPreparedModel>& model1,
+                              const std::shared_ptr<IPreparedModel>& model2) {
+        validateAllocate({
+                .preparedModels = {model1, model2},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                               {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+        });
+        validateAllocate({
+                .preparedModels = {model1, model2},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+                .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+        });
+        validateAllocate({
+                .preparedModels = {model1, model2},
+                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                                {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+        });
+    }
+};
+
+TEST_P(MemoryDomainAllocateTest, EmptyRole) {
+    // Test with empty prepared models and roles.
+    validateAllocate({});
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // Test again with non-empty prepared models but empty roles.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, NullptrPreparedModel) {
+    // Test with nullptr prepared model as input role.
+    validateAllocate({
+            .preparedModels = {nullptr},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // Test with nullptr prepared model as output role.
+    validateAllocate({
+            .preparedModels = {nullptr},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidPreparedModel) {
+    std::shared_ptr<InvalidPreparedModel> invalidPreparedModel =
+            ndk::SharedRefBase::make<InvalidPreparedModel>();
+
+    // Test with invalid prepared model as input role.
+    validateAllocate({
+            .preparedModels = {invalidPreparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // Test with invalid prepared model as output role.
+    validateAllocate({
+            .preparedModels = {invalidPreparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidModelIndex) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // This should fail, because the model index is out of bound.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // This should fail, because the model index is out of bound.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidIOIndex) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // This should fail, because the model only has one input.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 1, .frequency = 1.0f}},
+    });
+
+    // This should fail, because the model only has one output.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 1, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidFrequency) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    for (float invalidFreq : {10.0f, 0.0f, -0.5f}) {
+        // Test with invalid frequency for input roles.
+        validateAllocate({
+                .preparedModels = {preparedModel},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = invalidFreq}},
+        });
+        // Test with invalid frequency for output roles.
+        validateAllocate({
+                .preparedModels = {preparedModel},
+                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = invalidFreq}},
+        });
+    }
+}
+
+TEST_P(MemoryDomainAllocateTest, SameRoleSpecifiedTwice) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // Same role with same model index.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                           {.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                            {.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // Different model indexes, but logically referring to the same role.
+    validateAllocate({
+            .preparedModels = {preparedModel, preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                           {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .preparedModels = {preparedModel, preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                            {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictOperandType) {
+    const std::map<TestOperandType, TestOperandType> conflictTypeMap = {
+            {TestOperandType::TENSOR_FLOAT32, TestOperandType::TENSOR_FLOAT16},
+            {TestOperandType::TENSOR_FLOAT16, TestOperandType::TENSOR_FLOAT32},
+            {TestOperandType::TENSOR_QUANT8_ASYMM, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+            {TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, TestOperandType::TENSOR_QUANT8_ASYMM},
+    };
+
+    TestOperand conflictTestOperand = kTestOperand;
+    const auto it = conflictTypeMap.find(kTestOperandType);
+    ASSERT_FALSE(it == conflictTypeMap.end());
+    conflictTestOperand.type = it->second;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictScale) {
+    if (isFloat(kTestOperandType)) return;
+
+    TestOperand conflictTestOperand = kTestOperand;
+    ASSERT_NE(conflictTestOperand.scale, 1.0f);
+    conflictTestOperand.scale = 1.0f;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictZeroPoint) {
+    if (isFloat(kTestOperandType)) return;
+
+    TestOperand conflictTestOperand = kTestOperand;
+    ASSERT_NE(conflictTestOperand.zeroPoint, 10);
+    conflictTestOperand.zeroPoint = 10;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictRankBetweenRoles) {
+    TestOperand conflictTestOperand = kTestOperand;
+    conflictTestOperand.dimensions.pop_back();
+
+    auto preparedModel = createAddPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createAddPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictDimensionsBetweenRoles) {
+    TestOperand conflictTestOperand = kTestOperand;
+    conflictTestOperand.dimensions[0] = 4;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictRankBetweenRoleAndDesc) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    auto badDimensions = utils::toSigned(kTestOperand.dimensions).value();
+    badDimensions.pop_back();
+
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictDimensionsBetweenRoleAndDesc) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    auto badDimensions = utils::toSigned(kTestOperand.dimensions).value();
+    badDimensions[0] = 4;
+
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictRankWithScalarRole) {
+    auto preparedModel = createAddPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // This should fail, because the target operand is a scalar but a non-empty dimension is
+    // specified.
+    validateAllocate({
+            .dimensions = {1},
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 2, .frequency = 1.0f}},
+    });
+}
+
+std::string printMemoryDomainAllocateTest(
+        const testing::TestParamInfo<MemoryDomainAllocateTestParam>& info) {
+    const auto& [namedDevice, operandType] = info.param;
+    const std::string type = toString(static_cast<OperandType>(operandType));
+    return gtestCompliantName(getName(namedDevice) + "_" + type);
+}
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(MemoryDomainAllocateTest);
+INSTANTIATE_TEST_SUITE_P(TestMemoryDomain, MemoryDomainAllocateTest,
+                         testing::Combine(testing::ValuesIn(getNamedDevices()),
+                                          kTestOperandTypeChoices),
+                         printMemoryDomainAllocateTest);
+
+class MemoryDomainCopyTestBase : public MemoryDomainTestBase {
+  protected:
+    MemoryDomainCopyTestBase(std::shared_ptr<IDevice> device, TestOperandType type)
+        : MemoryDomainTestBase(std::move(device), type) {}
+
+    // Allocates device memory for roles of a single prepared model.
+    // Returns {IBuffer, token} if success; returns {nullptr, 0} if not supported.
+    DeviceBuffer allocateBuffer(const std::shared_ptr<IPreparedModel>& preparedModel,
+                                const std::vector<int32_t>& inputIndexes,
+                                const std::vector<int32_t>& outputIndexes,
+                                const std::vector<int32_t>& dimensions) {
+        if (preparedModel == nullptr) {
+            return {.buffer = nullptr, .token = 0};
+        }
+
+        std::vector<BufferRole> inputRoles(inputIndexes.size()), outputRoles(outputIndexes.size());
+        auto trans = [](int32_t ind) -> BufferRole {
+            return {.modelIndex = 0, .ioIndex = ind, .frequency = 1.0f};
+        };
+        std::transform(inputIndexes.begin(), inputIndexes.end(), inputRoles.begin(), trans);
+        std::transform(outputIndexes.begin(), outputIndexes.end(), outputRoles.begin(), trans);
+
+        IPreparedModelParcel parcel;
+        parcel.preparedModel = preparedModel;
+
+        DeviceBuffer buffer;
+
+        const auto ret = kDevice->allocate({.dimensions = dimensions}, {parcel}, inputRoles,
+                                           outputRoles, &buffer);
+
+        if (!ret.isOk()) {
+            EXPECT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+            EXPECT_EQ(static_cast<ErrorStatus>(ret.getServiceSpecificError()),
+                      ErrorStatus::GENERAL_FAILURE);
+            return DeviceBuffer{
+                    .buffer = nullptr,
+                    .token = 0,
+            };
+        }
+
+        EXPECT_NE(buffer.buffer, nullptr);
+        EXPECT_GT(buffer.token, 0);
+
+        return buffer;
+    }
+
+    DeviceBuffer allocateBuffer(const std::shared_ptr<IPreparedModel>& preparedModel,
+                                const std::vector<int32_t>& inputIndexes,
+                                const std::vector<int32_t>& outputIndexes) {
+        return allocateBuffer(preparedModel, inputIndexes, outputIndexes, {});
+    }
+
+    Memory allocateSharedMemory(uint32_t size) {
+        const auto sharedMemory = nn::createSharedMemory(size).value();
+        auto memory = utils::convert(sharedMemory).value();
+        EXPECT_EQ(memory.size, size);
+        return memory;
+    }
+
+    void testCopyFrom(const std::shared_ptr<IBuffer>& buffer, const Memory& memory,
+                      const std::vector<int32_t>& dimensions, ErrorStatus expectedStatus) {
+        const auto ret = buffer->copyFrom(memory, dimensions);
+        if (expectedStatus == ErrorStatus::NONE) {
+            ASSERT_TRUE(ret.isOk());
+        } else {
+            ASSERT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+            ASSERT_EQ(expectedStatus, static_cast<ErrorStatus>(ret.getServiceSpecificError()));
+        }
+    }
+
+    void testCopyTo(const std::shared_ptr<IBuffer>& buffer, const Memory& memory,
+                    ErrorStatus expectedStatus) {
+        const auto ret = buffer->copyTo(memory);
+        if (expectedStatus == ErrorStatus::NONE) {
+            ASSERT_TRUE(ret.isOk());
+        } else {
+            ASSERT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+            ASSERT_EQ(expectedStatus, static_cast<ErrorStatus>(ret.getServiceSpecificError()));
+        }
+    }
+
+    void initializeDeviceMemory(const std::shared_ptr<IBuffer>& buffer) {
+        Memory memory = allocateSharedMemory(kTestOperandDataSize);
+        ASSERT_EQ(memory.size, kTestOperandDataSize);
+        testCopyFrom(buffer, memory, utils::toSigned(kTestOperand.dimensions).value(),
+                     ErrorStatus::NONE);
+    }
+};
+
+using MemoryDomainCopyTestParam = std::tuple<NamedDevice, TestOperandType>;
+class MemoryDomainCopyTest : public MemoryDomainCopyTestBase,
+                             public testing::WithParamInterface<MemoryDomainCopyTestParam> {
+  protected:
+    MemoryDomainCopyTest()
+        : MemoryDomainCopyTestBase(getData(std::get<NamedDevice>(GetParam())),
+                                   std::get<TestOperandType>(GetParam())) {}
+};
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidMemorySize) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    Memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    Memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    testCopyFrom(buffer, badMemory1, {}, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, badMemory2, {}, ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidMemorySize_DynamicShape) {
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    Memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    Memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    Memory goodMemory = allocateSharedMemory(kTestOperandDataSize);
+
+    const auto goodDimensions = utils::toSigned(kTestOperand.dimensions).value();
+    auto badDimensions = goodDimensions;
+    badDimensions[0] = 2;
+
+    testCopyFrom(buffer, badMemory1, goodDimensions, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, badMemory2, goodDimensions, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, goodMemory, goodDimensions, ErrorStatus::NONE);
+    testCopyFrom(buffer, goodMemory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidDimensions) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    Memory memory = allocateSharedMemory(kTestOperandDataSize);
+
+    const auto goodDimensions = utils::toSigned(kTestOperand.dimensions).value();
+    std::vector<int32_t> badDimensions = goodDimensions;
+    badDimensions.pop_back();
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = goodDimensions;
+    badDimensions[0] = 2;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = goodDimensions;
+    badDimensions[0] = 0;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    testCopyFrom(buffer, memory, {}, ErrorStatus::NONE);
+    testCopyFrom(buffer, memory, goodDimensions, ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidDimensions_DynamicShape) {
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    Memory memory = allocateSharedMemory(kTestOperandDataSize);
+
+    const auto goodDimensions = utils::toSigned(kTestOperand.dimensions).value();
+    std::vector<int32_t> badDimensions = goodDimensions;
+    badDimensions.pop_back();
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = goodDimensions;
+    badDimensions[0] = 2;
+    badDimensions[3] = 4;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = goodDimensions;
+    badDimensions[0] = 1;
+    badDimensions[3] = 0;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    testCopyFrom(buffer, memory, {}, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, memory, goodDimensions, ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyTo_UninitializedMemory) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    Memory memory = allocateSharedMemory(kTestOperandDataSize);
+    testCopyTo(buffer, memory, ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyTo_InvalidMemorySize) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    Memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    Memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    Memory goodMemory = allocateSharedMemory(kTestOperandDataSize);
+
+    initializeDeviceMemory(buffer);
+    testCopyTo(buffer, badMemory1, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, badMemory2, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, goodMemory, ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyTo_InvalidMemorySize_DynamicShape) {
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    Memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    Memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    Memory goodMemory = allocateSharedMemory(kTestOperandDataSize);
+
+    initializeDeviceMemory(buffer);
+    testCopyTo(buffer, badMemory1, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, badMemory2, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, goodMemory, ErrorStatus::NONE);
+}
+
+std::string printMemoryDomainCopyTest(
+        const testing::TestParamInfo<MemoryDomainCopyTestParam>& info) {
+    const auto& [namedDevice, operandType] = info.param;
+    const std::string type = toString(static_cast<OperandType>(operandType));
+    return gtestCompliantName(getName(namedDevice) + "_" + type);
+}
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(MemoryDomainCopyTest);
+INSTANTIATE_TEST_SUITE_P(TestMemoryDomain, MemoryDomainCopyTest,
+                         testing::Combine(testing::ValuesIn(getNamedDevices()),
+                                          kTestOperandTypeChoices),
+                         printMemoryDomainCopyTest);
+
+using MemoryDomainExecutionTestParam = std::tuple<NamedDevice, TestOperandType, Executor>;
+class MemoryDomainExecutionTest
+    : public MemoryDomainCopyTestBase,
+      public testing::WithParamInterface<MemoryDomainExecutionTestParam> {
+  protected:
+    MemoryDomainExecutionTest()
+        : MemoryDomainCopyTestBase(getData(std::get<NamedDevice>(GetParam())),
+                                   std::get<TestOperandType>(GetParam())) {}
+
+    RequestMemoryPool createSharedMemoryPool(uint32_t size) {
+        return RequestMemoryPool(allocateSharedMemory(size));
+    }
+
+    RequestMemoryPool createDeviceMemoryPool(uint32_t token) {
+        return RequestMemoryPool(static_cast<int32_t>(token));
+    }
+
+    void testExecution(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request,
+                       ErrorStatus expectedStatus) {
+        switch (kExecutor) {
+            case Executor::SYNC:
+                EXPECT_EQ(executeSync(preparedModel, request), expectedStatus);
+                break;
+            case Executor::FENCED:
+                EXPECT_EQ(executeFenced(preparedModel, request), expectedStatus);
+                break;
+            default:
+                ASSERT_TRUE(false);
+        }
+    }
+
+    ErrorStatus executeSync(const std::shared_ptr<IPreparedModel>& preparedModel,
+                            const Request& request) {
+        ExecutionResult executionResult;
+        const auto ret = preparedModel->executeSynchronously(
+                request, false, kNoDeadline, kOmittedTimeoutDuration, &executionResult);
+
+        if (!ret.isOk()) {
+            EXPECT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+            return static_cast<ErrorStatus>(ret.getServiceSpecificError());
+        }
+        const ErrorStatus executionStatus = executionResult.outputSufficientSize
+                                                    ? ErrorStatus::NONE
+                                                    : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE;
+        EXPECT_EQ(executionResult.timing, kNoTiming);
+        return executionStatus;
+    }
+
+    ErrorStatus executeFenced(const std::shared_ptr<IPreparedModel>& preparedModel,
+                              const Request& request) {
+        ndk::ScopedFileDescriptor syncFence;
+        std::shared_ptr<IFencedExecutionCallback> fencedCallback;
+        const auto ret = preparedModel->executeFenced(request, {}, false, kNoDeadline,
+                                                      kOmittedTimeoutDuration, kNoDuration,
+                                                      &syncFence, &fencedCallback);
+        if (!ret.isOk()) {
+            EXPECT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC);
+            return static_cast<ErrorStatus>(ret.getServiceSpecificError());
+        }
+        if (syncFence.get() != -1) {
+            waitForSyncFence(syncFence.get());
+        }
+        EXPECT_NE(fencedCallback, nullptr);
+
+        ErrorStatus executionStatus = ErrorStatus::GENERAL_FAILURE;
+        Timing time = kNoTiming;
+        Timing timeFenced = kNoTiming;
+        const auto retExecutionInfo =
+                fencedCallback->getExecutionInfo(&time, &timeFenced, &executionStatus);
+        EXPECT_TRUE(retExecutionInfo.isOk());
+        EXPECT_EQ(time, kNoTiming);
+        return executionStatus;
+    }
+
+    const Executor kExecutor = std::get<Executor>(GetParam());
+};
+
+TEST_P(MemoryDomainExecutionTest, InvalidToken) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    RequestMemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool badDeviceMemory1 = createDeviceMemoryPool(0);    // Invalid token.
+    RequestMemoryPool badDeviceMemory2 = createDeviceMemoryPool(100);  // Unknown token.
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, badDeviceMemory1)},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, badDeviceMemory2)},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, badDeviceMemory1)},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, badDeviceMemory2)},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidPreparedModel) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+    auto badPreparedModel = createConvPreparedModel(kTestOperand);
+    if (badPreparedModel == nullptr) return;
+
+    RequestMemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    // This should fail, because the buffer is not allocated for badPreparedModel.
+    initializeDeviceMemory(buffer);
+    testExecution(badPreparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(badPreparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidIOIndex) {
+    auto preparedModel = createConvPreparedModel(kTestOperand, 2);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {});
+    if (buffer == nullptr) return;
+
+    RequestMemoryPool sharedMemory1 = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool sharedMemory2 = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool sharedMemory3 = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg1 = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument sharedMemoryArg2 = {
+            .location = {.poolIndex = 1, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument sharedMemoryArg3 = {
+            .location = {.poolIndex = 2, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 3}};
+
+    // This should fail, because the device memory is not allocated for input 1.
+    initializeDeviceMemory(buffer);
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg1, deviceMemoryArg},
+                   .outputs = {sharedMemoryArg2, sharedMemoryArg3},
+                   .pools = createRequestMemoryPools(sharedMemory1, sharedMemory2, sharedMemory3,
+                                                     deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // This should fail, because the device memory is not allocated for output 1.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg1, sharedMemoryArg2},
+                   .outputs = {sharedMemoryArg3, deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory1, sharedMemory2, sharedMemory3,
+                                                     deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidIOType) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [inputBuffer, inputToken] = allocateBuffer(preparedModel, {0}, {});
+    auto [outputBuffer, outputToken] = allocateBuffer(preparedModel, {}, {0});
+    if (inputBuffer == nullptr || outputBuffer == nullptr) return;
+
+    RequestMemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool deviceMemory = createDeviceMemoryPool(inputToken);
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    // This should fail, because the device memory is allocated for input but used as output.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // This should fail, because the device memory is allocated for output but used as input.
+    deviceMemory.set<RequestMemoryPool::Tag::token>(outputToken);
+    initializeDeviceMemory(outputBuffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, UninitializedMemory) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    RequestMemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    // This should fail, because the device memory is not initialized.
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::GENERAL_FAILURE);
+
+    // This should initialize the device memory.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::NONE);
+
+    // Test again with initialized device memory.
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainExecutionTest, SameRequestMultipleRoles) {
+    auto preparedModel = createConvPreparedModel(kTestOperand, 2);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0, 1}, {0, 1});
+    if (buffer == nullptr) return;
+
+    RequestMemoryPool sharedMemory1 = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool sharedMemory2 = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg1 = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument sharedMemoryArg2 = {
+            .location = {.poolIndex = 1, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 2}};
+
+    // This should fail, because the same device memory cannot be used for both input and output.
+    initializeDeviceMemory(buffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg, sharedMemoryArg1},
+                   .outputs = {deviceMemoryArg, sharedMemoryArg2},
+                   .pools = createRequestMemoryPools(sharedMemory1, sharedMemory2, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // This should fail, because the same device memory cannot be used for multiple outputs.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg1, sharedMemoryArg2},
+                   .outputs = {deviceMemoryArg, deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory1, sharedMemory2, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // The same device memory can be used for multiple inputs.
+    initializeDeviceMemory(buffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg, deviceMemoryArg},
+                   .outputs = {sharedMemoryArg1, sharedMemoryArg2},
+                   .pools = createRequestMemoryPools(sharedMemory1, sharedMemory2, deviceMemory)},
+                  ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidDimensions) {
+    // FENCED execution does not support dynamic shape.
+    if (kExecutor == Executor::FENCED) return;
+
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto deviceBuffer = allocateBuffer(preparedModel, {0}, {0},
+                                       utils::toSigned(kTestOperand.dimensions).value());
+    if (deviceBuffer.buffer == nullptr) return;
+
+    RequestMemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    RequestMemoryPool deviceMemory = createDeviceMemoryPool(deviceBuffer.token);
+    auto badDimensions = utils::toSigned(kTestOperand.dimensions).value();
+    badDimensions[0] = 2;
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize},
+            .dimensions = badDimensions};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+    RequestArgument deviceMemoryArgWithBadDimensions = {.location = {.poolIndex = 1},
+                                                        .dimensions = badDimensions};
+
+    initializeDeviceMemory(deviceBuffer.buffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArgWithBadDimensions},
+                   .outputs = {sharedMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArgWithBadDimensions},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = createRequestMemoryPools(sharedMemory, deviceMemory)},
+                  ErrorStatus::GENERAL_FAILURE);
+}
+
+const auto kExecutorChoices = testing::Values(Executor::SYNC, Executor::FENCED);
+
+std::string printMemoryDomainExecutionTest(
+        const testing::TestParamInfo<MemoryDomainExecutionTestParam>& info) {
+    const auto& [namedDevice, operandType, executor] = info.param;
+    const std::string type = toString(static_cast<OperandType>(operandType));
+    const std::string executorStr = toString(executor);
+    return gtestCompliantName(getName(namedDevice) + "_" + type + "_" + executorStr);
+}
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(MemoryDomainExecutionTest);
+INSTANTIATE_TEST_SUITE_P(TestMemoryDomain, MemoryDomainExecutionTest,
+                         testing::Combine(testing::ValuesIn(getNamedDevices()),
+                                          kTestOperandTypeChoices, kExecutorChoices),
+                         printMemoryDomainExecutionTest);
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/QualityOfServiceTests.cpp b/neuralnetworks/aidl/vts/functional/QualityOfServiceTests.cpp
new file mode 100644
index 0000000..58db98f
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/QualityOfServiceTests.cpp
@@ -0,0 +1,270 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <android/binder_enums.h>
+#include <android/binder_interface_utils.h>
+#include <android/binder_status.h>
+
+#include <nnapi/hal/aidl/Conversions.h>
+
+#include "Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "Utils.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using implementation::PreparedModelCallback;
+using test_helper::TestBuffer;
+using test_helper::TestModel;
+
+enum class DeadlineBoundType { NOW, UNLIMITED, SHORT };
+constexpr std::array<DeadlineBoundType, 3> deadlineBounds = {
+        DeadlineBoundType::NOW, DeadlineBoundType::UNLIMITED, DeadlineBoundType::SHORT};
+std::string toString(DeadlineBoundType type) {
+    switch (type) {
+        case DeadlineBoundType::NOW:
+            return "NOW";
+        case DeadlineBoundType::UNLIMITED:
+            return "UNLIMITED";
+        case DeadlineBoundType::SHORT:
+            return "SHORT";
+    }
+    LOG(FATAL) << "Unrecognized DeadlineBoundType: " << static_cast<int>(type);
+    return {};
+}
+
+constexpr auto kShortDuration = std::chrono::milliseconds{5};
+
+using Results = std::tuple<ErrorStatus, std::vector<OutputShape>, Timing>;
+using MaybeResults = std::optional<Results>;
+
+static int64_t makeDeadline(DeadlineBoundType deadlineBoundType) {
+    const auto getNanosecondsSinceEpoch = [](const auto& time) -> int64_t {
+        const auto timeSinceEpoch = time.time_since_epoch();
+        return std::chrono::duration_cast<std::chrono::nanoseconds>(timeSinceEpoch).count();
+    };
+
+    std::chrono::steady_clock::time_point timePoint;
+    switch (deadlineBoundType) {
+        case DeadlineBoundType::NOW:
+            timePoint = std::chrono::steady_clock::now();
+            break;
+        case DeadlineBoundType::UNLIMITED:
+            timePoint = std::chrono::steady_clock::time_point::max();
+            break;
+        case DeadlineBoundType::SHORT:
+            timePoint = std::chrono::steady_clock::now() + kShortDuration;
+            break;
+    }
+
+    return getNanosecondsSinceEpoch(timePoint);
+}
+
+void runPrepareModelTest(const std::shared_ptr<IDevice>& device, const Model& model,
+                         Priority priority, std::optional<DeadlineBoundType> deadlineBound) {
+    int64_t deadline = kNoDeadline;
+    if (deadlineBound.has_value()) {
+        deadline = makeDeadline(deadlineBound.value());
+    }
+
+    // see if service can handle model
+    std::vector<bool> supportedOps;
+    const auto supportedCallStatus = device->getSupportedOperations(model, &supportedOps);
+    ASSERT_TRUE(supportedCallStatus.isOk());
+    ASSERT_NE(0ul, supportedOps.size());
+    const bool fullySupportsModel =
+            std::all_of(supportedOps.begin(), supportedOps.end(), [](bool valid) { return valid; });
+
+    // launch prepare model
+    const std::shared_ptr<PreparedModelCallback> preparedModelCallback =
+            ndk::SharedRefBase::make<PreparedModelCallback>();
+    const auto prepareLaunchStatus =
+            device->prepareModel(model, ExecutionPreference::FAST_SINGLE_ANSWER, priority, deadline,
+                                 {}, {}, kEmptyCacheToken, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk())
+            << "prepareLaunchStatus: " << prepareLaunchStatus.getDescription();
+
+    // retrieve prepared model
+    preparedModelCallback->wait();
+    const ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    const std::shared_ptr<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+
+    // The getSupportedOperations call returns a list of operations that are guaranteed not to fail
+    // if prepareModel is called, and 'fullySupportsModel' is true i.f.f. the entire model is
+    // guaranteed. If a driver has any doubt that it can prepare an operation, it must return false.
+    // So here, if a driver isn't sure if it can support an operation, but reports that it
+    // successfully prepared the model, the test can continue.
+    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
+        ASSERT_EQ(nullptr, preparedModel.get());
+        return;
+    }
+
+    // verify return status
+    if (!deadlineBound.has_value()) {
+        EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    } else {
+        switch (deadlineBound.value()) {
+            case DeadlineBoundType::NOW:
+            case DeadlineBoundType::SHORT:
+                // Either the driver successfully completed the task or it
+                // aborted and returned MISSED_DEADLINE_*.
+                EXPECT_TRUE(prepareReturnStatus == ErrorStatus::NONE ||
+                            prepareReturnStatus == ErrorStatus::MISSED_DEADLINE_TRANSIENT ||
+                            prepareReturnStatus == ErrorStatus::MISSED_DEADLINE_PERSISTENT);
+                break;
+            case DeadlineBoundType::UNLIMITED:
+                // If an unlimited deadline is supplied, we expect the execution to
+                // proceed normally. In this case, check it normally by breaking out
+                // of the switch statement.
+                EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+                break;
+        }
+    }
+    ASSERT_EQ(prepareReturnStatus == ErrorStatus::NONE, preparedModel.get() != nullptr);
+}
+
+void runPrepareModelTests(const std::shared_ptr<IDevice>& device, const Model& model) {
+    // test priority
+    for (auto priority : ndk::enum_range<Priority>{}) {
+        SCOPED_TRACE("priority: " + toString(priority));
+        if (priority == kDefaultPriority) continue;
+        runPrepareModelTest(device, model, priority, {});
+    }
+
+    // test deadline
+    for (auto deadlineBound : deadlineBounds) {
+        SCOPED_TRACE("deadlineBound: " + toString(deadlineBound));
+        runPrepareModelTest(device, model, kDefaultPriority, deadlineBound);
+    }
+}
+
+static MaybeResults executeSynchronously(const std::shared_ptr<IPreparedModel>& preparedModel,
+                                         const Request& request, int64_t deadline) {
+    SCOPED_TRACE("synchronous");
+    const bool measure = false;
+
+    // run execution
+    ExecutionResult executionResult;
+    const auto ret = preparedModel->executeSynchronously(request, measure, deadline,
+                                                         kOmittedTimeoutDuration, &executionResult);
+    EXPECT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC)
+            << ret.getDescription();
+    if (!ret.isOk()) {
+        if (ret.getExceptionCode() != EX_SERVICE_SPECIFIC) {
+            return std::nullopt;
+        }
+        return MaybeResults(
+                {static_cast<ErrorStatus>(ret.getServiceSpecificError()), {}, kNoTiming});
+    }
+
+    // return results
+    return MaybeResults({executionResult.outputSufficientSize
+                                 ? ErrorStatus::NONE
+                                 : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE,
+                         std::move(executionResult.outputShapes), executionResult.timing});
+}
+
+void runExecutionTest(const std::shared_ptr<IPreparedModel>& preparedModel,
+                      const TestModel& testModel, const Request& request,
+                      const ExecutionContext& context, DeadlineBoundType deadlineBound) {
+    const auto deadline = makeDeadline(deadlineBound);
+
+    // Perform execution and unpack results.
+    const auto results = executeSynchronously(preparedModel, request, deadline);
+    if (!results.has_value()) return;
+    const auto& [status, outputShapes, timing] = results.value();
+
+    // Verify no timing information was returned
+    EXPECT_EQ(timing, kNoTiming);
+
+    // Validate deadline information if applicable.
+    switch (deadlineBound) {
+        case DeadlineBoundType::NOW:
+        case DeadlineBoundType::SHORT:
+            // Either the driver successfully completed the task or it
+            // aborted and returned MISSED_DEADLINE_*.
+            ASSERT_TRUE(status == ErrorStatus::NONE ||
+                        status == ErrorStatus::MISSED_DEADLINE_TRANSIENT ||
+                        status == ErrorStatus::MISSED_DEADLINE_PERSISTENT);
+            break;
+        case DeadlineBoundType::UNLIMITED:
+            // If an unlimited deadline is supplied, we expect the execution to
+            // proceed normally. In this case, check it normally by breaking out
+            // of the switch statement.
+            ASSERT_EQ(ErrorStatus::NONE, status);
+            break;
+    }
+
+    // If the model output operands are fully specified, outputShapes must be either
+    // either empty, or have the same number of elements as the number of outputs.
+    ASSERT_TRUE(outputShapes.size() == 0 ||
+                outputShapes.size() == testModel.main.outputIndexes.size());
+
+    // Go through all outputs, check returned output shapes.
+    for (uint32_t i = 0; i < outputShapes.size(); i++) {
+        EXPECT_TRUE(outputShapes[i].isSufficient);
+        const auto expect =
+                utils::toSigned(testModel.main.operands[testModel.main.outputIndexes[i]].dimensions)
+                        .value();
+        const std::vector<int32_t>& actual = outputShapes[i].dimensions;
+        EXPECT_EQ(expect, actual);
+    }
+
+    // Retrieve execution results.
+    const std::vector<TestBuffer> outputs = context.getOutputBuffers(request);
+
+    // We want "close-enough" results.
+    if (status == ErrorStatus::NONE) {
+        checkResults(testModel, outputs);
+    }
+}
+
+void runExecutionTests(const std::shared_ptr<IPreparedModel>& preparedModel,
+                       const TestModel& testModel, const Request& request,
+                       const ExecutionContext& context) {
+    for (auto deadlineBound : deadlineBounds) {
+        runExecutionTest(preparedModel, testModel, request, context, deadlineBound);
+    }
+}
+
+void runTests(const std::shared_ptr<IDevice>& device, const TestModel& testModel) {
+    // setup
+    const Model model = createModel(testModel);
+
+    // run prepare model tests
+    runPrepareModelTests(device, model);
+
+    // prepare model
+    std::shared_ptr<IPreparedModel> preparedModel;
+    createPreparedModel(device, model, &preparedModel);
+    if (preparedModel == nullptr) return;
+
+    // run execution tests
+    ExecutionContext context;
+    const Request request = context.createRequest(testModel);
+    runExecutionTests(preparedModel, testModel, request, context);
+}
+
+class DeadlineTest : public GeneratedTestBase {};
+
+TEST_P(DeadlineTest, Test) {
+    runTests(kDevice, kTestModel);
+}
+
+INSTANTIATE_GENERATED_TEST(DeadlineTest,
+                           [](const TestModel& testModel) { return !testModel.expectFailure; });
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/TestAssertions.cpp b/neuralnetworks/aidl/vts/functional/TestAssertions.cpp
new file mode 100644
index 0000000..a9e9456
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/TestAssertions.cpp
@@ -0,0 +1,153 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <aidl/android/hardware/neuralnetworks/IPreparedModel.h>
+#include <aidl/android/hardware/neuralnetworks/OperandType.h>
+#include <aidl/android/hardware/neuralnetworks/OperationType.h>
+
+#include <ControlFlow.h>
+#include <TestHarness.h>
+
+namespace aidl::android::hardware::neuralnetworks {
+
+namespace nn = ::android::nn;
+
+static_assert(static_cast<uint64_t>(IPreparedModel::DEFAULT_LOOP_TIMEOUT_DURATION_NS) ==
+              nn::operation_while::kTimeoutNsDefault);
+static_assert(static_cast<uint64_t>(IPreparedModel::MAXIMUM_LOOP_TIMEOUT_DURATION_NS) ==
+              nn::operation_while::kTimeoutNsMaximum);
+
+// Make sure that the HIDL enums are compatible with the values defined in
+// frameworks/ml/nn/tools/test_generator/test_harness/include/TestHarness.h.
+using namespace test_helper;
+#define CHECK_TEST_ENUM(EnumType, enumValue) \
+    static_assert(static_cast<EnumType>(Test##EnumType::enumValue) == EnumType::enumValue)
+
+CHECK_TEST_ENUM(OperandType, FLOAT32);
+CHECK_TEST_ENUM(OperandType, INT32);
+CHECK_TEST_ENUM(OperandType, UINT32);
+CHECK_TEST_ENUM(OperandType, TENSOR_FLOAT32);
+CHECK_TEST_ENUM(OperandType, TENSOR_INT32);
+CHECK_TEST_ENUM(OperandType, TENSOR_QUANT8_ASYMM);
+CHECK_TEST_ENUM(OperandType, BOOL);
+CHECK_TEST_ENUM(OperandType, TENSOR_QUANT16_SYMM);
+CHECK_TEST_ENUM(OperandType, TENSOR_FLOAT16);
+CHECK_TEST_ENUM(OperandType, TENSOR_BOOL8);
+CHECK_TEST_ENUM(OperandType, FLOAT16);
+CHECK_TEST_ENUM(OperandType, TENSOR_QUANT8_SYMM_PER_CHANNEL);
+CHECK_TEST_ENUM(OperandType, TENSOR_QUANT16_ASYMM);
+CHECK_TEST_ENUM(OperandType, TENSOR_QUANT8_SYMM);
+CHECK_TEST_ENUM(OperandType, TENSOR_QUANT8_ASYMM_SIGNED);
+
+CHECK_TEST_ENUM(OperationType, ADD);
+CHECK_TEST_ENUM(OperationType, AVERAGE_POOL_2D);
+CHECK_TEST_ENUM(OperationType, CONCATENATION);
+CHECK_TEST_ENUM(OperationType, CONV_2D);
+CHECK_TEST_ENUM(OperationType, DEPTHWISE_CONV_2D);
+CHECK_TEST_ENUM(OperationType, DEPTH_TO_SPACE);
+CHECK_TEST_ENUM(OperationType, DEQUANTIZE);
+CHECK_TEST_ENUM(OperationType, EMBEDDING_LOOKUP);
+CHECK_TEST_ENUM(OperationType, FLOOR);
+CHECK_TEST_ENUM(OperationType, FULLY_CONNECTED);
+CHECK_TEST_ENUM(OperationType, HASHTABLE_LOOKUP);
+CHECK_TEST_ENUM(OperationType, L2_NORMALIZATION);
+CHECK_TEST_ENUM(OperationType, L2_POOL_2D);
+CHECK_TEST_ENUM(OperationType, LOCAL_RESPONSE_NORMALIZATION);
+CHECK_TEST_ENUM(OperationType, LOGISTIC);
+CHECK_TEST_ENUM(OperationType, LSH_PROJECTION);
+CHECK_TEST_ENUM(OperationType, LSTM);
+CHECK_TEST_ENUM(OperationType, MAX_POOL_2D);
+CHECK_TEST_ENUM(OperationType, MUL);
+CHECK_TEST_ENUM(OperationType, RELU);
+CHECK_TEST_ENUM(OperationType, RELU1);
+CHECK_TEST_ENUM(OperationType, RELU6);
+CHECK_TEST_ENUM(OperationType, RESHAPE);
+CHECK_TEST_ENUM(OperationType, RESIZE_BILINEAR);
+CHECK_TEST_ENUM(OperationType, RNN);
+CHECK_TEST_ENUM(OperationType, SOFTMAX);
+CHECK_TEST_ENUM(OperationType, SPACE_TO_DEPTH);
+CHECK_TEST_ENUM(OperationType, SVDF);
+CHECK_TEST_ENUM(OperationType, TANH);
+CHECK_TEST_ENUM(OperationType, BATCH_TO_SPACE_ND);
+CHECK_TEST_ENUM(OperationType, DIV);
+CHECK_TEST_ENUM(OperationType, MEAN);
+CHECK_TEST_ENUM(OperationType, PAD);
+CHECK_TEST_ENUM(OperationType, SPACE_TO_BATCH_ND);
+CHECK_TEST_ENUM(OperationType, SQUEEZE);
+CHECK_TEST_ENUM(OperationType, STRIDED_SLICE);
+CHECK_TEST_ENUM(OperationType, SUB);
+CHECK_TEST_ENUM(OperationType, TRANSPOSE);
+CHECK_TEST_ENUM(OperationType, ABS);
+CHECK_TEST_ENUM(OperationType, ARGMAX);
+CHECK_TEST_ENUM(OperationType, ARGMIN);
+CHECK_TEST_ENUM(OperationType, AXIS_ALIGNED_BBOX_TRANSFORM);
+CHECK_TEST_ENUM(OperationType, BIDIRECTIONAL_SEQUENCE_LSTM);
+CHECK_TEST_ENUM(OperationType, BIDIRECTIONAL_SEQUENCE_RNN);
+CHECK_TEST_ENUM(OperationType, BOX_WITH_NMS_LIMIT);
+CHECK_TEST_ENUM(OperationType, CAST);
+CHECK_TEST_ENUM(OperationType, CHANNEL_SHUFFLE);
+CHECK_TEST_ENUM(OperationType, DETECTION_POSTPROCESSING);
+CHECK_TEST_ENUM(OperationType, EQUAL);
+CHECK_TEST_ENUM(OperationType, EXP);
+CHECK_TEST_ENUM(OperationType, EXPAND_DIMS);
+CHECK_TEST_ENUM(OperationType, GATHER);
+CHECK_TEST_ENUM(OperationType, GENERATE_PROPOSALS);
+CHECK_TEST_ENUM(OperationType, GREATER);
+CHECK_TEST_ENUM(OperationType, GREATER_EQUAL);
+CHECK_TEST_ENUM(OperationType, GROUPED_CONV_2D);
+CHECK_TEST_ENUM(OperationType, HEATMAP_MAX_KEYPOINT);
+CHECK_TEST_ENUM(OperationType, INSTANCE_NORMALIZATION);
+CHECK_TEST_ENUM(OperationType, LESS);
+CHECK_TEST_ENUM(OperationType, LESS_EQUAL);
+CHECK_TEST_ENUM(OperationType, LOG);
+CHECK_TEST_ENUM(OperationType, LOGICAL_AND);
+CHECK_TEST_ENUM(OperationType, LOGICAL_NOT);
+CHECK_TEST_ENUM(OperationType, LOGICAL_OR);
+CHECK_TEST_ENUM(OperationType, LOG_SOFTMAX);
+CHECK_TEST_ENUM(OperationType, MAXIMUM);
+CHECK_TEST_ENUM(OperationType, MINIMUM);
+CHECK_TEST_ENUM(OperationType, NEG);
+CHECK_TEST_ENUM(OperationType, NOT_EQUAL);
+CHECK_TEST_ENUM(OperationType, PAD_V2);
+CHECK_TEST_ENUM(OperationType, POW);
+CHECK_TEST_ENUM(OperationType, PRELU);
+CHECK_TEST_ENUM(OperationType, QUANTIZE);
+CHECK_TEST_ENUM(OperationType, QUANTIZED_16BIT_LSTM);
+CHECK_TEST_ENUM(OperationType, RANDOM_MULTINOMIAL);
+CHECK_TEST_ENUM(OperationType, REDUCE_ALL);
+CHECK_TEST_ENUM(OperationType, REDUCE_ANY);
+CHECK_TEST_ENUM(OperationType, REDUCE_MAX);
+CHECK_TEST_ENUM(OperationType, REDUCE_MIN);
+CHECK_TEST_ENUM(OperationType, REDUCE_PROD);
+CHECK_TEST_ENUM(OperationType, REDUCE_SUM);
+CHECK_TEST_ENUM(OperationType, ROI_ALIGN);
+CHECK_TEST_ENUM(OperationType, ROI_POOLING);
+CHECK_TEST_ENUM(OperationType, RSQRT);
+CHECK_TEST_ENUM(OperationType, SELECT);
+CHECK_TEST_ENUM(OperationType, SIN);
+CHECK_TEST_ENUM(OperationType, SLICE);
+CHECK_TEST_ENUM(OperationType, SPLIT);
+CHECK_TEST_ENUM(OperationType, SQRT);
+CHECK_TEST_ENUM(OperationType, TILE);
+CHECK_TEST_ENUM(OperationType, TOPK_V2);
+CHECK_TEST_ENUM(OperationType, TRANSPOSE_CONV_2D);
+CHECK_TEST_ENUM(OperationType, UNIDIRECTIONAL_SEQUENCE_LSTM);
+CHECK_TEST_ENUM(OperationType, UNIDIRECTIONAL_SEQUENCE_RNN);
+CHECK_TEST_ENUM(OperationType, RESIZE_NEAREST_NEIGHBOR);
+
+#undef CHECK_TEST_ENUM
+
+}  // namespace aidl::android::hardware::neuralnetworks
diff --git a/neuralnetworks/aidl/vts/functional/TestMain.cpp b/neuralnetworks/aidl/vts/functional/TestMain.cpp
new file mode 100644
index 0000000..1d58608
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/TestMain.cpp
@@ -0,0 +1,27 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <android/binder_process.h>
+#include <gtest/gtest.h>
+#include "LogTestCaseToLogcat.h"
+
+int main(int argc, char** argv) {
+    testing::InitGoogleTest(&argc, argv);
+    testing::UnitTest::GetInstance()->listeners().Append(
+            new aidl::android::hardware::neuralnetworks::LogTestCaseToLogcat());
+    ABinderProcess_startThreadPool();
+    return RUN_ALL_TESTS();
+}
diff --git a/neuralnetworks/aidl/vts/functional/Utils.cpp b/neuralnetworks/aidl/vts/functional/Utils.cpp
new file mode 100644
index 0000000..14a496a
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/Utils.cpp
@@ -0,0 +1,252 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Utils.h"
+
+#include <aidl/android/hardware/neuralnetworks/IPreparedModelParcel.h>
+#include <aidl/android/hardware/neuralnetworks/Operand.h>
+#include <aidl/android/hardware/neuralnetworks/OperandType.h>
+#include <android-base/logging.h>
+#include <android/binder_status.h>
+#include <android/hardware_buffer.h>
+
+#include <iostream>
+#include <limits>
+#include <numeric>
+
+#include <MemoryUtils.h>
+#include <nnapi/SharedMemory.h>
+#include <nnapi/hal/aidl/Conversions.h>
+#include <nnapi/hal/aidl/Utils.h>
+
+namespace aidl::android::hardware::neuralnetworks {
+
+using test_helper::TestBuffer;
+using test_helper::TestModel;
+
+uint32_t sizeOfData(OperandType type) {
+    switch (type) {
+        case OperandType::FLOAT32:
+        case OperandType::INT32:
+        case OperandType::UINT32:
+        case OperandType::TENSOR_FLOAT32:
+        case OperandType::TENSOR_INT32:
+            return 4;
+        case OperandType::TENSOR_QUANT16_SYMM:
+        case OperandType::TENSOR_FLOAT16:
+        case OperandType::FLOAT16:
+        case OperandType::TENSOR_QUANT16_ASYMM:
+            return 2;
+        case OperandType::TENSOR_QUANT8_ASYMM:
+        case OperandType::BOOL:
+        case OperandType::TENSOR_BOOL8:
+        case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
+        case OperandType::TENSOR_QUANT8_SYMM:
+        case OperandType::TENSOR_QUANT8_ASYMM_SIGNED:
+            return 1;
+        case OperandType::SUBGRAPH:
+            return 0;
+        default:
+            CHECK(false) << "Invalid OperandType " << static_cast<uint32_t>(type);
+            return 0;
+    }
+}
+
+static bool isTensor(OperandType type) {
+    switch (type) {
+        case OperandType::FLOAT32:
+        case OperandType::INT32:
+        case OperandType::UINT32:
+        case OperandType::FLOAT16:
+        case OperandType::BOOL:
+        case OperandType::SUBGRAPH:
+            return false;
+        case OperandType::TENSOR_FLOAT32:
+        case OperandType::TENSOR_INT32:
+        case OperandType::TENSOR_QUANT16_SYMM:
+        case OperandType::TENSOR_FLOAT16:
+        case OperandType::TENSOR_QUANT16_ASYMM:
+        case OperandType::TENSOR_QUANT8_ASYMM:
+        case OperandType::TENSOR_BOOL8:
+        case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
+        case OperandType::TENSOR_QUANT8_SYMM:
+        case OperandType::TENSOR_QUANT8_ASYMM_SIGNED:
+            return true;
+        default:
+            CHECK(false) << "Invalid OperandType " << static_cast<uint32_t>(type);
+            return false;
+    }
+}
+
+uint32_t sizeOfData(const Operand& operand) {
+    const uint32_t dataSize = sizeOfData(operand.type);
+    if (isTensor(operand.type) && operand.dimensions.size() == 0) return 0;
+    return std::accumulate(operand.dimensions.begin(), operand.dimensions.end(), dataSize,
+                           std::multiplies<>{});
+}
+
+std::unique_ptr<TestAshmem> TestAshmem::create(uint32_t size) {
+    auto ashmem = std::make_unique<TestAshmem>(size);
+    return ashmem->mIsValid ? std::move(ashmem) : nullptr;
+}
+
+void TestAshmem::initialize(uint32_t size) {
+    mIsValid = false;
+    ASSERT_GT(size, 0);
+    const auto sharedMemory = nn::createSharedMemory(size).value();
+    mMappedMemory = nn::map(sharedMemory).value();
+    mPtr = static_cast<uint8_t*>(std::get<void*>(mMappedMemory.pointer));
+    CHECK_NE(mPtr, nullptr);
+    mAidlMemory = utils::convert(sharedMemory).value();
+    mIsValid = true;
+}
+
+std::unique_ptr<TestBlobAHWB> TestBlobAHWB::create(uint32_t size) {
+    auto ahwb = std::make_unique<TestBlobAHWB>(size);
+    return ahwb->mIsValid ? std::move(ahwb) : nullptr;
+}
+
+void TestBlobAHWB::initialize(uint32_t size) {
+    mIsValid = false;
+    ASSERT_GT(size, 0);
+    const auto usage = AHARDWAREBUFFER_USAGE_CPU_READ_OFTEN | AHARDWAREBUFFER_USAGE_CPU_WRITE_OFTEN;
+    const AHardwareBuffer_Desc desc = {
+            .width = size,
+            .height = 1,
+            .layers = 1,
+            .format = AHARDWAREBUFFER_FORMAT_BLOB,
+            .usage = usage,
+            .stride = size,
+    };
+
+    ASSERT_EQ(AHardwareBuffer_allocate(&desc, &mAhwb), 0);
+    ASSERT_NE(mAhwb, nullptr);
+
+    const auto sharedMemory = nn::createSharedMemoryFromAHWB(*mAhwb).value();
+    mMapping = nn::map(sharedMemory).value();
+    mPtr = static_cast<uint8_t*>(std::get<void*>(mMapping.pointer));
+    CHECK_NE(mPtr, nullptr);
+    mAidlMemory = utils::convert(sharedMemory).value();
+
+    mIsValid = true;
+}
+
+TestBlobAHWB::~TestBlobAHWB() {
+    if (mAhwb) {
+        AHardwareBuffer_unlock(mAhwb, nullptr);
+        AHardwareBuffer_release(mAhwb);
+    }
+}
+
+std::string gtestCompliantName(std::string name) {
+    // gtest test names must only contain alphanumeric characters
+    std::replace_if(
+            name.begin(), name.end(), [](char c) { return !std::isalnum(c); }, '_');
+    return name;
+}
+
+::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus) {
+    return os << toString(errorStatus);
+}
+
+Request ExecutionContext::createRequest(const TestModel& testModel, MemoryType memoryType) {
+    CHECK(memoryType == MemoryType::ASHMEM || memoryType == MemoryType::BLOB_AHWB);
+
+    // Model inputs.
+    std::vector<RequestArgument> inputs(testModel.main.inputIndexes.size());
+    size_t inputSize = 0;
+    for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
+        const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]];
+        if (op.data.size() == 0) {
+            // Omitted input.
+            inputs[i] = {.hasNoValue = true};
+        } else {
+            DataLocation loc = {.poolIndex = kInputPoolIndex,
+                                .offset = static_cast<int64_t>(inputSize),
+                                .length = static_cast<int64_t>(op.data.size())};
+            inputSize += op.data.alignedSize();
+            inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+        }
+    }
+
+    // Model outputs.
+    std::vector<RequestArgument> outputs(testModel.main.outputIndexes.size());
+    size_t outputSize = 0;
+    for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) {
+        const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]];
+
+        // In the case of zero-sized output, we should at least provide a one-byte buffer.
+        // This is because zero-sized tensors are only supported internally to the driver, or
+        // reported in output shapes. It is illegal for the client to pre-specify a zero-sized
+        // tensor as model output. Otherwise, we will have two semantic conflicts:
+        // - "Zero dimension" conflicts with "unspecified dimension".
+        // - "Omitted operand buffer" conflicts with "zero-sized operand buffer".
+        size_t bufferSize = std::max<size_t>(op.data.size(), 1);
+
+        DataLocation loc = {.poolIndex = kOutputPoolIndex,
+                            .offset = static_cast<int64_t>(outputSize),
+                            .length = static_cast<int64_t>(bufferSize)};
+        outputSize += op.data.size() == 0 ? TestBuffer::kAlignment : op.data.alignedSize();
+        outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+    }
+
+    // Allocate memory pools.
+    if (memoryType == MemoryType::ASHMEM) {
+        mInputMemory = TestAshmem::create(inputSize);
+        mOutputMemory = TestAshmem::create(outputSize);
+    } else {
+        mInputMemory = TestBlobAHWB::create(inputSize);
+        mOutputMemory = TestBlobAHWB::create(outputSize);
+    }
+    CHECK_NE(mInputMemory, nullptr);
+    CHECK_NE(mOutputMemory, nullptr);
+
+    auto copiedInputMemory = utils::clone(*mInputMemory->getAidlMemory());
+    CHECK(copiedInputMemory.has_value()) << copiedInputMemory.error().message;
+    auto copiedOutputMemory = utils::clone(*mOutputMemory->getAidlMemory());
+    CHECK(copiedOutputMemory.has_value()) << copiedOutputMemory.error().message;
+
+    std::vector<RequestMemoryPool> pools;
+    pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::pool>(
+            std::move(copiedInputMemory).value()));
+    pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::pool>(
+            std::move(copiedOutputMemory).value()));
+
+    // Copy input data to the memory pool.
+    uint8_t* inputPtr = mInputMemory->getPointer();
+    for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
+        const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]];
+        if (op.data.size() > 0) {
+            const uint8_t* begin = op.data.get<uint8_t>();
+            const uint8_t* end = begin + op.data.size();
+            std::copy(begin, end, inputPtr + inputs[i].location.offset);
+        }
+    }
+
+    return {.inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)};
+}
+
+std::vector<TestBuffer> ExecutionContext::getOutputBuffers(const Request& request) const {
+    // Copy out output results.
+    uint8_t* outputPtr = mOutputMemory->getPointer();
+    std::vector<TestBuffer> outputBuffers;
+    for (const auto& output : request.outputs) {
+        outputBuffers.emplace_back(output.location.length, outputPtr + output.location.offset);
+    }
+    return outputBuffers;
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks
diff --git a/neuralnetworks/aidl/vts/functional/Utils.h b/neuralnetworks/aidl/vts/functional/Utils.h
new file mode 100644
index 0000000..266301c
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/Utils.h
@@ -0,0 +1,153 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_AIDL_UTILS_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_AIDL_UTILS_H
+
+#include <android-base/logging.h>
+#include <android/hardware_buffer.h>
+#include <gtest/gtest.h>
+
+#include <algorithm>
+#include <iosfwd>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include <aidl/android/hardware/neuralnetworks/IDevice.h>
+#include <aidl/android/hardware/neuralnetworks/Memory.h>
+#include <aidl/android/hardware/neuralnetworks/Operand.h>
+#include <aidl/android/hardware/neuralnetworks/OperandType.h>
+#include <aidl/android/hardware/neuralnetworks/Priority.h>
+#include <aidl/android/hardware/neuralnetworks/Request.h>
+
+#include <TestHarness.h>
+#include <nnapi/SharedMemory.h>
+
+namespace aidl::android::hardware::neuralnetworks {
+
+namespace nn = ::android::nn;
+
+inline constexpr Priority kDefaultPriority = Priority::MEDIUM;
+
+inline constexpr Timing kNoTiming = {.timeOnDevice = -1, .timeInDriver = -1};
+inline constexpr int64_t kNoDeadline = -1;
+inline constexpr int64_t kOmittedTimeoutDuration = -1;
+inline constexpr int64_t kNoDuration = -1;
+inline const std::vector<uint8_t> kEmptyCacheToken(IDevice::BYTE_SIZE_OF_CACHE_TOKEN);
+
+// Returns the amount of space needed to store a value of the specified type.
+//
+// Aborts if the specified type is an extension type or OEM type.
+uint32_t sizeOfData(OperandType type);
+
+// Returns the amount of space needed to store a value of the dimensions and
+// type of this operand. For a non-extension, non-OEM tensor with unspecified
+// rank or at least one unspecified dimension, returns zero.
+//
+// Aborts if the specified type is an extension type or OEM type.
+uint32_t sizeOfData(const Operand& operand);
+
+// Convenience class to manage the lifetime of memory resources.
+class TestMemoryBase {
+    DISALLOW_COPY_AND_ASSIGN(TestMemoryBase);
+
+  public:
+    TestMemoryBase() = default;
+    virtual ~TestMemoryBase() = default;
+    uint8_t* getPointer() const { return mPtr; }
+    const Memory* getAidlMemory() const { return &mAidlMemory; }
+
+  protected:
+    uint8_t* mPtr = nullptr;
+    Memory mAidlMemory;
+    bool mIsValid = false;
+};
+
+class TestAshmem : public TestMemoryBase {
+  public:
+    static std::unique_ptr<TestAshmem> create(uint32_t size);
+
+    // Prefer TestAshmem::create.
+    // The constructor calls initialize, which constructs the memory resources. This is a workaround
+    // that gtest macros cannot be used directly in a constructor.
+    TestAshmem(uint32_t size) { initialize(size); }
+
+  private:
+    void initialize(uint32_t size);
+    nn::Mapping mMappedMemory;
+};
+
+class TestBlobAHWB : public TestMemoryBase {
+  public:
+    static std::unique_ptr<TestBlobAHWB> create(uint32_t size);
+
+    // Prefer TestBlobAHWB::create.
+    // The constructor calls initialize, which constructs the memory resources. This is a
+    // workaround that gtest macros cannot be used directly in a constructor.
+    TestBlobAHWB(uint32_t size) { initialize(size); }
+    ~TestBlobAHWB();
+
+  private:
+    void initialize(uint32_t size);
+    AHardwareBuffer* mAhwb = nullptr;
+    nn::Mapping mMapping;
+};
+
+enum class MemoryType { ASHMEM, BLOB_AHWB, DEVICE };
+
+// Manages the lifetime of memory resources used in an execution.
+class ExecutionContext {
+    DISALLOW_COPY_AND_ASSIGN(ExecutionContext);
+
+  public:
+    static constexpr uint32_t kInputPoolIndex = 0;
+    static constexpr uint32_t kOutputPoolIndex = 1;
+
+    ExecutionContext() = default;
+
+    // Create HIDL Request from the TestModel struct.
+    Request createRequest(const test_helper::TestModel& testModel,
+                          MemoryType memoryType = MemoryType::ASHMEM);
+
+    // After execution, copy out output results from the output memory pool.
+    std::vector<test_helper::TestBuffer> getOutputBuffers(const Request& request) const;
+
+  private:
+    std::unique_ptr<TestMemoryBase> mInputMemory, mOutputMemory;
+};
+
+template <typename Type>
+using Named = std::pair<std::string, Type>;
+
+template <typename Type>
+const std::string& getName(const Named<Type>& namedData) {
+    return namedData.first;
+}
+
+template <typename Type>
+const Type& getData(const Named<Type>& namedData) {
+    return namedData.second;
+}
+
+std::string gtestCompliantName(std::string name);
+
+// pretty-print values for error messages
+::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus);
+
+}  // namespace aidl::android::hardware::neuralnetworks
+
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_AIDL_UTILS_H
diff --git a/neuralnetworks/aidl/vts/functional/ValidateModel.cpp b/neuralnetworks/aidl/vts/functional/ValidateModel.cpp
new file mode 100644
index 0000000..b84d981
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/ValidateModel.cpp
@@ -0,0 +1,1338 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_aidl_hal_test"
+
+#include <aidl/android/hardware/common/NativeHandle.h>
+#include <android/binder_auto_utils.h>
+#include <android/binder_enums.h>
+#include <android/binder_interface_utils.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/hal/aidl/Conversions.h>
+#include <nnapi/hal/aidl/Utils.h>
+
+#include <optional>
+#include <type_traits>
+#include <utility>
+
+#include "Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using common::NativeHandle;
+using implementation::PreparedModelCallback;
+
+using PrepareModelMutation = std::function<void(Model*, ExecutionPreference*, Priority*)>;
+
+///////////////////////// UTILITY FUNCTIONS /////////////////////////
+
+static void validateGetSupportedOperations(const std::shared_ptr<IDevice>& device,
+                                           const std::string& message, const Model& model) {
+    SCOPED_TRACE(message + " [getSupportedOperations]");
+
+    std::vector<bool> supported;
+    const auto retStatus = device->getSupportedOperations(model, &supported);
+
+    ASSERT_FALSE(retStatus.isOk());
+    ASSERT_EQ(retStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+    ASSERT_EQ(static_cast<ErrorStatus>(retStatus.getServiceSpecificError()),
+              ErrorStatus::INVALID_ARGUMENT);
+}
+
+static void validatePrepareModel(const std::shared_ptr<IDevice>& device, const std::string& message,
+                                 const Model& model, ExecutionPreference preference,
+                                 Priority priority) {
+    SCOPED_TRACE(message + " [prepareModel]");
+
+    std::shared_ptr<PreparedModelCallback> preparedModelCallback =
+            ndk::SharedRefBase::make<PreparedModelCallback>();
+    const auto prepareLaunchStatus =
+            device->prepareModel(model, preference, priority, kNoDeadline, {}, {}, kEmptyCacheToken,
+                                 preparedModelCallback);
+    ASSERT_FALSE(prepareLaunchStatus.isOk());
+    ASSERT_EQ(prepareLaunchStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+    ASSERT_EQ(static_cast<ErrorStatus>(prepareLaunchStatus.getServiceSpecificError()),
+              ErrorStatus::INVALID_ARGUMENT);
+
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, prepareReturnStatus);
+    std::shared_ptr<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+    ASSERT_EQ(nullptr, preparedModel.get());
+}
+
+static bool validExecutionPreference(ExecutionPreference preference) {
+    return preference == ExecutionPreference::LOW_POWER ||
+           preference == ExecutionPreference::FAST_SINGLE_ANSWER ||
+           preference == ExecutionPreference::SUSTAINED_SPEED;
+}
+
+static bool validExecutionPriority(Priority priority) {
+    return priority == Priority::LOW || priority == Priority::MEDIUM || priority == Priority::HIGH;
+}
+
+// Primary validation function. This function will take a valid model, apply a
+// mutation to invalidate the model, the execution preference, or the priority,
+// then pass these to supportedOperations and/or prepareModel if that method is
+// called with an invalid argument.
+static void validate(const std::shared_ptr<IDevice>& device, const std::string& message,
+                     const Model& originalModel, const PrepareModelMutation& mutate) {
+    Model model = utils::clone(originalModel).value();
+    ExecutionPreference preference = ExecutionPreference::FAST_SINGLE_ANSWER;
+    Priority priority = kDefaultPriority;
+    mutate(&model, &preference, &priority);
+
+    if (validExecutionPreference(preference) && validExecutionPriority(priority)) {
+        validateGetSupportedOperations(device, message, model);
+    }
+
+    validatePrepareModel(device, message, model, preference, priority);
+}
+
+static uint32_t addOperand(Model* model) {
+    model->main.operands.push_back({
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::SUBGRAPH_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+    });
+    return model->main.operands.size() - 1;
+}
+
+static uint32_t addOperand(Model* model, OperandLifeTime lifetime) {
+    uint32_t index = addOperand(model);
+    model->main.operands[index].lifetime = lifetime;
+    return index;
+}
+
+// If we introduce a CONSTANT_COPY for an operand of size operandSize,
+// how much will this increase the size of the model?  This assumes
+// that we can (re)use all of model.operandValues for the operand
+// value.
+static size_t constantCopyExtraSize(const Model& model, size_t operandSize) {
+    const size_t operandValuesSize = model.operandValues.size();
+    return (operandValuesSize < operandSize) ? (operandSize - operandValuesSize) : 0;
+}
+
+// Highly specialized utility routine for converting an operand to
+// CONSTANT_COPY lifetime.
+//
+// Expects that:
+// - operand has a known size
+// - operand->lifetime has already been set to CONSTANT_COPY
+// - operand->location has been zeroed out
+//
+// Does the following:
+// - initializes operand->location to point to the beginning of model->operandValues
+// - resizes model->operandValues (if necessary) to be large enough for the operand
+//   value, padding it with zeroes on the end
+//
+// Potential problem:
+// By changing the operand to CONSTANT_COPY lifetime, this function is effectively initializing the
+// operand with unspecified (but deterministic) data. This means that the model may be invalidated
+// in two ways: not only is the lifetime of CONSTANT_COPY invalid, but the operand's value in the
+// graph may also be invalid (e.g., if the operand is used as an activation code and has an invalid
+// value). For now, this should be fine because it just means we're not testing what we think we're
+// testing in certain cases; but we can handwave this and assume we're probabilistically likely to
+// exercise the validation code over the span of the entire test set and operand space.
+//
+// Aborts if the specified operand type is an extension type or OEM type.
+static void becomeConstantCopy(Model* model, Operand* operand) {
+    // sizeOfData will abort if the specified type is an extension type or OEM type.
+    const size_t sizeOfOperand = sizeOfData(*operand);
+    EXPECT_NE(sizeOfOperand, size_t(0));
+    operand->location.poolIndex = 0;
+    operand->location.offset = 0;
+    operand->location.length = sizeOfOperand;
+    if (model->operandValues.size() < sizeOfOperand) {
+        model->operandValues.resize(sizeOfOperand);
+    }
+}
+
+// The sizeForBinder() functions estimate the size of the
+// representation of a value when sent to binder.  It's probably a bit
+// of an under-estimate, because we don't know the size of the
+// metadata in the binder format (e.g., representation of the size of
+// a vector); but at least it adds up "big" things like vector
+// contents.  However, it doesn't treat inter-field or end-of-struct
+// padding in a methodical way -- there's no attempt to be consistent
+// in whether or not padding in the native (C++) representation
+// contributes to the estimated size for the binder representation;
+// and there's no attempt to understand what padding (if any) is
+// needed in the binder representation.
+//
+// This assumes that non-metadata uses a fixed length encoding (e.g.,
+// a uint32_t is always encoded in sizeof(uint32_t) bytes, rather than
+// using an encoding whose length is related to the magnitude of the
+// encoded value).
+
+template <typename Type>
+static size_t sizeForBinder(const Type& val) {
+    static_assert(std::is_trivially_copyable_v<std::remove_reference_t<Type>>,
+                  "expected a trivially copyable type");
+    return sizeof(val);
+}
+
+template <typename Type>
+static size_t sizeForBinder(const std::vector<Type>& vec) {
+    return std::accumulate(vec.begin(), vec.end(), 0,
+                           [](size_t acc, const Type& x) { return acc + sizeForBinder(x); });
+}
+
+template <>
+size_t sizeForBinder(const SymmPerChannelQuantParams& symmPerChannelQuantParams) {
+    size_t size = 0;
+
+    size += sizeForBinder(symmPerChannelQuantParams.scales);
+    size += sizeForBinder(symmPerChannelQuantParams.channelDim);
+
+    return size;
+}
+
+template <>
+size_t sizeForBinder(const std::optional<OperandExtraParams>& optionalExtraParams) {
+    if (!optionalExtraParams.has_value()) {
+        return 0;
+    }
+    const auto& extraParams = optionalExtraParams.value();
+    using Tag = OperandExtraParams::Tag;
+    switch (extraParams.getTag()) {
+        case Tag::channelQuant:
+            return sizeForBinder(extraParams.get<Tag::channelQuant>());
+        case Tag::extension:
+            return sizeForBinder(extraParams.get<Tag::extension>());
+    }
+    LOG(FATAL) << "Unrecognized extraParams tag: " << static_cast<int>(extraParams.getTag());
+    return 0;
+}
+
+template <>
+size_t sizeForBinder(const Operand& operand) {
+    size_t size = 0;
+
+    size += sizeForBinder(operand.type);
+    size += sizeForBinder(operand.dimensions);
+    size += sizeForBinder(operand.scale);
+    size += sizeForBinder(operand.zeroPoint);
+    size += sizeForBinder(operand.lifetime);
+    size += sizeForBinder(operand.location);
+    size += sizeForBinder(operand.extraParams);
+
+    return size;
+}
+
+template <>
+size_t sizeForBinder(const Operation& operation) {
+    size_t size = 0;
+
+    size += sizeForBinder(operation.type);
+    size += sizeForBinder(operation.inputs);
+    size += sizeForBinder(operation.outputs);
+
+    return size;
+}
+
+template <>
+size_t sizeForBinder(const std::string& name) {
+    return name.size();
+}
+
+template <>
+size_t sizeForBinder(const Memory& memory) {
+    // This is just a guess.
+
+    size_t size = 0;
+    const NativeHandle& handle = memory.handle;
+    size += sizeof(decltype(handle.fds)::value_type) * handle.fds.size();
+    size += sizeof(decltype(handle.ints)::value_type) * handle.ints.size();
+    size += sizeForBinder(memory.name);
+    size += sizeof(memory);
+
+    return size;
+}
+
+template <>
+size_t sizeForBinder(const Subgraph& subgraph) {
+    size_t size = 0;
+
+    size += sizeForBinder(subgraph.operands);
+    size += sizeForBinder(subgraph.operations);
+    size += sizeForBinder(subgraph.inputIndexes);
+    size += sizeForBinder(subgraph.outputIndexes);
+
+    return size;
+}
+
+template <>
+size_t sizeForBinder(const ExtensionNameAndPrefix& extensionNameToPrefix) {
+    size_t size = 0;
+
+    size += sizeForBinder(extensionNameToPrefix.name);
+    size += sizeForBinder(extensionNameToPrefix.prefix);
+
+    return size;
+}
+
+template <>
+size_t sizeForBinder(const Model& model) {
+    size_t size = 0;
+
+    size += sizeForBinder(model.main);
+    size += sizeForBinder(model.referenced);
+    size += sizeForBinder(model.operandValues);
+    size += sizeForBinder(model.pools);
+    size += sizeForBinder(model.relaxComputationFloat32toFloat16);
+    size += sizeForBinder(model.extensionNameToPrefix);
+
+    return size;
+}
+
+// https://developer.android.com/reference/android/os/TransactionTooLargeException.html
+//
+//     "The Binder transaction buffer has a limited fixed size,
+//     currently 1Mb, which is shared by all transactions in progress
+//     for the process."
+//
+// Will our representation fit under this limit?  There are two complications:
+// - Our representation size is just approximate (see sizeForBinder()).
+// - This object may not be the only occupant of the Binder transaction buffer.
+// So we'll be very conservative: We want the representation size to be no
+// larger than half the transaction buffer size.
+//
+// If our representation grows large enough that it still fits within
+// the transaction buffer but combined with other transactions may
+// exceed the buffer size, then we may see intermittent HAL transport
+// errors.
+static bool exceedsBinderSizeLimit(size_t representationSize) {
+    // Instead of using this fixed buffer size, we might instead be able to use
+    // ProcessState::self()->getMmapSize(). However, this has a potential
+    // problem: The binder/mmap size of the current process does not necessarily
+    // indicate the binder/mmap size of the service (i.e., the other process).
+    // The only way it would be a good indication is if both the current process
+    // and the service use the default size.
+    static const size_t kHalfBufferSize = 1024 * 1024 / 2;
+
+    return representationSize > kHalfBufferSize;
+}
+
+///////////////////////// VALIDATE EXECUTION ORDER ////////////////////////////
+
+static void mutateExecutionOrderTest(const std::shared_ptr<IDevice>& device, const Model& model,
+                                     const std::vector<uint32_t>& numberOfConsumers) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        const Operation& operationObj = model.main.operations[operation];
+        for (uint32_t input : operationObj.inputs) {
+            if (model.main.operands[input].lifetime == OperandLifeTime::TEMPORARY_VARIABLE ||
+                model.main.operands[input].lifetime == OperandLifeTime::SUBGRAPH_OUTPUT) {
+                // This operation reads an operand written by some
+                // other operation.  Move this operation to the
+                // beginning of the sequence, ensuring that it reads
+                // the operand before that operand is written, thereby
+                // violating execution order rules.
+                const std::string message = "mutateExecutionOrderTest: operation " +
+                                            std::to_string(operation) + " is a reader";
+                validate(device, message, model,
+                         [operation](Model* model, ExecutionPreference*, Priority*) {
+                             auto& operations = model->main.operations;
+                             std::rotate(operations.begin(), operations.begin() + operation,
+                                         operations.begin() + operation + 1);
+                         });
+                break;  // only need to do this once per operation
+            }
+        }
+        for (uint32_t output : operationObj.outputs) {
+            if (numberOfConsumers[output] > 0) {
+                // This operation writes an operand read by some other
+                // operation.  Move this operation to the end of the
+                // sequence, ensuring that it writes the operand after
+                // that operand is read, thereby violating execution
+                // order rules.
+                const std::string message = "mutateExecutionOrderTest: operation " +
+                                            std::to_string(operation) + " is a writer";
+                validate(device, message, model,
+                         [operation](Model* model, ExecutionPreference*, Priority*) {
+                             auto& operations = model->main.operations;
+                             std::rotate(operations.begin() + operation,
+                                         operations.begin() + operation + 1, operations.end());
+                         });
+                break;  // only need to do this once per operation
+            }
+        }
+    }
+}
+
+///////////////////////// VALIDATE MODEL OPERAND TYPE /////////////////////////
+
+static const int32_t invalidOperandTypes[] = {
+        -1,
+        static_cast<int32_t>(*(ndk::enum_range<OperandType>().end() - 1)) + 1,
+};
+
+static void mutateOperandTypeTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        for (int32_t invalidOperandType : invalidOperandTypes) {
+            const std::string message = "mutateOperandTypeTest: operand " +
+                                        std::to_string(operand) + " set to value " +
+                                        std::to_string(invalidOperandType);
+            validate(device, message, model,
+                     [operand, invalidOperandType](Model* model, ExecutionPreference*, Priority*) {
+                         model->main.operands[operand].type =
+                                 static_cast<OperandType>(invalidOperandType);
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE OPERAND RANK /////////////////////////
+
+static uint32_t getInvalidRank(OperandType type) {
+    switch (type) {
+        case OperandType::FLOAT16:
+        case OperandType::FLOAT32:
+        case OperandType::INT32:
+        case OperandType::UINT32:
+        case OperandType::BOOL:
+            return 1;
+        case OperandType::TENSOR_BOOL8:
+        case OperandType::TENSOR_FLOAT16:
+        case OperandType::TENSOR_FLOAT32:
+        case OperandType::TENSOR_INT32:
+        case OperandType::TENSOR_QUANT8_ASYMM:
+        case OperandType::TENSOR_QUANT8_SYMM:
+        case OperandType::TENSOR_QUANT16_ASYMM:
+        case OperandType::TENSOR_QUANT16_SYMM:
+        case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
+            return 0;
+        default:
+            return 0;
+    }
+}
+
+static void mutateOperandRankTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        const uint32_t invalidRank = getInvalidRank(model.main.operands[operand].type);
+        if (invalidRank == 0) {
+            continue;
+        }
+        const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) +
+                                    " has rank of " + std::to_string(invalidRank);
+        validate(device, message, model,
+                 [operand, invalidRank](Model* model, ExecutionPreference*, Priority*) {
+                     model->main.operands[operand].dimensions =
+                             std::vector<int32_t>(invalidRank, 0);
+                 });
+    }
+}
+
+///////////////////////// VALIDATE OPERAND SCALE /////////////////////////
+
+static float getInvalidScale(OperandType type) {
+    switch (type) {
+        case OperandType::FLOAT16:
+        case OperandType::FLOAT32:
+        case OperandType::INT32:
+        case OperandType::UINT32:
+        case OperandType::BOOL:
+        case OperandType::TENSOR_BOOL8:
+        case OperandType::TENSOR_FLOAT16:
+        case OperandType::TENSOR_FLOAT32:
+        case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
+        case OperandType::SUBGRAPH:
+            return 1.0f;
+        case OperandType::TENSOR_INT32:
+            return -1.0f;
+        case OperandType::TENSOR_QUANT8_SYMM:
+        case OperandType::TENSOR_QUANT8_ASYMM:
+        case OperandType::TENSOR_QUANT16_ASYMM:
+        case OperandType::TENSOR_QUANT16_SYMM:
+            return 0.0f;
+        default:
+            return 0.0f;
+    }
+}
+
+static void mutateOperandScaleTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        const float invalidScale = getInvalidScale(model.main.operands[operand].type);
+        const std::string message = "mutateOperandScaleTest: operand " + std::to_string(operand) +
+                                    " has scale of " + std::to_string(invalidScale);
+        validate(device, message, model,
+                 [operand, invalidScale](Model* model, ExecutionPreference*, Priority*) {
+                     model->main.operands[operand].scale = invalidScale;
+                 });
+    }
+}
+
+///////////////////////// VALIDATE OPERAND ZERO POINT /////////////////////////
+
+static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
+    switch (type) {
+        case OperandType::FLOAT16:
+        case OperandType::FLOAT32:
+        case OperandType::INT32:
+        case OperandType::UINT32:
+        case OperandType::BOOL:
+        case OperandType::TENSOR_BOOL8:
+        case OperandType::TENSOR_FLOAT16:
+        case OperandType::TENSOR_FLOAT32:
+        case OperandType::TENSOR_INT32:
+        case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
+        case OperandType::SUBGRAPH:
+            return {1};
+        case OperandType::TENSOR_QUANT8_ASYMM:
+            return {-1, 256};
+        case OperandType::TENSOR_QUANT8_SYMM:
+            return {-129, -1, 1, 128};
+        case OperandType::TENSOR_QUANT16_ASYMM:
+            return {-1, 65536};
+        case OperandType::TENSOR_QUANT16_SYMM:
+            return {-32769, -1, 1, 32768};
+        default:
+            return {};
+    }
+}
+
+static void mutateOperandZeroPointTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        const std::vector<int32_t> invalidZeroPoints =
+                getInvalidZeroPoints(model.main.operands[operand].type);
+        for (int32_t invalidZeroPoint : invalidZeroPoints) {
+            const std::string message = "mutateOperandZeroPointTest: operand " +
+                                        std::to_string(operand) + " has zero point of " +
+                                        std::to_string(invalidZeroPoint);
+            validate(device, message, model,
+                     [operand, invalidZeroPoint](Model* model, ExecutionPreference*, Priority*) {
+                         model->main.operands[operand].zeroPoint = invalidZeroPoint;
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE OPERAND LIFETIME /////////////////////////////////////////////
+
+static std::vector<OperandLifeTime> getInvalidLifeTimes(const Model& model, size_t modelSize,
+                                                        const Operand& operand) {
+    // TODO: Support OperandLifeTime::CONSTANT_REFERENCE as an invalid lifetime
+    // TODO: Support OperandLifeTime::NO_VALUE as an invalid lifetime
+
+    // Ways to get an invalid lifetime:
+    // - change whether a lifetime means an operand should have a writer
+    std::vector<OperandLifeTime> ret;
+    switch (operand.lifetime) {
+        case OperandLifeTime::SUBGRAPH_OUTPUT:
+        case OperandLifeTime::TEMPORARY_VARIABLE:
+            ret = {
+                    OperandLifeTime::SUBGRAPH_INPUT,
+                    OperandLifeTime::CONSTANT_COPY,
+            };
+            break;
+        case OperandLifeTime::CONSTANT_COPY:
+        case OperandLifeTime::CONSTANT_POOL:
+        case OperandLifeTime::SUBGRAPH_INPUT:
+            ret = {
+                    OperandLifeTime::TEMPORARY_VARIABLE,
+                    OperandLifeTime::SUBGRAPH_OUTPUT,
+            };
+            break;
+        case OperandLifeTime::NO_VALUE:
+            // Not enough information to know whether
+            // TEMPORARY_VARIABLE or CONSTANT_COPY would be invalid --
+            // is this operand written (then CONSTANT_COPY would be
+            // invalid) or not (then TEMPORARY_VARIABLE would be
+            // invalid)?
+            break;
+        case OperandLifeTime::SUBGRAPH:
+            break;
+        default:
+            ADD_FAILURE();
+            break;
+    }
+
+    const size_t operandSize = sizeOfData(operand);  // will be zero if shape is unknown
+    if (!operandSize ||
+        exceedsBinderSizeLimit(modelSize + constantCopyExtraSize(model, operandSize))) {
+        // Unknown size or too-large size
+        ret.erase(std::remove(ret.begin(), ret.end(), OperandLifeTime::CONSTANT_COPY), ret.end());
+    }
+
+    return ret;
+}
+
+static void mutateOperandLifeTimeTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    const size_t modelSize = sizeForBinder(model);
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        const std::vector<OperandLifeTime> invalidLifeTimes =
+                getInvalidLifeTimes(model, modelSize, model.main.operands[operand]);
+        for (OperandLifeTime invalidLifeTime : invalidLifeTimes) {
+            const std::string message = "mutateOperandLifetimeTest: operand " +
+                                        std::to_string(operand) + " has lifetime " +
+                                        toString(invalidLifeTime) + " instead of lifetime " +
+                                        toString(model.main.operands[operand].lifetime);
+            validate(device, message, model,
+                     [operand, invalidLifeTime](Model* model, ExecutionPreference*, Priority*) {
+                         static const DataLocation kZeroDataLocation = {};
+                         Operand& operandObj = model->main.operands[operand];
+                         switch (operandObj.lifetime) {
+                             case OperandLifeTime::SUBGRAPH_INPUT: {
+                                 auto& inputs = model->main.inputIndexes;
+                                 inputs.erase(std::remove(inputs.begin(), inputs.end(), operand),
+                                              inputs.end());
+                                 break;
+                             }
+                             case OperandLifeTime::SUBGRAPH_OUTPUT: {
+                                 auto& outputs = model->main.outputIndexes;
+                                 outputs.erase(std::remove(outputs.begin(), outputs.end(), operand),
+                                               outputs.end());
+                                 break;
+                             }
+                             default:
+                                 break;
+                         }
+                         operandObj.lifetime = invalidLifeTime;
+                         operandObj.location = kZeroDataLocation;
+                         switch (invalidLifeTime) {
+                             case OperandLifeTime::CONSTANT_COPY: {
+                                 becomeConstantCopy(model, &operandObj);
+                                 break;
+                             }
+                             case OperandLifeTime::SUBGRAPH_INPUT:
+                                 model->main.inputIndexes.push_back(operand);
+                                 break;
+                             case OperandLifeTime::SUBGRAPH_OUTPUT:
+                                 model->main.outputIndexes.push_back(operand);
+                                 break;
+                             default:
+                                 break;
+                         }
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE OPERAND INPUT-or-OUTPUT //////////////////////////////////////
+
+static std::optional<OperandLifeTime> getInputOutputLifeTime(const Model& model, size_t modelSize,
+                                                             const Operand& operand) {
+    // Ways to get an invalid lifetime (with respect to model inputIndexes and outputIndexes):
+    // - change whether a lifetime means an operand is a model input, a model output, or neither
+    // - preserve whether or not a lifetime means an operand should have a writer
+    switch (operand.lifetime) {
+        case OperandLifeTime::CONSTANT_COPY:
+        case OperandLifeTime::CONSTANT_POOL:
+            return OperandLifeTime::SUBGRAPH_INPUT;
+        case OperandLifeTime::SUBGRAPH_INPUT: {
+            const size_t operandSize = sizeOfData(operand);  // will be zero if shape is unknown
+            if (!operandSize ||
+                exceedsBinderSizeLimit(modelSize + constantCopyExtraSize(model, operandSize))) {
+                // Unknown size or too-large size
+                break;
+            }
+            return OperandLifeTime::CONSTANT_COPY;
+        }
+        case OperandLifeTime::SUBGRAPH_OUTPUT:
+            return OperandLifeTime::TEMPORARY_VARIABLE;
+        case OperandLifeTime::TEMPORARY_VARIABLE:
+            return OperandLifeTime::SUBGRAPH_OUTPUT;
+        case OperandLifeTime::NO_VALUE:
+            // Not enough information to know whether
+            // TEMPORARY_VARIABLE or CONSTANT_COPY would be an
+            // appropriate choice -- is this operand written (then
+            // TEMPORARY_VARIABLE would be appropriate) or not (then
+            // CONSTANT_COPY would be appropriate)?
+            break;
+        case OperandLifeTime::SUBGRAPH:
+            break;
+        default:
+            ADD_FAILURE();
+            break;
+    }
+
+    return std::nullopt;
+}
+
+static void mutateOperandInputOutputTest(const std::shared_ptr<IDevice>& device,
+                                         const Model& model) {
+    const size_t modelSize = sizeForBinder(model);
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        const std::optional<OperandLifeTime> changedLifeTime =
+                getInputOutputLifeTime(model, modelSize, model.main.operands[operand]);
+        if (changedLifeTime) {
+            const std::string message = "mutateOperandInputOutputTest: operand " +
+                                        std::to_string(operand) + " has lifetime " +
+                                        toString(*changedLifeTime) + " instead of lifetime " +
+                                        toString(model.main.operands[operand].lifetime);
+            validate(device, message, model,
+                     [operand, changedLifeTime](Model* model, ExecutionPreference*, Priority*) {
+                         static const DataLocation kZeroDataLocation = {};
+                         Operand& operandObj = model->main.operands[operand];
+                         operandObj.lifetime = *changedLifeTime;
+                         operandObj.location = kZeroDataLocation;
+                         if (*changedLifeTime == OperandLifeTime::CONSTANT_COPY) {
+                             becomeConstantCopy(model, &operandObj);
+                         }
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE OPERAND NUMBER OF WRITERS ////////////////////////////////////
+
+static void mutateOperandAddWriterTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        for (size_t badOutputNum = 0;
+             badOutputNum < model.main.operations[operation].outputs.size(); ++badOutputNum) {
+            const uint32_t outputOperandIndex =
+                    model.main.operations[operation].outputs[badOutputNum];
+            const std::string message = "mutateOperandAddWriterTest: operation " +
+                                        std::to_string(operation) + " writes to " +
+                                        std::to_string(outputOperandIndex);
+            // We'll insert a copy of the operation, all of whose
+            // OTHER output operands are newly-created -- i.e.,
+            // there'll only be a duplicate write of ONE of that
+            // operation's output operands.
+            validate(device, message, model,
+                     [operation, badOutputNum](Model* model, ExecutionPreference*, Priority*) {
+                         Operation newOperation = model->main.operations[operation];
+                         for (size_t outputNum = 0; outputNum < newOperation.outputs.size();
+                              ++outputNum) {
+                             if (outputNum == badOutputNum) continue;
+
+                             Operand operandValue =
+                                     model->main.operands[newOperation.outputs[outputNum]];
+                             if (operandValue.lifetime == OperandLifeTime::SUBGRAPH_OUTPUT) {
+                                 operandValue.lifetime = OperandLifeTime::TEMPORARY_VARIABLE;
+                             } else {
+                                 ASSERT_EQ(operandValue.lifetime,
+                                           OperandLifeTime::TEMPORARY_VARIABLE);
+                             }
+                             newOperation.outputs[outputNum] = model->main.operands.size();
+                             model->main.operands.push_back(operandValue);
+                         }
+                         // Where do we insert the extra writer (a new
+                         // operation)?  It has to be later than all the
+                         // writers of its inputs.  The easiest thing to do
+                         // is to insert it at the end of the operation
+                         // sequence.
+                         model->main.operations.push_back(newOperation);
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE EXTRA ??? /////////////////////////
+
+// TODO: Operand::location
+
+///////////////////////// VALIDATE OPERATION OPERAND TYPE /////////////////////////
+
+static void mutateOperand(Operand* operand, OperandType type) {
+    Operand newOperand = *operand;
+    newOperand.type = type;
+    switch (type) {
+        case OperandType::FLOAT16:
+        case OperandType::FLOAT32:
+        case OperandType::INT32:
+        case OperandType::UINT32:
+        case OperandType::BOOL:
+            newOperand.dimensions = {};
+            newOperand.scale = 0.0f;
+            newOperand.zeroPoint = 0;
+            break;
+        case OperandType::TENSOR_BOOL8:
+        case OperandType::TENSOR_FLOAT16:
+        case OperandType::TENSOR_FLOAT32:
+            newOperand.dimensions = operand->dimensions.size() > 0 ? operand->dimensions
+                                                                   : std::vector<int32_t>({1});
+            newOperand.scale = 0.0f;
+            newOperand.zeroPoint = 0;
+            break;
+        case OperandType::TENSOR_INT32:
+            newOperand.dimensions = operand->dimensions.size() > 0 ? operand->dimensions
+                                                                   : std::vector<int32_t>({1});
+            newOperand.zeroPoint = 0;
+            break;
+        case OperandType::TENSOR_QUANT8_ASYMM:
+        case OperandType::TENSOR_QUANT8_SYMM:
+        case OperandType::TENSOR_QUANT16_ASYMM:
+        case OperandType::TENSOR_QUANT16_SYMM:
+            newOperand.dimensions = operand->dimensions.size() > 0 ? operand->dimensions
+                                                                   : std::vector<int32_t>({1});
+            newOperand.scale = operand->scale != 0.0f ? operand->scale : 1.0f;
+            break;
+        case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL: {
+            newOperand.dimensions = operand->dimensions.size() > 0 ? operand->dimensions
+                                                                   : std::vector<int32_t>({1});
+            newOperand.scale = 0.0f;
+            newOperand.zeroPoint = 0;
+
+            SymmPerChannelQuantParams channelQuant;
+            channelQuant.channelDim = 0;
+            channelQuant.scales = std::vector<float>(
+                    operand->dimensions.size() > 0 ? static_cast<size_t>(operand->dimensions[0])
+                                                   : 0);
+            for (size_t i = 0; i < channelQuant.scales.size(); ++i) {
+                channelQuant.scales[i] = 1.0f;
+            }
+            newOperand.extraParams->set<OperandExtraParams::Tag::channelQuant>(
+                    std::move(channelQuant));
+        } break;
+        default:
+            break;
+    }
+    *operand = newOperand;
+}
+
+static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, const Model& model) {
+    if (type == model.main.operands[operand].type) {
+        return true;
+    }
+    for (const Operation& operation : model.main.operations) {
+        // Skip mutateOperationOperandTypeTest for the following operations.
+        // - LSH_PROJECTION's second argument is allowed to have any type.
+        // - ARGMIN and ARGMAX's first argument can be any of
+        // TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM).
+        // - CAST's argument can be any of TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM).
+        // - RANDOM_MULTINOMIAL's argument can be either TENSOR_FLOAT16 or TENSOR_FLOAT32.
+        // - DEQUANTIZE input can be any of
+        // TENSOR_(QUANT8_ASYMM|QUANT8_ASYMM_SIGNED|QUANT8_SYMM|QUANT8_SYMM_PER_CHANNEL),
+        // output can be of either TENSOR_FLOAT16 or TENSOR_FLOAT32.
+        // - QUANTIZE input can be either TENSOR_FLOAT16 or TENSOR_FLOAT32
+        // - CONV_2D filter type (arg 1) can be QUANT8_ASYMM or QUANT8_SYMM_PER_CHANNEL
+        // - DEPTHWISE_CONV_2D filter type (arg 1) can be QUANT8_ASYMM or QUANT8_SYMM_PER_CHANNEL
+        // - GROUPED_CONV_2D filter type (arg 1) can be QUANT8_ASYMM or QUANT8_SYMM_PER_CHANNEL
+        // - TRANSPOSE_CONV_2D filter type (arg 1) can be QUANT8_ASYMM or QUANT8_SYMM_PER_CHANNEL
+        // - AXIS_ALIGNED_BBOX_TRANSFORM bounding boxes (arg 1) can be of
+        //     TENSOR_QUANT8_ASYMM or TENSOR_QUANT8_ASYMM_SIGNED.
+        // - RANK's input can have any TENSOR_* type.
+        switch (operation.type) {
+            case OperationType::LSH_PROJECTION: {
+                if (operand == operation.inputs[1]) {
+                    return true;
+                }
+            } break;
+            case OperationType::CAST:
+            case OperationType::ARGMAX:
+            case OperationType::ARGMIN: {
+                if (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32 ||
+                    type == OperandType::TENSOR_INT32 || type == OperandType::TENSOR_QUANT8_ASYMM ||
+                    type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED) {
+                    return true;
+                }
+            } break;
+            case OperationType::QUANTIZE: {
+                if (operand == operation.inputs[0] &&
+                    (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32)) {
+                    return true;
+                }
+                if (operand == operation.outputs[0] &&
+                    (type == OperandType::TENSOR_QUANT8_ASYMM ||
+                     type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED)) {
+                    return true;
+                }
+            } break;
+            case OperationType::RANDOM_MULTINOMIAL: {
+                if (operand == operation.inputs[0] &&
+                    (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32)) {
+                    return true;
+                }
+            } break;
+            case OperationType::DEQUANTIZE: {
+                if (operand == operation.inputs[0] &&
+                    (type == OperandType::TENSOR_QUANT8_ASYMM ||
+                     type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED ||
+                     type == OperandType::TENSOR_QUANT8_SYMM ||
+                     type == OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL)) {
+                    return true;
+                }
+                if (operand == operation.outputs[0] &&
+                    (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32)) {
+                    return true;
+                }
+            } break;
+            case OperationType::TRANSPOSE_CONV_2D:
+            case OperationType::GROUPED_CONV_2D:
+            case OperationType::DEPTHWISE_CONV_2D:
+            case OperationType::CONV_2D: {
+                if (operand == operation.inputs[1] &&
+                    (type == OperandType::TENSOR_QUANT8_ASYMM ||
+                     type == OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL)) {
+                    return true;
+                }
+            } break;
+            case OperationType::AXIS_ALIGNED_BBOX_TRANSFORM: {
+                if (operand == operation.inputs[1] &&
+                    (type == OperandType::TENSOR_QUANT8_ASYMM ||
+                     type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED)) {
+                    return true;
+                }
+            } break;
+            case OperationType::RANK: {
+                if (operand == operation.inputs[0] &&
+                    (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32 ||
+                     type == OperandType::TENSOR_INT32 ||
+                     type == OperandType::TENSOR_QUANT8_ASYMM ||
+                     type == OperandType::TENSOR_QUANT16_SYMM ||
+                     type == OperandType::TENSOR_BOOL8 ||
+                     type == OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL ||
+                     type == OperandType::TENSOR_QUANT16_ASYMM ||
+                     type == OperandType::TENSOR_QUANT8_SYMM ||
+                     type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED)) {
+                    return true;
+                }
+            } break;
+            default:
+                break;
+        }
+    }
+    return false;
+}
+
+static void mutateOperationOperandTypeTest(const std::shared_ptr<IDevice>& device,
+                                           const Model& model) {
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        for (OperandType invalidOperandType : ndk::enum_range<OperandType>()) {
+            if (mutateOperationOperandTypeSkip(operand, invalidOperandType, model)) {
+                continue;
+            }
+            const std::string message = "mutateOperationOperandTypeTest: operand " +
+                                        std::to_string(operand) + " set to type " +
+                                        toString(invalidOperandType);
+            validate(device, message, model,
+                     [operand, invalidOperandType](Model* model, ExecutionPreference*, Priority*) {
+                         mutateOperand(&model->main.operands[operand], invalidOperandType);
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE MODEL OPERATION TYPE /////////////////////////
+
+static const int32_t invalidOperationTypes[] = {
+        -1,
+        static_cast<int32_t>(*(ndk::enum_range<OperationType>().end() - 1)) + 1,
+};
+
+static void mutateOperationTypeTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        for (int32_t invalidOperationType : invalidOperationTypes) {
+            const std::string message = "mutateOperationTypeTest: operation " +
+                                        std::to_string(operation) + " set to value " +
+                                        std::to_string(invalidOperationType);
+            validate(device, message, model,
+                     [operation, invalidOperationType](Model* model, ExecutionPreference*,
+                                                       Priority*) {
+                         model->main.operations[operation].type =
+                                 static_cast<OperationType>(invalidOperationType);
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE MODEL OPERATION INPUT OPERAND INDEX /////////////////////////
+
+static void mutateOperationInputOperandIndexTest(const std::shared_ptr<IDevice>& device,
+                                                 const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        const uint32_t invalidOperand = model.main.operands.size();
+        for (size_t input = 0; input < model.main.operations[operation].inputs.size(); ++input) {
+            const std::string message = "mutateOperationInputOperandIndexTest: operation " +
+                                        std::to_string(operation) + " input " +
+                                        std::to_string(input);
+            validate(device, message, model,
+                     [operation, input, invalidOperand](Model* model, ExecutionPreference*,
+                                                        Priority*) {
+                         model->main.operations[operation].inputs[input] = invalidOperand;
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE MODEL OPERATION OUTPUT OPERAND INDEX /////////////////////////
+
+static void mutateOperationOutputOperandIndexTest(const std::shared_ptr<IDevice>& device,
+                                                  const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        const uint32_t invalidOperand = model.main.operands.size();
+        for (size_t output = 0; output < model.main.operations[operation].outputs.size();
+             ++output) {
+            const std::string message = "mutateOperationOutputOperandIndexTest: operation " +
+                                        std::to_string(operation) + " output " +
+                                        std::to_string(output);
+            validate(device, message, model,
+                     [operation, output, invalidOperand](Model* model, ExecutionPreference*,
+                                                         Priority*) {
+                         model->main.operations[operation].outputs[output] = invalidOperand;
+                     });
+        }
+    }
+}
+
+///////////////////////// VALIDATE MODEL OPERANDS WRITTEN ///////////////////////////////////////
+
+static void mutateOperationRemoveWriteTest(const std::shared_ptr<IDevice>& device,
+                                           const Model& model,
+                                           const std::vector<uint32_t>& numberOfConsumers) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        for (size_t outputNum = 0; outputNum < model.main.operations[operation].outputs.size();
+             ++outputNum) {
+            const uint32_t outputOperandIndex = model.main.operations[operation].outputs[outputNum];
+            if (numberOfConsumers[outputOperandIndex] > 0) {
+                const std::string message = "mutateOperationRemoveWriteTest: operation " +
+                                            std::to_string(operation) + " writes to " +
+                                            std::to_string(outputOperandIndex);
+                validate(device, message, model,
+                         [operation, outputNum](Model* model, ExecutionPreference*, Priority*) {
+                             int32_t& outputOperandIndex =
+                                     model->main.operations[operation].outputs[outputNum];
+                             Operand operandValue = model->main.operands[outputOperandIndex];
+                             if (operandValue.lifetime == OperandLifeTime::SUBGRAPH_OUTPUT) {
+                                 operandValue.lifetime = OperandLifeTime::TEMPORARY_VARIABLE;
+                             } else {
+                                 ASSERT_EQ(operandValue.lifetime,
+                                           OperandLifeTime::TEMPORARY_VARIABLE);
+                             }
+                             outputOperandIndex = model->main.operands.size();
+                             model->main.operands.push_back(operandValue);
+                         });
+            }
+        }
+    }
+}
+
+///////////////////////// REMOVE OPERAND FROM EVERYTHING /////////////////////////
+
+static void removeValueAndDecrementGreaterValues(std::vector<int32_t>* vec, uint32_t value) {
+    if (vec) {
+        // remove elements matching "value"
+        vec->erase(std::remove(vec->begin(), vec->end(), value), vec->end());
+
+        // decrement elements exceeding "value"
+        std::transform(vec->begin(), vec->end(), vec->begin(),
+                       [value](uint32_t v) { return v > value ? v-- : v; });
+    }
+}
+
+static void removeOperand(Model* model, uint32_t index) {
+    model->main.operands.erase(model->main.operands.begin() + index);
+    for (Operation& operation : model->main.operations) {
+        removeValueAndDecrementGreaterValues(&operation.inputs, index);
+        removeValueAndDecrementGreaterValues(&operation.outputs, index);
+    }
+    removeValueAndDecrementGreaterValues(&model->main.inputIndexes, index);
+    removeValueAndDecrementGreaterValues(&model->main.outputIndexes, index);
+}
+
+static bool removeOperandSkip(size_t operandIndex, const Model& model,
+                              const std::vector<uint32_t>& numberOfConsumers) {
+    if (numberOfConsumers[operandIndex] == 0) {
+        // Removing an unused operand has no effect.
+        return true;
+    }
+    for (const Operation& operation : model.main.operations) {
+        // Skip removeOperandTest for the following operations.
+        // - SPLIT's outputs are not checked during prepareModel.
+        if (operation.type == OperationType::SPLIT) {
+            for (const size_t index : operation.outputs) {
+                if (index == operandIndex) {
+                    return true;
+                }
+            }
+        }
+        // BIDIRECTIONAL_SEQUENCE_LSTM and BIDIRECTIONAL_SEQUENCE_RNN can have
+        // either one, two, three or four outputs depending on their
+        // mergeOutputs parameter and if state outputs are provided.
+        // UNIDIRECTIONAL_SEQUENCE_LSTM and UNIDIRECTIONAL_SEQUENCE_RNN can have
+        // either one or three outputs depending on whether state outputs are
+        // provided.
+        if (operation.type == OperationType::UNIDIRECTIONAL_SEQUENCE_LSTM ||
+            operation.type == OperationType::UNIDIRECTIONAL_SEQUENCE_RNN ||
+            operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_LSTM ||
+            operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_RNN) {
+            for (const size_t index : operation.outputs) {
+                if (index == operandIndex) {
+                    return true;
+                }
+            }
+        }
+    }
+    return false;
+}
+
+static void removeOperandTest(const std::shared_ptr<IDevice>& device, const Model& model,
+                              const std::vector<uint32_t>& numberOfConsumers) {
+    for (size_t operand = 0; operand < model.main.operands.size(); ++operand) {
+        if (removeOperandSkip(operand, model, numberOfConsumers)) {
+            continue;
+        }
+        const std::string message = "removeOperandTest: operand " + std::to_string(operand);
+        validate(device, message, model, [operand](Model* model, ExecutionPreference*, Priority*) {
+            removeOperand(model, operand);
+        });
+    }
+}
+
+///////////////////////// REMOVE OPERATION /////////////////////////
+
+static void removeOperation(Model* model, uint32_t index) {
+    auto& operations = model->main.operations;
+    operations.erase(operations.begin() + index);
+}
+
+static void removeOperationTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        const std::string message = "removeOperationTest: operation " + std::to_string(operation);
+        validate(device, message, model,
+                 [operation](Model* model, ExecutionPreference*, Priority*) {
+                     removeOperation(model, operation);
+                 });
+    }
+}
+
+///////////////////////// REMOVE OPERATION INPUT /////////////////////////
+
+static bool removeOperationInputSkip(const Operation& op, size_t input) {
+    // Skip removeOperationInputTest for the following operations.
+    // - CONCATENATION has at least 2 inputs, with the last element being INT32.
+    // - CONV_2D, DEPTHWISE_CONV_2D, MAX_POOL_2D, AVERAGE_POOL_2D, L2_POOL_2D, RESIZE_BILINEAR,
+    //   SPACE_TO_DEPTH, SPACE_TO_DEPTH, SPACE_TO_BATCH_ND, BATCH_TO_SPACE_ND can have an optional
+    //   layout parameter.
+    //   RESIZE_BILINEAR and RESIZE_NEAREST_NEIGHBOR can have optional
+    //   align_corners and half_pixel_centers parameters.
+    // - L2_NORMALIZATION, LOCAL_RESPONSE_NORMALIZATION, SOFTMAX can have an optional axis
+    //   parameter.
+    switch (op.type) {
+        case OperationType::CONCATENATION: {
+            if (op.inputs.size() > 2 && input != op.inputs.size() - 1) {
+                return true;
+            }
+        } break;
+        case OperationType::DEPTHWISE_CONV_2D: {
+            if ((op.inputs.size() == 12 && input == 11) || (op.inputs.size() == 9 && input == 8)) {
+                return true;
+            }
+        } break;
+        case OperationType::CONV_2D:
+        case OperationType::AVERAGE_POOL_2D:
+        case OperationType::MAX_POOL_2D:
+        case OperationType::L2_POOL_2D: {
+            if ((op.inputs.size() == 11 && input == 10) || (op.inputs.size() == 8 && input == 7)) {
+                return true;
+            }
+        } break;
+        case OperationType::RESIZE_BILINEAR: {
+            if (op.inputs.size() >= 4 && input >= 3) {
+                return true;
+            }
+        } break;
+        case OperationType::RESIZE_NEAREST_NEIGHBOR: {
+            if (op.inputs.size() >= 5 && input >= 3) {
+                return true;
+            }
+        } break;
+        case OperationType::SPACE_TO_DEPTH:
+        case OperationType::DEPTH_TO_SPACE:
+        case OperationType::BATCH_TO_SPACE_ND: {
+            if (op.inputs.size() == 3 && input == 2) {
+                return true;
+            }
+        } break;
+        case OperationType::SPACE_TO_BATCH_ND: {
+            if (op.inputs.size() == 4 && input == 3) {
+                return true;
+            }
+        } break;
+        case OperationType::L2_NORMALIZATION: {
+            if (op.inputs.size() == 2 && input == 1) {
+                return true;
+            }
+        } break;
+        case OperationType::LOCAL_RESPONSE_NORMALIZATION: {
+            if (op.inputs.size() == 6 && input == 5) {
+                return true;
+            }
+        } break;
+        case OperationType::SOFTMAX: {
+            if (op.inputs.size() == 3 && input == 2) {
+                return true;
+            }
+        } break;
+        default:
+            break;
+    }
+    return false;
+}
+
+static void removeOperationInputTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        for (size_t input = 0; input < model.main.operations[operation].inputs.size(); ++input) {
+            const Operation& op = model.main.operations[operation];
+            if (removeOperationInputSkip(op, input)) {
+                continue;
+            }
+            const std::string message = "removeOperationInputTest: operation " +
+                                        std::to_string(operation) + ", input " +
+                                        std::to_string(input);
+            validate(device, message, model,
+                     [operation, input](Model* model, ExecutionPreference*, Priority*) {
+                         auto& inputs = model->main.operations[operation].inputs;
+                         inputs.erase(inputs.begin() + input);
+                     });
+        }
+    }
+}
+
+///////////////////////// REMOVE OPERATION OUTPUT /////////////////////////
+
+static void removeOperationOutputTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        for (size_t output = 0; output < model.main.operations[operation].outputs.size();
+             ++output) {
+            const std::string message = "removeOperationOutputTest: operation " +
+                                        std::to_string(operation) + ", output " +
+                                        std::to_string(output);
+            validate(device, message, model,
+                     [operation, output](Model* model, ExecutionPreference*, Priority*) {
+                         auto& outputs = model->main.operations[operation].outputs;
+                         outputs.erase(outputs.begin() + output);
+                     });
+        }
+    }
+}
+
+///////////////////////// MODEL VALIDATION /////////////////////////
+
+// TODO: remove model input
+// TODO: remove model output
+// TODO: add unused operation
+
+///////////////////////// ADD OPERATION INPUT /////////////////////////
+
+static bool addOperationInputSkip(const Operation& op) {
+    // Skip addOperationInputTest for the following operations.
+    // - L2_NORMALIZATION, LOCAL_RESPONSE_NORMALIZATION, SOFTMAX can have an optional INT32 axis
+    //   parameter.
+    if ((op.type == OperationType::L2_NORMALIZATION && op.inputs.size() == 1) ||
+        (op.type == OperationType::LOCAL_RESPONSE_NORMALIZATION && op.inputs.size() == 5) ||
+        (op.type == OperationType::SOFTMAX && op.inputs.size() == 2) ||
+        (op.type == OperationType::RESIZE_BILINEAR && op.inputs.size() < 6) ||
+        (op.type == OperationType::RESIZE_NEAREST_NEIGHBOR && op.inputs.size() < 6)) {
+        return true;
+    }
+    return false;
+}
+
+static void addOperationInputTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        if (addOperationInputSkip(model.main.operations[operation])) {
+            continue;
+        }
+        const std::string message = "addOperationInputTest: operation " + std::to_string(operation);
+        validate(device, message, model,
+                 [operation](Model* model, ExecutionPreference*, Priority*) {
+                     uint32_t index = addOperand(model, OperandLifeTime::SUBGRAPH_INPUT);
+                     model->main.operations[operation].inputs.push_back(index);
+                     model->main.inputIndexes.push_back(index);
+                 });
+    }
+}
+
+///////////////////////// ADD OPERATION OUTPUT /////////////////////////
+
+static void addOperationOutputTest(const std::shared_ptr<IDevice>& device, const Model& model) {
+    for (size_t operation = 0; operation < model.main.operations.size(); ++operation) {
+        const std::string message =
+                "addOperationOutputTest: operation " + std::to_string(operation);
+        validate(device, message, model,
+                 [operation](Model* model, ExecutionPreference*, Priority*) {
+                     uint32_t index = addOperand(model, OperandLifeTime::SUBGRAPH_OUTPUT);
+                     model->main.operations[operation].outputs.push_back(index);
+                     model->main.outputIndexes.push_back(index);
+                 });
+    }
+}
+
+///////////////////////// VALIDATE EXECUTION PREFERENCE /////////////////////////
+
+static const int32_t invalidExecutionPreferences[] = {
+        static_cast<int32_t>(ExecutionPreference::LOW_POWER) - 1,        // lower bound
+        static_cast<int32_t>(ExecutionPreference::SUSTAINED_SPEED) + 1,  // upper bound
+};
+
+static void mutateExecutionPreferenceTest(const std::shared_ptr<IDevice>& device,
+                                          const Model& model) {
+    for (int32_t invalidPreference : invalidExecutionPreferences) {
+        const std::string message =
+                "mutateExecutionPreferenceTest: preference " + std::to_string(invalidPreference);
+        validate(device, message, model,
+                 [invalidPreference](Model*, ExecutionPreference* preference, Priority*) {
+                     *preference = static_cast<ExecutionPreference>(invalidPreference);
+                 });
+    }
+}
+
+///////////////////////// VALIDATE PRIORITY /////////////////////////
+
+static const int32_t invalidPriorities[] = {
+        static_cast<int32_t>(Priority::LOW) - 1,   // lower bound
+        static_cast<int32_t>(Priority::HIGH) + 1,  // upper bound
+};
+
+static void mutateExecutionPriorityTest(const std::shared_ptr<IDevice>& device,
+                                        const Model& model) {
+    for (int32_t invalidPriority : invalidPriorities) {
+        const std::string message =
+                "mutatePriorityTest: priority " + std::to_string(invalidPriority);
+        validate(device, message, model,
+                 [invalidPriority](Model*, ExecutionPreference*, Priority* priority) {
+                     *priority = static_cast<Priority>(invalidPriority);
+                 });
+    }
+}
+
+////////////////////////// ENTRY POINT //////////////////////////////
+
+void validateModel(const std::shared_ptr<IDevice>& device, const Model& model) {
+    const auto numberOfConsumers = nn::countNumberOfConsumers(
+            model.main.operands.size(), nn::convert(model.main.operations).value());
+    mutateExecutionOrderTest(device, model, numberOfConsumers);
+    mutateOperandTypeTest(device, model);
+    mutateOperandRankTest(device, model);
+    mutateOperandScaleTest(device, model);
+    mutateOperandZeroPointTest(device, model);
+    mutateOperandLifeTimeTest(device, model);
+    mutateOperandInputOutputTest(device, model);
+    mutateOperandAddWriterTest(device, model);
+    mutateOperationOperandTypeTest(device, model);
+    mutateOperationTypeTest(device, model);
+    mutateOperationInputOperandIndexTest(device, model);
+    mutateOperationOutputOperandIndexTest(device, model);
+    mutateOperationRemoveWriteTest(device, model, numberOfConsumers);
+    removeOperandTest(device, model, numberOfConsumers);
+    removeOperationTest(device, model);
+    removeOperationInputTest(device, model);
+    removeOperationOutputTest(device, model);
+    addOperationInputTest(device, model);
+    addOperationOutputTest(device, model);
+    mutateExecutionPreferenceTest(device, model);
+    mutateExecutionPriorityTest(device, model);
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/ValidateRequest.cpp b/neuralnetworks/aidl/vts/functional/ValidateRequest.cpp
new file mode 100644
index 0000000..db8f429
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/ValidateRequest.cpp
@@ -0,0 +1,126 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_aidl_hal_test"
+
+#include <android/binder_auto_utils.h>
+
+#include <chrono>
+
+#include <TestHarness.h>
+#include <nnapi/hal/aidl/Utils.h>
+
+#include "Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using ExecutionMutation = std::function<void(Request*)>;
+
+///////////////////////// UTILITY FUNCTIONS /////////////////////////
+
+// Primary validation function. This function will take a valid request, apply a
+// mutation to it to invalidate the request, then pass it to interface calls
+// that use the request.
+static void validate(const std::shared_ptr<IPreparedModel>& preparedModel,
+                     const std::string& message, const Request& originalRequest,
+                     const ExecutionMutation& mutate) {
+    Request request = utils::clone(originalRequest).value();
+    mutate(&request);
+
+    // We'd like to test both with timing requested and without timing
+    // requested. Rather than running each test both ways, we'll decide whether
+    // to request timing by hashing the message. We do not use std::hash because
+    // it is not guaranteed stable across executions.
+    char hash = 0;
+    for (auto c : message) {
+        hash ^= c;
+    };
+    bool measure = (hash & 1);
+
+    // synchronous
+    {
+        SCOPED_TRACE(message + " [executeSynchronously]");
+        ExecutionResult executionResult;
+        const auto executeStatus = preparedModel->executeSynchronously(
+                request, measure, kNoDeadline, kOmittedTimeoutDuration, &executionResult);
+        ASSERT_FALSE(executeStatus.isOk());
+        ASSERT_EQ(executeStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+        ASSERT_EQ(static_cast<ErrorStatus>(executeStatus.getServiceSpecificError()),
+                  ErrorStatus::INVALID_ARGUMENT);
+    }
+
+    // fenced
+    {
+        SCOPED_TRACE(message + " [executeFenced]");
+        ndk::ScopedFileDescriptor syncFence;
+        std::shared_ptr<IFencedExecutionCallback> callback;
+        const auto executeStatus = preparedModel->executeFenced(request, {}, false, kNoDeadline,
+                                                                kOmittedTimeoutDuration,
+                                                                kNoDuration, &syncFence, &callback);
+        ASSERT_FALSE(executeStatus.isOk());
+        ASSERT_EQ(executeStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+        ASSERT_EQ(static_cast<ErrorStatus>(executeStatus.getServiceSpecificError()),
+                  ErrorStatus::INVALID_ARGUMENT);
+    }
+}
+
+///////////////////////// REMOVE INPUT ////////////////////////////////////
+
+static void removeInputTest(const std::shared_ptr<IPreparedModel>& preparedModel,
+                            const Request& request) {
+    for (size_t input = 0; input < request.inputs.size(); ++input) {
+        const std::string message = "removeInput: removed input " + std::to_string(input);
+        validate(preparedModel, message, request, [input](Request* request) {
+            request->inputs.erase(request->inputs.begin() + input);
+        });
+    }
+}
+
+///////////////////////// REMOVE OUTPUT ////////////////////////////////////
+
+static void removeOutputTest(const std::shared_ptr<IPreparedModel>& preparedModel,
+                             const Request& request) {
+    for (size_t output = 0; output < request.outputs.size(); ++output) {
+        const std::string message = "removeOutput: removed Output " + std::to_string(output);
+        validate(preparedModel, message, request, [output](Request* request) {
+            request->outputs.erase(request->outputs.begin() + output);
+        });
+    }
+}
+
+///////////////////////////// ENTRY POINT //////////////////////////////////
+
+void validateRequest(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request) {
+    removeInputTest(preparedModel, request);
+    removeOutputTest(preparedModel, request);
+}
+
+void validateRequestFailure(const std::shared_ptr<IPreparedModel>& preparedModel,
+                            const Request& request) {
+    SCOPED_TRACE("Expecting request to fail [executeSynchronously]");
+    ExecutionResult executionResult;
+    const auto executeStatus = preparedModel->executeSynchronously(
+            request, false, kNoDeadline, kOmittedTimeoutDuration, &executionResult);
+
+    ASSERT_FALSE(executeStatus.isOk());
+    ASSERT_EQ(executeStatus.getExceptionCode(), EX_SERVICE_SPECIFIC);
+    ASSERT_NE(static_cast<ErrorStatus>(executeStatus.getServiceSpecificError()), ErrorStatus::NONE);
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.cpp
new file mode 100644
index 0000000..2d91b8e
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.cpp
@@ -0,0 +1,194 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_aidl_hal_test"
+#include "VtsHalNeuralnetworks.h"
+
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <android/binder_interface_utils.h>
+#include <android/binder_manager.h>
+#include <android/binder_status.h>
+#include <gtest/gtest.h>
+#include <memory>
+#include <string>
+#include <utility>
+
+#include <TestHarness.h>
+#include <aidl/Vintf.h>
+#include <nnapi/hal/aidl/Conversions.h>
+
+#include "Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "Utils.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using implementation::PreparedModelCallback;
+
+// internal helper function
+void createPreparedModel(const std::shared_ptr<IDevice>& device, const Model& model,
+                         std::shared_ptr<IPreparedModel>* preparedModel, bool reportSkipping) {
+    ASSERT_NE(nullptr, preparedModel);
+    *preparedModel = nullptr;
+
+    // see if service can handle model
+    std::vector<bool> supportedOperations;
+    const auto supportedCallStatus = device->getSupportedOperations(model, &supportedOperations);
+    ASSERT_TRUE(supportedCallStatus.isOk());
+    ASSERT_NE(0ul, supportedOperations.size());
+    const bool fullySupportsModel = std::all_of(
+            supportedOperations.begin(), supportedOperations.end(), [](bool v) { return v; });
+
+    // launch prepare model
+    const std::shared_ptr<PreparedModelCallback> preparedModelCallback =
+            ndk::SharedRefBase::make<PreparedModelCallback>();
+    const auto prepareLaunchStatus =
+            device->prepareModel(model, ExecutionPreference::FAST_SINGLE_ANSWER, kDefaultPriority,
+                                 kNoDeadline, {}, {}, kEmptyCacheToken, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk()) << prepareLaunchStatus.getDescription();
+
+    // retrieve prepared model
+    preparedModelCallback->wait();
+    const ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    *preparedModel = preparedModelCallback->getPreparedModel();
+
+    // The getSupportedOperations call returns a list of operations that are guaranteed not to fail
+    // if prepareModel is called, and 'fullySupportsModel' is true i.f.f. the entire model is
+    // guaranteed. If a driver has any doubt that it can prepare an operation, it must return false.
+    // So here, if a driver isn't sure if it can support an operation, but reports that it
+    // successfully prepared the model, the test can continue.
+    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
+        ASSERT_EQ(nullptr, preparedModel->get());
+        if (!reportSkipping) {
+            return;
+        }
+        LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot prepare "
+                     "model that it does not support.";
+        std::cout << "[          ]   Early termination of test because vendor service cannot "
+                     "prepare model that it does not support."
+                  << std::endl;
+        GTEST_SKIP();
+    }
+
+    ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    ASSERT_NE(nullptr, preparedModel->get());
+}
+
+void NeuralNetworksAidlTest::SetUp() {
+    testing::TestWithParam<NeuralNetworksAidlTestParam>::SetUp();
+    ASSERT_NE(kDevice, nullptr);
+}
+
+static NamedDevice makeNamedDevice(const std::string& name) {
+    ndk::SpAIBinder binder(AServiceManager_getService(name.c_str()));
+    return {name, IDevice::fromBinder(binder)};
+}
+
+static std::vector<NamedDevice> getNamedDevicesImpl() {
+    // Retrieves the name of all service instances that implement IDevice,
+    // including any Lazy HAL instances.
+    const std::vector<std::string> names = ::android::getAidlHalInstanceNames(IDevice::descriptor);
+
+    // Get a handle to each device and pair it with its name.
+    std::vector<NamedDevice> namedDevices;
+    namedDevices.reserve(names.size());
+    std::transform(names.begin(), names.end(), std::back_inserter(namedDevices), makeNamedDevice);
+    return namedDevices;
+}
+
+const std::vector<NamedDevice>& getNamedDevices() {
+    const static std::vector<NamedDevice> devices = getNamedDevicesImpl();
+    return devices;
+}
+
+std::string printNeuralNetworksAidlTest(
+        const testing::TestParamInfo<NeuralNetworksAidlTestParam>& info) {
+    return gtestCompliantName(getName(info.param));
+}
+
+INSTANTIATE_DEVICE_TEST(NeuralNetworksAidlTest);
+
+// Forward declaration from ValidateModel.cpp
+void validateModel(const std::shared_ptr<IDevice>& device, const Model& model);
+// Forward declaration from ValidateRequest.cpp
+void validateRequest(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request);
+// Forward declaration from ValidateRequest.cpp
+void validateRequestFailure(const std::shared_ptr<IPreparedModel>& preparedModel,
+                            const Request& request);
+
+void validateEverything(const std::shared_ptr<IDevice>& device, const Model& model,
+                        const Request& request) {
+    validateModel(device, model);
+
+    // Create IPreparedModel.
+    std::shared_ptr<IPreparedModel> preparedModel;
+    createPreparedModel(device, model, &preparedModel);
+    if (preparedModel == nullptr) return;
+
+    validateRequest(preparedModel, request);
+    // HIDL also had test that expected executeFenced to fail on received null fd (-1). This is not
+    // allowed in AIDL and will result in EX_TRANSACTION_FAILED.
+}
+
+void validateFailure(const std::shared_ptr<IDevice>& device, const Model& model,
+                     const Request& request) {
+    // TODO: Should this always succeed?
+    //       What if the invalid input is part of the model (i.e., a parameter).
+    validateModel(device, model);
+
+    // Create IPreparedModel.
+    std::shared_ptr<IPreparedModel> preparedModel;
+    createPreparedModel(device, model, &preparedModel);
+    if (preparedModel == nullptr) return;
+
+    validateRequestFailure(preparedModel, request);
+}
+
+TEST_P(ValidationTest, Test) {
+    const Model model = createModel(kTestModel);
+    ExecutionContext context;
+    const Request request = context.createRequest(kTestModel);
+    if (kTestModel.expectFailure) {
+        validateFailure(kDevice, model, request);
+    } else {
+        validateEverything(kDevice, model, request);
+    }
+}
+
+INSTANTIATE_GENERATED_TEST(ValidationTest, [](const std::string& testName) {
+    // Skip validation for the "inputs_as_internal" and "all_tensors_as_inputs"
+    // generated tests.
+    return testName.find("inputs_as_internal") == std::string::npos &&
+           testName.find("all_tensors_as_inputs") == std::string::npos;
+});
+
+std::string toString(Executor executor) {
+    switch (executor) {
+        case Executor::ASYNC:
+            return "ASYNC";
+        case Executor::SYNC:
+            return "SYNC";
+        case Executor::BURST:
+            return "BURST";
+        case Executor::FENCED:
+            return "FENCED";
+        default:
+            CHECK(false);
+    }
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
diff --git a/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.h
new file mode 100644
index 0000000..9b81ee1
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/VtsHalNeuralnetworks.h
@@ -0,0 +1,61 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_AIDL_VTS_HAL_NEURALNETWORKS_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_AIDL_VTS_HAL_NEURALNETWORKS_H
+
+#include <gtest/gtest.h>
+#include <vector>
+
+#include <aidl/android/hardware/neuralnetworks/IDevice.h>
+
+#include "Callbacks.h"
+#include "Utils.h"
+
+namespace aidl::android::hardware::neuralnetworks::vts::functional {
+
+using NamedDevice = Named<std::shared_ptr<IDevice>>;
+using NeuralNetworksAidlTestParam = NamedDevice;
+
+class NeuralNetworksAidlTest : public testing::TestWithParam<NeuralNetworksAidlTestParam> {
+  protected:
+    void SetUp() override;
+    const std::shared_ptr<IDevice> kDevice = getData(GetParam());
+};
+
+const std::vector<NamedDevice>& getNamedDevices();
+
+std::string printNeuralNetworksAidlTest(
+        const testing::TestParamInfo<NeuralNetworksAidlTestParam>& info);
+
+#define INSTANTIATE_DEVICE_TEST(TestSuite)                                                 \
+    GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(TestSuite);                              \
+    INSTANTIATE_TEST_SUITE_P(PerInstance, TestSuite, testing::ValuesIn(getNamedDevices()), \
+                             printNeuralNetworksAidlTest)
+
+// Create an IPreparedModel object. If the model cannot be prepared,
+// "preparedModel" will be nullptr instead.
+void createPreparedModel(const std::shared_ptr<IDevice>& device, const Model& model,
+                         std::shared_ptr<IPreparedModel>* preparedModel,
+                         bool reportSkipping = true);
+
+enum class Executor { ASYNC, SYNC, BURST, FENCED };
+
+std::string toString(Executor executor);
+
+}  // namespace aidl::android::hardware::neuralnetworks::vts::functional
+
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_AIDL_VTS_HAL_NEURALNETWORKS_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
index b3989e5..fef9d9c 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
@@ -24,15 +24,21 @@
 #include <functional>
 #include <vector>
 
-// Shorthand
+// Shorthands
 namespace android::hardware::neuralnetworks {
 namespace hal = ::android::hardware::neuralnetworks;
 }  // namespace android::hardware::neuralnetworks
 
-// Shorthand
+// Shorthands
+namespace aidl::android::hardware::neuralnetworks {
+namespace aidl_hal = ::aidl::android::hardware::neuralnetworks;
+}  // namespace aidl::android::hardware::neuralnetworks
+
+// Shorthands
 namespace android::nn {
 namespace hal = ::android::hardware::neuralnetworks;
-}
+namespace aidl_hal = ::aidl::android::hardware::neuralnetworks;
+}  // namespace android::nn
 
 namespace android::hardware::neuralnetworks::utils {
 
diff --git a/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumer.aidl b/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumer.aidl
index c8d7645..cd9239e 100644
--- a/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumer.aidl
+++ b/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumer.aidl
@@ -35,6 +35,6 @@
 parcelable EnergyConsumer {
   int id;
   int ordinal;
-  android.hardware.power.stats.EnergyConsumerType type;
+  android.hardware.power.stats.EnergyConsumerType type = android.hardware.power.stats.EnergyConsumerType.OTHER;
   @utf8InCpp String name;
 }
diff --git a/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumerType.aidl b/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumerType.aidl
index 7b05d2f..ce3e1f5 100644
--- a/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumerType.aidl
+++ b/power/stats/aidl/aidl_api/android.hardware.power.stats/current/android/hardware/power/stats/EnergyConsumerType.aidl
@@ -34,6 +34,10 @@
 @VintfStability
 enum EnergyConsumerType {
   OTHER = 0,
-  CPU_CLUSTER = 1,
-  DISPLAY = 2,
+  BLUETOOTH = 1,
+  CPU_CLUSTER = 2,
+  DISPLAY = 3,
+  GNSS = 4,
+  MOBILE_RADIO = 5,
+  WIFI = 6,
 }
diff --git a/power/stats/aidl/android/hardware/power/stats/EnergyConsumer.aidl b/power/stats/aidl/android/hardware/power/stats/EnergyConsumer.aidl
index 2ff1279..ec616f2 100644
--- a/power/stats/aidl/android/hardware/power/stats/EnergyConsumer.aidl
+++ b/power/stats/aidl/android/hardware/power/stats/EnergyConsumer.aidl
@@ -32,10 +32,10 @@
     int ordinal;
 
     /* Type of this EnergyConsumer */
-    EnergyConsumerType type;
+    EnergyConsumerType type = EnergyConsumerType.OTHER;
 
     /**
      * Unique name of this EnergyConsumer. Vendor/device specific. Opaque to framework
      */
     @utf8InCpp String name;
-}
\ No newline at end of file
+}
diff --git a/power/stats/aidl/android/hardware/power/stats/EnergyConsumerType.aidl b/power/stats/aidl/android/hardware/power/stats/EnergyConsumerType.aidl
index 7fd2348..d871ced 100644
--- a/power/stats/aidl/android/hardware/power/stats/EnergyConsumerType.aidl
+++ b/power/stats/aidl/android/hardware/power/stats/EnergyConsumerType.aidl
@@ -20,6 +20,10 @@
 @VintfStability
 enum EnergyConsumerType {
     OTHER,
+    BLUETOOTH,
     CPU_CLUSTER,
     DISPLAY,
-}
\ No newline at end of file
+    GNSS,
+    MOBILE_RADIO,
+    WIFI,
+}
diff --git a/radio/1.6/IRadio.hal b/radio/1.6/IRadio.hal
index 7c00e04..714be47 100644
--- a/radio/1.6/IRadio.hal
+++ b/radio/1.6/IRadio.hal
@@ -344,6 +344,9 @@
      * setPreferredNetworkType, setPreferredNetworkTypesBitmap will not be called anymore
      * except for IRadio v1.5 or older devices.
      *
+     * In case of an emergency call, the modem is authorized to bypass this
+     * restriction.
+     *
      * @param serial Serial number of request.
      * @param networkTypeBitmap a 32-bit bearer bitmap of RadioAccessFamily
      *
@@ -518,4 +521,20 @@
      * Response function is IRadioResponse.getSlicingConfigResponse()
      */
     oneway getSlicingConfig(int32_t serial);
+
+    /**
+     * Provide Carrier specific information to the modem that must be used to
+     * encrypt the IMSI and IMPI. Sent by the framework during boot, carrier
+     * switch and everytime the framework receives a new certificate.
+     *
+     * @param serial Serial number of request.
+     * @param imsiEncryptionInfo ImsiEncryptionInfo as defined in types.hal.
+     *
+     * Response callback is
+     * IRadioResponse.setCarrierInfoForImsiEncryptionResponse()
+     *
+     * Note this API is the same as the 1.1 version except using the 1.6 ImsiEncryptionInfo
+     * as the input param.
+     */
+    oneway setCarrierInfoForImsiEncryption_1_6(int32_t serial, @1.6::ImsiEncryptionInfo imsiEncryptionInfo);
 };
diff --git a/radio/1.6/types.hal b/radio/1.6/types.hal
index 6c23650..5d363c9 100644
--- a/radio/1.6/types.hal
+++ b/radio/1.6/types.hal
@@ -27,6 +27,7 @@
 import @1.1::GeranBands;
 import @1.1::ScanStatus;
 import @1.1::UtranBands;
+import @1.1::ImsiEncryptionInfo;
 import @1.2::Call;
 import @1.2::CellInfoCdma;
 import @1.2::CellConnectionStatus;
@@ -1115,3 +1116,20 @@
     MODE_2 = 2,
     MODE_3 = 3,
 };
+
+/**
+ * Public key type from carrier certificate.
+ */
+enum PublicKeyType : int32_t {
+    EPDG    = 1,                   // Key type to be used for ePDG
+    WLAN    = 2,                   // Key type to be used for WLAN
+};
+
+/**
+ * Carrier specific Information sent by the carrier,
+ * which will be used to encrypt the IMSI and IMPI.
+ */
+struct ImsiEncryptionInfo {
+    @1.1::ImsiEncryptionInfo base;
+    PublicKeyType keyType;         // Public key type
+};
diff --git a/radio/1.6/vts/functional/radio_hidl_hal_api.cpp b/radio/1.6/vts/functional/radio_hidl_hal_api.cpp
index 07b8ccb..fb50990 100644
--- a/radio/1.6/vts/functional/radio_hidl_hal_api.cpp
+++ b/radio/1.6/vts/functional/radio_hidl_hal_api.cpp
@@ -676,3 +676,29 @@
     EXPECT_EQ(serial, radioRsp_v1_6->rspInfo.serial);
     EXPECT_EQ(::android::hardware::radio::V1_6::RadioError::NONE, radioRsp_v1_6->rspInfo.error);
 }
+
+/*
+ * Test IRadio.setCarrierInfoForImsiEncryption_1_6() for the response returned.
+ */
+TEST_P(RadioHidlTest_v1_6, setCarrierInfoForImsiEncryption_1_6) {
+    serial = GetRandomSerialNumber();
+    ::android::hardware::radio::V1_6::ImsiEncryptionInfo imsiInfo;
+    imsiInfo.base.mcc = "310";
+    imsiInfo.base.mnc = "004";
+    imsiInfo.base.carrierKey = (std::vector<uint8_t>){1, 2, 3, 4, 5, 6};
+    imsiInfo.base.keyIdentifier = "Test";
+    imsiInfo.base.expirationTime = 20180101;
+    imsiInfo.keyType = PublicKeyType::EPDG;
+
+    radio_v1_6->setCarrierInfoForImsiEncryption_1_6(serial, imsiInfo);
+    EXPECT_EQ(std::cv_status::no_timeout, wait());
+    EXPECT_EQ(RadioResponseType::SOLICITED, radioRsp_v1_6->rspInfo.type);
+    EXPECT_EQ(serial, radioRsp_v1_6->rspInfo.serial);
+
+    if (cardStatus.base.base.base.cardState == CardState::ABSENT) {
+        ASSERT_TRUE(CheckAnyOfErrors(
+                radioRsp_v1_6->rspInfo.error,
+                {::android::hardware::radio::V1_6::RadioError::NONE,
+                 ::android::hardware::radio::V1_6::RadioError::REQUEST_NOT_SUPPORTED}));
+    }
+}
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/AttestationKey.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/AttestationKey.aidl
new file mode 100644
index 0000000..893b016
--- /dev/null
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/AttestationKey.aidl
@@ -0,0 +1,39 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.security.keymint;
+@RustDerive(Clone=true, Eq=true, Hash=true, Ord=true, PartialEq=true, PartialOrd=true) @VintfStability
+parcelable AttestationKey {
+  byte[] keyBlob;
+  android.hardware.security.keymint.KeyParameter[] attestKeyParams;
+  byte[] issuerSubjectName;
+}
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/ErrorCode.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/ErrorCode.aidl
index a35b46c..3faba48 100644
--- a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/ErrorCode.aidl
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/ErrorCode.aidl
@@ -113,6 +113,8 @@
   UNSUPPORTED_MGF_DIGEST = -79,
   MISSING_NOT_BEFORE = -80,
   MISSING_NOT_AFTER = -81,
+  MISSING_ISSUER_SUBJECT = -82,
+  INVALID_ISSUER_SUBJECT = -83,
   UNIMPLEMENTED = -100,
   VERSION_MISMATCH = -101,
   UNKNOWN_ERROR = -1000,
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/IKeyMintDevice.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/IKeyMintDevice.aidl
index 132135b..d3c6910 100644
--- a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/IKeyMintDevice.aidl
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/IKeyMintDevice.aidl
@@ -35,13 +35,15 @@
 interface IKeyMintDevice {
   android.hardware.security.keymint.KeyMintHardwareInfo getHardwareInfo();
   void addRngEntropy(in byte[] data);
-  android.hardware.security.keymint.KeyCreationResult generateKey(in android.hardware.security.keymint.KeyParameter[] keyParams);
-  android.hardware.security.keymint.KeyCreationResult importKey(in android.hardware.security.keymint.KeyParameter[] keyParams, in android.hardware.security.keymint.KeyFormat keyFormat, in byte[] keyData);
+  android.hardware.security.keymint.KeyCreationResult generateKey(in android.hardware.security.keymint.KeyParameter[] keyParams, in @nullable android.hardware.security.keymint.AttestationKey attestationKey);
+  android.hardware.security.keymint.KeyCreationResult importKey(in android.hardware.security.keymint.KeyParameter[] keyParams, in android.hardware.security.keymint.KeyFormat keyFormat, in byte[] keyData, in @nullable android.hardware.security.keymint.AttestationKey attestationKey);
   android.hardware.security.keymint.KeyCreationResult importWrappedKey(in byte[] wrappedKeyData, in byte[] wrappingKeyBlob, in byte[] maskingKey, in android.hardware.security.keymint.KeyParameter[] unwrappingParams, in long passwordSid, in long biometricSid);
-  byte[] upgradeKey(in byte[] inKeyBlobToUpgrade, in android.hardware.security.keymint.KeyParameter[] inUpgradeParams);
-  void deleteKey(in byte[] inKeyBlob);
+  byte[] upgradeKey(in byte[] keyBlobToUpgrade, in android.hardware.security.keymint.KeyParameter[] upgradeParams);
+  void deleteKey(in byte[] keyBlob);
   void deleteAllKeys();
   void destroyAttestationIds();
-  android.hardware.security.keymint.BeginResult begin(in android.hardware.security.keymint.KeyPurpose inPurpose, in byte[] inKeyBlob, in android.hardware.security.keymint.KeyParameter[] inParams, in android.hardware.security.keymint.HardwareAuthToken inAuthToken);
+  android.hardware.security.keymint.BeginResult begin(in android.hardware.security.keymint.KeyPurpose purpose, in byte[] keyBlob, in android.hardware.security.keymint.KeyParameter[] params, in android.hardware.security.keymint.HardwareAuthToken authToken);
+  void deviceLocked(in boolean passwordOnly, in @nullable android.hardware.security.secureclock.TimeStampToken timestampToken);
+  void earlyBootEnded();
   const int AUTH_TOKEN_MAC_LENGTH = 32;
 }
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/IRemotelyProvisionedComponent.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/IRemotelyProvisionedComponent.aidl
new file mode 100644
index 0000000..a864c3c
--- /dev/null
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/IRemotelyProvisionedComponent.aidl
@@ -0,0 +1,43 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.security.keymint;
+@VintfStability
+interface IRemotelyProvisionedComponent {
+  byte[] generateEcdsaP256KeyPair(in boolean testMode, out android.hardware.security.keymint.MacedPublicKey macedPublicKey);
+  void generateCertificateRequest(in boolean testMode, in android.hardware.security.keymint.MacedPublicKey[] keysToSign, in byte[] endpointEncryptionCertChain, in byte[] challenge, out byte[] keysToSignMac, out android.hardware.security.keymint.ProtectedData protectedData);
+  const int STATUS_FAILED = 1;
+  const int STATUS_INVALID_MAC = 2;
+  const int STATUS_PRODUCTION_KEY_IN_TEST_REQUEST = 3;
+  const int STATUS_TEST_KEY_IN_PRODUCTION_REQUEST = 4;
+  const int STATUS_INVALID_EEK = 5;
+}
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyMintHardwareInfo.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyMintHardwareInfo.aidl
index 93966ea..d06312a 100644
--- a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyMintHardwareInfo.aidl
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyMintHardwareInfo.aidl
@@ -37,4 +37,5 @@
   android.hardware.security.keymint.SecurityLevel securityLevel;
   @utf8InCpp String keyMintName;
   @utf8InCpp String keyMintAuthorName;
+  boolean timestampTokenRequired;
 }
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyPurpose.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyPurpose.aidl
index c1e92af..61bb7e4 100644
--- a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyPurpose.aidl
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/KeyPurpose.aidl
@@ -39,4 +39,5 @@
   VERIFY = 3,
   WRAP_KEY = 5,
   AGREE_KEY = 6,
+  ATTEST_KEY = 7,
 }
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/MacedPublicKey.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/MacedPublicKey.aidl
new file mode 100644
index 0000000..b4caeed
--- /dev/null
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/MacedPublicKey.aidl
@@ -0,0 +1,37 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.security.keymint;
+@VintfStability
+parcelable MacedPublicKey {
+  byte[] macedKey;
+}
diff --git a/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/ProtectedData.aidl b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/ProtectedData.aidl
new file mode 100644
index 0000000..46f602f
--- /dev/null
+++ b/security/keymint/aidl/aidl_api/android.hardware.security.keymint/current/android/hardware/security/keymint/ProtectedData.aidl
@@ -0,0 +1,37 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
+// THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
+///////////////////////////////////////////////////////////////////////////////
+
+// This file is a snapshot of an AIDL file. Do not edit it manually. There are
+// two cases:
+// 1). this is a frozen version file - do not edit this in any case.
+// 2). this is a 'current' file. If you make a backwards compatible change to
+//     the interface (from the latest frozen version), the build system will
+//     prompt you to update this file with `m <name>-update-api`.
+//
+// You must not make a backward incompatible change to any AIDL file built
+// with the aidl_interface module type with versions property set. The module
+// type is used to build AIDL files in a way that they can be used across
+// independently updatable components of the system. If a device is shipped
+// with such a backward incompatible change, it has a high risk of breaking
+// later when a module using the interface is updated, e.g., Mainline modules.
+
+package android.hardware.security.keymint;
+@VintfStability
+parcelable ProtectedData {
+  byte[] protectedData;
+}
diff --git a/security/keymint/aidl/android/hardware/security/keymint/AttestationKey.aidl b/security/keymint/aidl/android/hardware/security/keymint/AttestationKey.aidl
new file mode 100644
index 0000000..8167ceb
--- /dev/null
+++ b/security/keymint/aidl/android/hardware/security/keymint/AttestationKey.aidl
@@ -0,0 +1,32 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.security.keymint;
+
+import android.hardware.security.keymint.KeyParameter;
+
+/**
+ * Contains a key blob with Tag::ATTEST_KEY that can be used to sign an attestation certificate,
+ * and the DER-encoded X.501 Subject Name that will be placed in the Issuer field of the attestation
+ * certificate.
+ */
+@VintfStability
+@RustDerive(Clone=true, Eq=true, PartialEq=true, Ord=true, PartialOrd=true, Hash=true)
+parcelable AttestationKey {
+    byte[] keyBlob;
+    KeyParameter[] attestKeyParams;
+    byte[] issuerSubjectName;
+}
diff --git a/security/keymint/aidl/android/hardware/security/keymint/ErrorCode.aidl b/security/keymint/aidl/android/hardware/security/keymint/ErrorCode.aidl
index 35e3827..5765130 100644
--- a/security/keymint/aidl/android/hardware/security/keymint/ErrorCode.aidl
+++ b/security/keymint/aidl/android/hardware/security/keymint/ErrorCode.aidl
@@ -103,6 +103,8 @@
     UNSUPPORTED_MGF_DIGEST = -79,
     MISSING_NOT_BEFORE = -80,
     MISSING_NOT_AFTER = -81,
+    MISSING_ISSUER_SUBJECT = -82,
+    INVALID_ISSUER_SUBJECT = -83,
 
     UNIMPLEMENTED = -100,
     VERSION_MISMATCH = -101,
diff --git a/security/keymint/aidl/android/hardware/security/keymint/IKeyMintDevice.aidl b/security/keymint/aidl/android/hardware/security/keymint/IKeyMintDevice.aidl
index 0120a30..13e98af 100644
--- a/security/keymint/aidl/android/hardware/security/keymint/IKeyMintDevice.aidl
+++ b/security/keymint/aidl/android/hardware/security/keymint/IKeyMintDevice.aidl
@@ -16,16 +16,18 @@
 
 package android.hardware.security.keymint;
 
+import android.hardware.security.keymint.AttestationKey;
 import android.hardware.security.keymint.BeginResult;
 import android.hardware.security.keymint.ByteArray;
 import android.hardware.security.keymint.HardwareAuthToken;
 import android.hardware.security.keymint.IKeyMintOperation;
 import android.hardware.security.keymint.KeyCreationResult;
 import android.hardware.security.keymint.KeyFormat;
-import android.hardware.security.keymint.KeyParameter;
 import android.hardware.security.keymint.KeyMintHardwareInfo;
+import android.hardware.security.keymint.KeyParameter;
 import android.hardware.security.keymint.KeyPurpose;
 import android.hardware.security.keymint.SecurityLevel;
+import android.hardware.security.secureclock.TimeStampToken;
 
 /**
  * KeyMint device definition.
@@ -314,9 +316,18 @@
      *        provided in params.  See above for detailed specifications of which tags are required
      *        for which types of keys.
      *
+     * @param attestationKey, if provided, specifies the key that must be used to sign the
+     *        attestation certificate.  If `keyParams` does not contain a Tag::ATTESTATION_CHALLENGE
+     *        but `attestationKey` is non-null, the IKeyMintDevice must return
+     *        ErrorCode::INVALID_ARGUMENT.  If the provided AttestationKey does not contain a key
+     *        blob containing an asymmetric key with KeyPurpose::ATTEST_KEY, the IKeyMintDevice must
+     *        return ErrorCode::INVALID_PURPOSE.  If the provided AttestationKey has an empty issuer
+     *        subject name, the IKeyMintDevice must return ErrorCode::INVALID_ARGUMENT.
+     *
      * @return The result of key creation.  See KeyCreationResult.aidl.
      */
-    KeyCreationResult generateKey(in KeyParameter[] keyParams);
+    KeyCreationResult generateKey(
+            in KeyParameter[] keyParams, in @nullable AttestationKey attestationKey);
 
     /**
      * Imports key material into an IKeyMintDevice.  Key definition parameters and return values
@@ -344,10 +355,18 @@
      *
      * @param inKeyData The key material to import, in the format specified in keyFormat.
      *
+     * @param attestationKey, if provided, specifies the key that must be used to sign the
+     *        attestation certificate.  If `keyParams` does not contain a Tag::ATTESTATION_CHALLENGE
+     *        but `attestationKey` is non-null, the IKeyMintDevice must return
+     *        ErrorCode::INVALID_ARGUMENT.  If the provided AttestationKey does not contain a key
+     *        blob containing an asymmetric key with KeyPurpose::ATTEST_KEY, the IKeyMintDevice must
+     *        return ErrorCode::INVALID_PURPOSE.  If the provided AttestationKey has an empty issuer
+     *        subject name, the IKeyMintDevice must return ErrorCode::INVALID_ARGUMENT.
+     *
      * @return The result of key creation.  See KeyCreationResult.aidl.
      */
     KeyCreationResult importKey(in KeyParameter[] keyParams, in KeyFormat keyFormat,
-                                in byte[] keyData);
+            in byte[] keyData, in @nullable AttestationKey attestationKey);
 
     /**
      * Securely imports a key, or key pair, returning a key blob and a description of the imported
@@ -429,12 +448,9 @@
      *
      * @return The result of key creation.  See KeyCreationResult.aidl.
      */
-     KeyCreationResult importWrappedKey(in byte[] wrappedKeyData,
-                                        in byte[] wrappingKeyBlob,
-                                        in byte[] maskingKey,
-                                        in KeyParameter[] unwrappingParams,
-                                        in long passwordSid,
-                                        in long biometricSid);
+    KeyCreationResult importWrappedKey(in byte[] wrappedKeyData, in byte[] wrappingKeyBlob,
+            in byte[] maskingKey, in KeyParameter[] unwrappingParams, in long passwordSid,
+            in long biometricSid);
 
     /**
      * Upgrades an old key blob.  Keys can become "old" in two ways: IKeyMintDevice can be
@@ -469,7 +485,7 @@
      * @return A new key blob that references the same key as keyBlobToUpgrade, but is in the new
      *         format, or has the new version data.
      */
-    byte[] upgradeKey(in byte[] inKeyBlobToUpgrade, in KeyParameter[] inUpgradeParams);
+    byte[] upgradeKey(in byte[] keyBlobToUpgrade, in KeyParameter[] upgradeParams);
 
     /**
      * Deletes the key, or key pair, associated with the key blob.  Calling this function on
@@ -479,7 +495,7 @@
      *
      * @param inKeyBlob The opaque descriptor returned by generateKey() or importKey();
      */
-    void deleteKey(in byte[] inKeyBlob);
+    void deleteKey(in byte[] keyBlob);
 
     /**
      * Deletes all keys in the hardware keystore.  Used when keystore is reset completely.  After
@@ -705,8 +721,44 @@
      *         from operations that generate an IV or nonce, and IKeyMintOperation object pointer
      *         which is used to perform update(), finish() or abort() operations.
      */
-    BeginResult begin(in KeyPurpose inPurpose,
-               in byte[] inKeyBlob,
-               in KeyParameter[] inParams,
-               in HardwareAuthToken inAuthToken);
+    BeginResult begin(in KeyPurpose purpose, in byte[] keyBlob, in KeyParameter[] params,
+            in HardwareAuthToken authToken);
+
+    /**
+     * Called by client to notify the IKeyMintDevice that the device is now locked, and keys with
+     * the UNLOCKED_DEVICE_REQUIRED tag should no longer be usable.  When this function is called,
+     * the IKeyMintDevice should note the current timestamp, and attempts to use
+     * UNLOCKED_DEVICE_REQUIRED keys must be rejected with Error::DEVICE_LOCKED until an
+     * authentication token with a later timestamp is presented.  If the `passwordOnly' argument is
+     * set to true the sufficiently-recent authentication token must indicate that the user
+     * authenticated with a password, not a biometric.
+     *
+     * Note that the IKeyMintDevice UNLOCKED_DEVICE_REQUIRED semantics are slightly different from
+     * the UNLOCKED_DEVICE_REQUIRED semantics enforced by keystore.  Keystore handles device locking
+     * on a per-user basis.  Because auth tokens do not contain an Android user ID, it's not
+     * possible to replicate the keystore enformcement logic in IKeyMintDevice.  So from the
+     * IKeyMintDevice perspective, any user unlock unlocks all UNLOCKED_DEVICE_REQUIRED keys.
+     * Keystore will continue enforcing the per-user device locking.
+     *
+     * @param passwordOnly specifies whether the device must be unlocked with a password, rather
+     * than a biometric, before UNLOCKED_DEVICE_REQUIRED keys can be used.
+     *
+     * @param timestampToken is used by StrongBox implementations of IKeyMintDevice.  It
+     * provides the StrongBox IKeyMintDevice with a fresh, MACed timestamp which it can use as the
+     * device-lock time, for future comparison against auth tokens when operations using
+     * UNLOCKED_DEVICE_REQUIRED keys are attempted.  Unless the auth token timestamp is newer than
+     * the timestamp in the timestampToken, the device is still considered to be locked.
+     * Crucially, if a StrongBox IKeyMintDevice receives a deviceLocked() call with a timestampToken
+     * timestamp that is less than the timestamp in the last deviceLocked() call, it must ignore the
+     * new timestamp.  TEE IKeyMintDevice implementations will receive an empty timestampToken (zero
+     * values and empty vectors) and should use their own clock as the device-lock time.
+     */
+    void deviceLocked(in boolean passwordOnly, in @nullable TimeStampToken timestampToken);
+
+    /**
+     * Called by client to notify the IKeyMintDevice that the device has left the early boot
+     * state, and that keys with the EARLY_BOOT_ONLY tag may no longer be used.  All attempts to use
+     * an EARLY_BOOT_ONLY key after this method is called must fail with Error::INVALID_KEY_BLOB.
+     */
+    void earlyBootEnded();
 }
diff --git a/security/keymint/aidl/android/hardware/security/keymint/IRemotelyProvisionedComponent.aidl b/security/keymint/aidl/android/hardware/security/keymint/IRemotelyProvisionedComponent.aidl
new file mode 100644
index 0000000..1b09e9d
--- /dev/null
+++ b/security/keymint/aidl/android/hardware/security/keymint/IRemotelyProvisionedComponent.aidl
@@ -0,0 +1,262 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.security.keymint;
+
+import android.hardware.security.keymint.MacedPublicKey;
+import android.hardware.security.keymint.ProtectedData;
+
+/**
+ * An IRemotelyProvisionedComponent is a secure-side component for which certificates can be
+ * remotely provisioned. It provides an interface for generating asymmetric key pairs and then
+ * creating a CertificateRequest that contains the generated public keys, plus other information to
+ * authenticate the request origin. The CertificateRequest can be sent to a server, which can
+ * validate the request and create certificates.
+ *
+ * This interface does not provide any way to use the generated and certified key pairs. It's
+ * intended to be implemented by a HAL service that does other things with keys (e.g. Keymint).
+ *
+ * The root of trust for secure provisioning is something called the "Boot Certificate Chain", or
+ * BCC. The BCC is a chain of public key certificates, represented as COSE_Sign1 objects containing
+ * COSE_Key representations of the public keys. The "root" of the BCC is a self-signed certificate
+ * for a device-unique public key, denoted DK_pub. All public keys in the BCC are device-unique. The
+ * public key from each certificate in the chain is used to sign the next certificate in the
+ * chain. The final, "leaf" certificate contains a public key, denoted KM_pub, whose corresponding
+ * private key, denoted KM_priv, is available for use by the IRemotelyProvisionedComponent.
+ *
+ * BCC Design
+ * ==========
+ *
+ * The BCC is designed to mirror the boot stages of a device, and to prove the content and integrity
+ * of each firmware image. In a proper BCC, each boot stage hashes its own private key with the code
+ * and any relevant configuration parameters of the next stage to produce a key pair for the next
+ * stage. Each stage also uses its own private key to sign the public key of the next stage,
+ * including in the certificate the hash of the next firmware stage, then loads the next stage,
+ * passing the private key and certificate to it in a manner that does not leak the private key to
+ * later boot stages. The BCC root key pair is generated by immutable code (e.g. ROM), from a
+ * device-unique secret. After the device-unique secret is used, it must be made unavailable to any
+ * later boot stage.
+ *
+ * In this way, booting the device incrementally builds a certificate chain that (a) identifies and
+ * validates the integrity of every stage and (b) contains a set of public keys that correspond to
+ * private keys, one known to each stage. Any stage can compute the secrets of all later stages
+ * (given the necessary input), but no stage can compute the secret of any preceding stage. Updating
+ * the firmware or configuration of any stage changes the key pair of that stage, and of all
+ * subsequent stages, and no attacker who compromised the previous version of the updated firmware
+ * can know or predict the post-update key pairs.
+ *
+ * The first BCC certificate is special because its contained public key, DK_pub, will never change,
+ * making it a permanent, device-unique identifier. Although the remaining keys in the BCC are also
+ * device-unique, they are not necessarily permanent, since they can change when the device software
+ * is updated.
+ *
+ * When the provisioning server receives a message signed by KM_priv and containing a BCC that
+ * chains from DK_pub to KM_pub, it can be certain that (barring vulnerabilities in some boot
+ * stage), the CertificateRequest came from the device associated with DK_pub, running the specific
+ * software identified by the certificates in the BCC. If the server has some mechanism for knowing
+ * which the DK_pub values of "valid" devices, it can determine whether signing certificates is
+ * appropriate.
+ *
+ * Degenerate BCCs
+ * ===============
+ *
+ * While a proper BCC, as described above, reflects the complete boot sequence from boot ROM to the
+ * secure area image of the IRemotelyProvisionedComponent, it's also possible to use a "degenerate"
+ * BCC which consists only of a single, self-signed certificate containing the public key of a
+ * hardware-bound key pair. This is an appopriate solution for devices which haven't implemented
+ * everything necessary to produce a proper BCC, but can derive a unique key pair in the secure
+ * area.  In this degenerate case, DK_pub is the same as KM_pub.
+ *
+ * BCC Privacy
+ * ===========
+ *
+ * Because the BCC constitutes an unspoofable, device-unique identifier, special care is taken to
+ * prevent its availability to entities who may wish to track devices. Two precautions are taken:
+ *
+ * 1.  The BCC is never exported from the IRemotelyProvisionedComponent except in encrypted
+ *     form. The portion of the CertificateRequest that contains the BCC is encrypted using an
+ *     Endpoint Encryption Key (EEK).  The EEK is provided in the form of a certificate chain whose
+ *     root must be pre-provisioned into the secure area (hardcoding the roots into the secure area
+ *     firmware image is a recommended approach). Multiple roots may be provisioned. If the provided
+ *     EEK does not chain back to this already-known root, the IRemotelyProvisionedComponent must
+ *     reject it.
+ *
+ * 2.  Precaution 1 above ensures that only an entity with a valid EEK private key can decrypt the
+ *     BCC. To make it feasible to build a provisioning server which cannot use the BCC to track
+ *     devices, the CertificateRequest is structured so that the server can be partitioned into two
+ *     components.  The "decrypter" decrypts the BCC, verifies DK_pub and the device's right to
+ *     receive provisioned certificates, but does not see the public keys to be signed or the
+ *     resulting certificates.  The "certifier" gets informed of the results of the decrypter's
+ *     validation and sees the public keys to be signed and resulting certificates, but does not see
+ *     the BCC.
+ *
+ * Test Mode
+ * =========
+ *
+ * The IRemotelyProvisionedComponent supports a test mode, allowing the generation of test key pairs
+ * and test CertificateRequests. Test keys/requests are annotated as such, and the BCC used for test
+ * CertificateRequests must contain freshly-generated keys, not the real BCC key pairs.
+ */
+@VintfStability
+interface IRemotelyProvisionedComponent {
+    const int STATUS_FAILED = 1;
+    const int STATUS_INVALID_MAC = 2;
+    const int STATUS_PRODUCTION_KEY_IN_TEST_REQUEST = 3;
+    const int STATUS_TEST_KEY_IN_PRODUCTION_REQUEST = 4;
+    const int STATUS_INVALID_EEK = 5;
+
+    /**
+     * generateKeyPair generates a new ECDSA P-256 key pair that can be certified.  Note that this
+     * method only generates ECDSA P-256 key pairs, but the interface can be extended to add methods
+     * for generating keys for other algorithms, if necessary.
+     *
+     * @param in boolean testMode indicates whether the generated key is for testing only. Test keys
+     *        are marked (see the definition of PublicKey in the MacedPublicKey structure) to
+     *        prevent them from being confused with production keys.
+     *
+     * @param out MacedPublicKey macedPublicKey contains the public key of the generated key pair,
+     *        MACed so that generateCertificateRequest can easily verify, without the
+     *        privateKeyHandle, that the contained public key is for remote certification.
+     *
+     * @return data representing a handle to the private key. The format is implementation-defined,
+     *         but note that specific services may define a required format.
+     */
+    byte[] generateEcdsaP256KeyPair(in boolean testMode, out MacedPublicKey macedPublicKey);
+
+    /**
+     * generateCertificateRequest creates a certificate request to be sent to the provisioning
+     * server.
+     *
+     * @param in boolean testMode indicates whether the generated certificate request is for testing
+     *        only.
+     *
+     * @param in MacedPublicKey[] keysToSign contains the set of keys to certify. The
+     *        IRemotelyProvisionedComponent must validate the MACs on each key.  If any entry in the
+     *        array lacks a valid MAC, the method must return STATUS_INVALID_MAC.
+     *
+     *        If testMode is true, the keysToCertify array must contain only keys flagged as test
+     *        keys. Otherwise, the method must return STATUS_PRODUCTION_KEY_IN_TEST_REQUEST.
+     *
+     *        If testMode is false, the keysToCertify array must not contain any keys flagged as
+     *        test keys. Otherwise, the method must return STATUS_TEST_KEY_IN_PRODUCTION_REQUEST.
+     *
+     * @param in endpointEncryptionKey contains an X25519 public key which will be used to encrypt
+     *        the BCC. For flexibility, this is represented as a certificate chain, represented as a
+     *        CBOR array of COSE_Sign1 objects, ordered from root to leaf. The leaf contains the
+     *        X25519 encryption key, each other element is an Ed25519 key signing the next in the
+     *        chain. The root is self-signed.
+     *
+     *            EekChain = [ + SignedSignatureKey, SignedEek ]
+     *
+     *            SignedSignatureKey = [              // COSE_Sign1
+     *                protected: bstr .cbor {
+     *                    1 : -8,                     // Algorithm : EdDSA
+     *                },
+     *                unprotected: bstr .size 0
+     *                payload: bstr .cbor SignatureKey,
+     *                signature: bstr PureEd25519(.cbor SignatureKeySignatureInput)
+     *            ]
+     *
+     *            SignatureKey = {                    // COSE_Key
+     *                 1 : 1,                         // Key type : Octet Key Pair
+     *                 3 : -8,                        // Algorithm : EdDSA
+     *                 -1 : 6,                        // Curve : Ed25519
+     *                 -2 : bstr                      // Ed25519 public key
+     *            }
+     *
+     *            SignatureKeySignatureInput = [
+     *                context: "Signature1",
+     *                body_protected: bstr .cbor {
+     *                    1 : -8,                     // Algorithm : EdDSA
+     *                },
+     *                external_aad: bstr .size 0,
+     *                payload: bstr .cbor SignatureKey
+     *            ]
+     *
+     *            SignedEek = [                       // COSE_Sign1
+     *                protected: bstr .cbor {
+     *                    1 : -8,                     // Algorithm : EdDSA
+     *                },
+     *                unprotected: bstr .size 0
+     *                payload: bstr .cbor Eek,
+     *                signature: bstr PureEd25519(.cbor EekSignatureInput)
+     *            ]
+     *
+     *            Eek = {                             // COSE_Key
+     *                1 : 1,                          // Key type : Octet Key Pair
+     *                2 : bstr                        // KID : EEK ID
+     *                3 : -25,                        // Algorithm : ECDH-ES + HKDF-256
+     *                -1 : 4,                         // Curve : X25519
+     *                -2 : bstr                       // Ed25519 public key
+     *            }
+     *
+     *            EekSignatureInput = [
+     *                context: "Signature1",
+     *                body_protected: bstr .cbor {
+     *                    1 : -8,                     // Algorithm : EdDSA
+     *                },
+     *                external_aad: bstr .size 0,
+     *                payload: bstr .cbor Eek
+     *            ]
+     *
+     *        If the contents of endpointEncryptionKey do not match the SignedEek structure above,
+     *        the method must return STATUS_INVALID_EEK.
+     *
+     *        If testMode is true, the method must ignore the length and content of the signatures
+     *        in the chain, which implies that it must not attempt to validate the signature.
+     *
+     *        If testMode is false, the method must validate the chain signatures, and must verify
+     *        that the public key in the root certifictate is in its pre-configured set of
+     *        authorized EEK root keys. If the public key is not in the database, or if signature
+     *        verification fails, the method must return STATUS_INVALID_EEK.
+     *
+     * @param in challenge contains a byte string from the provisioning server that must be signed
+     *        by the secure area. See the description of the 'signature' output parameter for
+     *        details.
+     *
+     * @param out keysToSignMac contains the MAC of KeysToSign in the CertificateRequest
+     *        structure. Specifically, it contains:
+     *
+     *            HMAC-256(EK_mac, .cbor KeysToMacStructure)
+     *
+     *        Where EK_mac is an ephemeral MAC key, found in ProtectedData (see below).  The MACed
+     *        data is the "tag" field of a COSE_Mac0 structure like:
+     *
+     *            MacedKeys = [                            // COSE_Mac0
+     *                protected : bstr .cbor {
+     *                    1 : 5,                           // Algorithm : HMAC-256
+     *                },
+     *                unprotected : bstr .size 0,
+     *                // Payload is PublicKeys from keysToSign argument, in provided order.
+     *                payload: bstr .cbor [ * PublicKey ],
+     *                tag: bstr
+     *           ]
+     *
+     *            KeysToMacStructure = [
+     *                context : "MAC0",
+     *                protected : bstr .cbor { 1 : 5 },    // Algorithm : HMAC-256
+     *                external_aad : bstr .size 0,
+     *                // Payload is PublicKeys from keysToSign argument, in provided order.
+     *                payload : bstr .cbor [ * PublicKey ]
+     *            ]
+     *
+     * @param out ProtectedData contains the encrypted BCC and the ephemeral MAC key used to
+     *        authenticate the keysToSign (see keysToSignMac output argument).
+     */
+    void generateCertificateRequest(in boolean testMode, in MacedPublicKey[] keysToSign,
+            in byte[] endpointEncryptionCertChain, in byte[] challenge, out byte[] keysToSignMac,
+            out ProtectedData protectedData);
+}
diff --git a/security/keymint/aidl/android/hardware/security/keymint/KeyMintHardwareInfo.aidl b/security/keymint/aidl/android/hardware/security/keymint/KeyMintHardwareInfo.aidl
index 1a107ba..2fcaf4c 100644
--- a/security/keymint/aidl/android/hardware/security/keymint/KeyMintHardwareInfo.aidl
+++ b/security/keymint/aidl/android/hardware/security/keymint/KeyMintHardwareInfo.aidl
@@ -45,4 +45,11 @@
      *         same author.
      */
     @utf8InCpp String keyMintAuthorName;
+
+    /* The timestampTokenRequired is a boolean flag, which when true reflects that IKeyMintDevice
+     * instance will expect a valid TimeStampToken with various operations. This will typically
+     * required by the StrongBox implementations that generally don't have secure clock hardware to
+     * generate timestamp tokens.
+     */
+    boolean timestampTokenRequired;
 }
diff --git a/security/keymint/aidl/android/hardware/security/keymint/KeyPurpose.aidl b/security/keymint/aidl/android/hardware/security/keymint/KeyPurpose.aidl
index 68c1740..978a027 100644
--- a/security/keymint/aidl/android/hardware/security/keymint/KeyPurpose.aidl
+++ b/security/keymint/aidl/android/hardware/security/keymint/KeyPurpose.aidl
@@ -16,12 +16,11 @@
 
 package android.hardware.security.keymint;
 
-
 /**
  * Possible purposes of a key (or pair).
  */
 @VintfStability
-@Backing(type = "int")
+@Backing(type="int")
 enum KeyPurpose {
     /* Usable with RSA, EC and AES keys. */
     ENCRYPT = 0,
@@ -42,5 +41,7 @@
     /* Key Agreement, usable with EC keys. */
     AGREE_KEY = 6,
 
-    /* TODO(seleneh) add ATTEST_KEY and their corresponding codes and tests later*/
+    /* Usable as an attestation signing key.  Keys with this purpose must not have any other
+     * purpose. */
+    ATTEST_KEY = 7,
 }
diff --git a/security/keymint/aidl/android/hardware/security/keymint/MacedPublicKey.aidl b/security/keymint/aidl/android/hardware/security/keymint/MacedPublicKey.aidl
new file mode 100644
index 0000000..da85a50
--- /dev/null
+++ b/security/keymint/aidl/android/hardware/security/keymint/MacedPublicKey.aidl
@@ -0,0 +1,57 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.security.keymint;
+
+/**
+ * MacedPublicKey contains a CBOR-encoded public key, MACed by an IRemotelyProvisionedComponent, to
+ * prove that the key pair was generated by that component.
+ */
+@VintfStability
+parcelable MacedPublicKey {
+    /**
+     * key is a COSE_Mac0 structure containing the new public key.  It's MACed by a key available
+     * only to the secure environment, as proof that the public key was generated by that
+     * environment. In CDDL, assuming the contained key is an Ed25519 public key:
+     *
+     *     MacedPublicKey = [                     // COSE_Mac0
+     *         protected: bstr .cbor { 1 : 5},    // Algorithm : HMAC-256
+     *         unprotected: bstr .size 0,
+     *         payload : bstr .cbor PublicKey,
+     *         tag : bstr HMAC-256(K_mac, MAC_structure)
+     *     ]
+     *
+     *     PublicKey = {               // COSE_Key
+     *         1 : 1,                  // Key type : octet key pair
+     *         3 : -8                  // Algorithm : EdDSA
+     *         -1 : 6,                 // Curve : Ed25519
+     *         -2 : bstr               // X coordinate, little-endian
+     *         ? -70000 : nil          // Presence indicates this is a test key.  If set, K_mac is
+     *                                 // all zeros.
+     *     },
+     *
+     *     MAC_structure = [
+     *         context : "MAC0",
+     *         protected : bstr .cbor { 1 : 5 },
+     *         external_aad : bstr .size 0,
+     *         payload : bstr .cbor PublicKey
+     *     ]
+     *
+     * if a non-Ed25519 public key were contained, the contents of the PublicKey map would change a
+     * little; see RFC 8152 for details.
+     */
+    byte[] macedKey;
+}
diff --git a/security/keymint/aidl/android/hardware/security/keymint/ProtectedData.aidl b/security/keymint/aidl/android/hardware/security/keymint/ProtectedData.aidl
new file mode 100644
index 0000000..1ec3bf0
--- /dev/null
+++ b/security/keymint/aidl/android/hardware/security/keymint/ProtectedData.aidl
@@ -0,0 +1,169 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.security.keymint;
+
+/**
+ * ProtectedData contains the encrypted BCC and the ephemeral MAC key used to
+ * authenticate the keysToSign (see keysToSignMac output argument).
+ */
+@VintfStability
+parcelable ProtectedData {
+    /**
+     * ProtectedData is a COSE_Encrypt structure, specified by the following CDDL
+     *
+     *     ProtectedData = [               // COSE_Encrypt
+     *         protected: bstr .cbor {
+     *             1 : 3                   // Algorithm : AES-GCM 256
+     *         },
+     *         unprotected: {
+     *             5 : bstr .size 12       // IV
+     *         },
+     *         ciphertext: bstr,           // AES-GCM-128(K, .cbor ProtectedDataPayload)
+     *         recipients : [
+     *             [                       // COSE_Recipient
+     *                 protected : bstr .cbor {
+     *                     1 : -25         // Algorithm : ECDH-ES + HKDF-256
+     *                 },
+     *                 unprotected : {
+     *                     -1 : {          // COSE_Key
+     *                         1 : 1,      // Key type : Octet Key Pair
+     *                         -1 : 4,     // Curve : X25519
+     *                         -2 : bstr   // Sender X25519 public key
+     *                     }
+     *                     4 : bstr,       // KID : EEK ID
+     *                 },
+     *                 ciphertext : nil
+     *             ]
+     *         ]
+     *     ]
+     *
+     *     K = HKDF-256(ECDH(EEK_pub, Ephemeral_priv), Context)
+     *
+     *     Context = [                     // COSE_KDF_Context
+     *         AlgorithmID : 3             // AES-GCM 256
+     *         PartyUInfo : [
+     *             identity : bstr "client"
+     *             nonce : bstr .size 0,
+     *             other : bstr            // Ephemeral pubkey
+     *         ],
+     *         PartyVInfo : [
+     *             identity : bstr "server",
+     *             nonce : bstr .size 0,
+     *             other : bstr            // EEK pubkey
+     *         ],
+     *         SuppPubInfo : [
+     *             128,                    // Output key length
+     *             protected : bstr .size 0
+     *         ]
+     *     ]
+     *
+     *     ProtectedDataPayload [
+     *         SignedMac,
+     *         Bcc,
+     *     ]
+     *
+     *     SignedMac = [                       // COSE_Sign1
+     *         bstr .cbor {                    // Protected params
+     *             1 : -8,                     // Algorithm : EdDSA
+     *         },
+     *         bstr .size 0,                   // Unprotected params
+     *         bstr .size 32,                  // MAC key
+     *         bstr PureEd25519(DK_priv, .cbor SignedMac_structure)
+     *     ]
+     *
+     *     SignedMac_structure = [
+     *         "Signature1",
+     *         bstr .cbor {                    // Protected params
+     *             1 : -8,                     // Algorithm : EdDSA
+     *         },
+     *         bstr .cbor SignedMacAad
+     *         bstr .size 32                   // MAC key
+     *     ]
+     *
+     *     SignedMacAad = [
+     *         challenge : bstr,
+     *         DeviceInfo
+     *     ]
+     *
+     *     Bcc = [
+     *         PubKey,                        // DK_pub
+     *         + BccEntry,                    // Root -> leaf (KM_pub)
+     *     ]
+     *
+     *     BccPayload = {                     // CWT
+     *         1 : tstr,                      // Issuer
+     *         2 : tstr,                      // Subject
+     *         // See the Open Profile for DICE for details on these fields.
+     *         ? -4670545 : bstr,             // Code Hash
+     *         ? -4670546 : bstr,             // Code Descriptor
+     *         ? -4670547 : bstr,             // Configuration Hash
+     *         ? -4670548 : bstr .cbor {      // Configuration Descriptor
+     *             ? -70002 : tstr,           // Component name
+     *             ? -70003 : int,            // Firmware version
+     *             ? -70004 : null,           // Resettable
+     *         },
+     *         ? -4670549 : bstr,             // Authority Hash
+     *         ? -4670550 : bstr,             // Authority Descriptor
+     *         ? -4670551 : bstr,             // Mode
+     *         -4670552 : bstr .cbor PubKey   // Subject Public Key
+     *         -4670553 : bstr                // Key Usage
+     *     }
+     *
+     *     BccEntry = [                       // COSE_Sign1
+     *         protected: bstr .cbor {
+     *             1 : -8,                    // Algorithm : EdDSA
+     *         },
+     *         unprotected: bstr .size 0,
+     *         payload: bstr .cbor BccPayload,
+     *         // First entry in the chain is signed by DK_pub, the others are each signed by their
+     *         // immediate predecessor.  See RFC 8032 for signature representation.
+     *         signature: bstr .cbor PureEd25519(SigningKey, bstr .cbor BccEntryInput)
+     *     ]
+     *
+     *     PubKey = {                         // COSE_Key
+     *         1 : 1,                         // Key type : octet key pair
+     *         3 : -8,                        // Algorithm : EdDSA
+     *         4 : 2,                         // Ops: Verify
+     *         -1 : 6,                        // Curve : Ed25519
+     *         -2 : bstr                      // X coordinate, little-endian
+     *     }
+     *
+     *     BccEntryInput = [
+     *         context: "Signature1",
+     *         protected: bstr .cbor {
+     *             1 : -8,                    // Algorithm : EdDSA
+     *         },
+     *         external_aad: bstr .size 0,
+     *         payload: bstr .cbor BccPayload
+     *     ]
+     *
+     *     DeviceInfo = {
+     *         ? "brand" : tstr,
+     *         ? "manufacturer" : tstr,
+     *         ? "product" : tstr,
+     *         ? "model" : tstr,
+     *         ? "board" : tstr,
+     *         ? "vb_state" : "green" / "yellow" / "orange",
+     *         ? "bootloader_state" : "locked" / "unlocked",
+     *         ? "os_version" : tstr,
+     *         ? "system_patch_level" : uint,        // YYYYMMDD
+     *         ? "boot_patch_level" : uint,          // YYYYMMDD
+     *         ? "vendor_patch_level" : uint,        // YYYYMMDD
+     *     }
+     */
+    byte[] protectedData;
+}
diff --git a/security/keymint/aidl/default/Android.bp b/security/keymint/aidl/default/Android.bp
index b2758ad..e160548 100644
--- a/security/keymint/aidl/default/Android.bp
+++ b/security/keymint/aidl/default/Android.bp
@@ -2,7 +2,11 @@
     name: "android.hardware.security.keymint-service",
     relative_install_path: "hw",
     init_rc: ["android.hardware.security.keymint-service.rc"],
-    vintf_fragments: ["android.hardware.security.keymint-service.xml"],
+    vintf_fragments: [
+        "android.hardware.security.keymint-service.xml",
+        "android.hardware.security.sharedsecret-service.xml",
+        "android.hardware.security.secureclock-service.xml",
+    ],
     vendor: true,
     cflags: [
         "-Wall",
@@ -10,17 +14,45 @@
     ],
     shared_libs: [
         "android.hardware.security.keymint-V1-ndk_platform",
+        "android.hardware.security.sharedsecret-V1-ndk_platform",
+        "android.hardware.security.secureclock-V1-ndk_platform",
         "libbase",
         "libbinder_ndk",
-        "libcppbor",
+        "libcppbor_external",
         "libcrypto",
         "libkeymaster_portable",
         "libkeymint",
         "liblog",
         "libpuresoftkeymasterdevice",
+        "libremote_provisioner",
         "libutils",
     ],
     srcs: [
         "service.cpp",
     ],
 }
+
+cc_library {
+    name: "libremote_provisioner",
+    vendor_available: true,
+    static_libs: [
+        "libkeymint_remote_prov_support",
+    ],
+    shared_libs: [
+        "android.hardware.security.keymint-V1-ndk_platform",
+        "libbinder_ndk",
+        "libcppbor_external",
+        "libcppcose",
+        "libcrypto",
+        "libkeymaster_portable",
+        "libkeymint",
+        "liblog",
+        "libpuresoftkeymasterdevice",
+    ],
+    export_include_dirs: [
+        ".",
+    ],
+    srcs: [
+        "RemotelyProvisionedComponent.cpp",
+    ],
+}
diff --git a/security/keymint/aidl/default/RemotelyProvisionedComponent.cpp b/security/keymint/aidl/default/RemotelyProvisionedComponent.cpp
new file mode 100644
index 0000000..f2651fb
--- /dev/null
+++ b/security/keymint/aidl/default/RemotelyProvisionedComponent.cpp
@@ -0,0 +1,430 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "RemotelyProvisionedComponent.h"
+
+#include <assert.h>
+#include <variant>
+
+#include <cppbor.h>
+#include <cppbor_parse.h>
+
+#include <KeyMintUtils.h>
+#include <cppcose/cppcose.h>
+#include <keymaster/keymaster_configuration.h>
+#include <remote_prov/remote_prov_utils.h>
+
+#include <openssl/bn.h>
+#include <openssl/ec.h>
+#include <openssl/rand.h>
+#include <openssl/x509.h>
+
+namespace aidl::android::hardware::security::keymint {
+
+using ::std::string;
+using ::std::tuple;
+using ::std::unique_ptr;
+using ::std::variant;
+using ::std::vector;
+using bytevec = ::std::vector<uint8_t>;
+
+using namespace cppcose;
+using namespace keymaster;
+
+namespace {
+
+constexpr auto STATUS_FAILED = RemotelyProvisionedComponent::STATUS_FAILED;
+constexpr auto STATUS_INVALID_EEK = RemotelyProvisionedComponent::STATUS_INVALID_EEK;
+constexpr auto STATUS_INVALID_MAC = RemotelyProvisionedComponent::STATUS_INVALID_MAC;
+constexpr uint32_t kAffinePointLength = 32;
+struct AStatusDeleter {
+    void operator()(AStatus* p) { AStatus_delete(p); }
+};
+
+// TODO(swillden): Remove the dependency on AStatus stuff.  The COSE lib should use something like
+// StatusOr, but it shouldn't depend on AStatus.
+class Status {
+  public:
+    Status() {}
+    Status(int32_t errCode, const std::string& errMsg)
+        : status_(AStatus_fromServiceSpecificErrorWithMessage(errCode, errMsg.c_str())) {}
+    explicit Status(const std::string& errMsg)
+        : status_(AStatus_fromServiceSpecificErrorWithMessage(STATUS_FAILED, errMsg.c_str())) {}
+    Status(AStatus* status) : status_(status) {}
+    Status(Status&&) = default;
+    Status(const Status&) = delete;
+
+    operator ::ndk::ScopedAStatus() && { return ndk::ScopedAStatus(status_.release()); }
+
+    bool isOk() { return !status_; }
+
+    // Don't call getMessage() unless isOk() returns false;
+    const char* getMessage() const { return AStatus_getMessage(status_.get()); }
+
+  private:
+    std::unique_ptr<AStatus, AStatusDeleter> status_;
+};
+
+template <typename T>
+class StatusOr {
+  public:
+    StatusOr(AStatus* status) : status_(status) {}
+    StatusOr(Status status) : status_(std::move(status)) {}
+    StatusOr(T val) : value_(std::move(val)) {}
+
+    bool isOk() { return status_.isOk(); }
+
+    T* operator->() & {
+        assert(isOk());
+        return &value_.value();
+    }
+    T& operator*() & {
+        assert(isOk());
+        return value_.value();
+    }
+    T&& operator*() && {
+        assert(isOk());
+        return std::move(value_).value();
+    }
+
+    const char* getMessage() const {
+        assert(!isOk());
+        return status_.getMessage();
+    }
+
+    Status moveError() {
+        assert(!isOk());
+        return std::move(status_);
+    }
+
+    T moveValue() { return std::move(value_).value(); }
+
+  private:
+    Status status_;
+    std::optional<T> value_;
+};
+
+StatusOr<std::pair<bytevec /* EEK pub */, bytevec /* EEK ID */>> validateAndExtractEekPubAndId(
+        bool testMode, const bytevec& endpointEncryptionCertChain) {
+    auto [item, newPos, errMsg] = cppbor::parse(endpointEncryptionCertChain);
+
+    if (!item || !item->asArray()) {
+        return Status("Error parsing EEK chain" + errMsg);
+    }
+
+    const cppbor::Array* certArr = item->asArray();
+    bytevec lastPubKey;
+    for (int i = 0; i < certArr->size(); ++i) {
+        auto cosePubKey = verifyAndParseCoseSign1(testMode, certArr->get(i)->asArray(),
+                                                  std::move(lastPubKey), bytevec{} /* AAD */);
+        if (!cosePubKey) {
+            return Status(STATUS_INVALID_EEK,
+                          "Failed to validate EEK chain: " + cosePubKey.moveMessage());
+        }
+        lastPubKey = *std::move(cosePubKey);
+    }
+
+    auto eek = CoseKey::parseX25519(lastPubKey, true /* requireKid */);
+    if (!eek) return Status(STATUS_INVALID_EEK, "Failed to get EEK: " + eek.moveMessage());
+
+    return std::make_pair(eek->getBstrValue(CoseKey::PUBKEY_X).value(),
+                          eek->getBstrValue(CoseKey::KEY_ID).value());
+}
+
+StatusOr<bytevec /* pubkeys */> validateAndExtractPubkeys(bool testMode,
+                                                          const vector<MacedPublicKey>& keysToSign,
+                                                          const bytevec& macKey) {
+    auto pubKeysToMac = cppbor::Array();
+    for (auto& keyToSign : keysToSign) {
+        auto [macedKeyItem, _, coseMacErrMsg] = cppbor::parse(keyToSign.macedKey);
+        if (!macedKeyItem || !macedKeyItem->asArray() ||
+            macedKeyItem->asArray()->size() != kCoseMac0EntryCount) {
+            return Status("Invalid COSE_Mac0 structure");
+        }
+
+        auto protectedParms = macedKeyItem->asArray()->get(kCoseMac0ProtectedParams)->asBstr();
+        auto unprotectedParms = macedKeyItem->asArray()->get(kCoseMac0UnprotectedParams)->asBstr();
+        auto payload = macedKeyItem->asArray()->get(kCoseMac0Payload)->asBstr();
+        auto tag = macedKeyItem->asArray()->get(kCoseMac0Tag)->asBstr();
+        if (!protectedParms || !unprotectedParms || !payload || !tag) {
+            return Status("Invalid COSE_Mac0 contents");
+        }
+
+        auto [protectedMap, __, errMsg] = cppbor::parse(protectedParms);
+        if (!protectedMap || !protectedMap->asMap()) {
+            return Status("Invalid Mac0 protected: " + errMsg);
+        }
+        auto& algo = protectedMap->asMap()->get(ALGORITHM);
+        if (!algo || !algo->asInt() || algo->asInt()->value() != HMAC_256) {
+            return Status("Unsupported Mac0 algorithm");
+        }
+
+        auto pubKey = CoseKey::parse(payload->value(), EC2, ES256, P256);
+        if (!pubKey) return Status(pubKey.moveMessage());
+
+        bool testKey = static_cast<bool>(pubKey->getMap().get(CoseKey::TEST_KEY));
+        if (testMode && !testKey) {
+            return Status(BnRemotelyProvisionedComponent::STATUS_PRODUCTION_KEY_IN_TEST_REQUEST,
+                          "Production key in test request");
+        } else if (!testMode && testKey) {
+            return Status(BnRemotelyProvisionedComponent::STATUS_TEST_KEY_IN_PRODUCTION_REQUEST,
+                          "Test key in production request");
+        }
+
+        auto macTag = generateCoseMac0Mac(macKey, {} /* external_aad */, payload->value());
+        if (!macTag) return Status(STATUS_INVALID_MAC, macTag.moveMessage());
+        if (macTag->size() != tag->value().size() ||
+            CRYPTO_memcmp(macTag->data(), tag->value().data(), macTag->size()) != 0) {
+            return Status(STATUS_INVALID_MAC, "MAC tag mismatch");
+        }
+
+        pubKeysToMac.add(pubKey->moveMap());
+    }
+
+    return pubKeysToMac.encode();
+}
+
+StatusOr<std::pair<bytevec, bytevec>> buildCosePublicKeyFromKmCert(
+        const keymaster_blob_t* km_cert) {
+    if (km_cert == nullptr) {
+        return Status(STATUS_FAILED, "km_cert is a nullptr");
+    }
+    const uint8_t* temp = km_cert->data;
+    X509* cert = d2i_X509(NULL, &temp, km_cert->data_length);
+    if (cert == nullptr) {
+        return Status(STATUS_FAILED, "d2i_X509 returned null when attempting to get the cert.");
+    }
+    EVP_PKEY* pubKey = X509_get_pubkey(cert);
+    if (pubKey == nullptr) {
+        return Status(STATUS_FAILED, "Boringssl failed to get the public key from the cert");
+    }
+    EC_KEY* ecKey = EVP_PKEY_get0_EC_KEY(pubKey);
+    if (ecKey == nullptr) {
+        return Status(STATUS_FAILED,
+                      "The key in the certificate returned from GenerateKey is not "
+                      "an EC key.");
+    }
+    const EC_POINT* jacobian_coords = EC_KEY_get0_public_key(ecKey);
+    BIGNUM x;
+    BIGNUM y;
+    BN_CTX* ctx = BN_CTX_new();
+    if (ctx == nullptr) {
+        return Status(STATUS_FAILED, "Memory allocation failure for BN_CTX");
+    }
+    if (!EC_POINT_get_affine_coordinates_GFp(EC_KEY_get0_group(ecKey), jacobian_coords, &x, &y,
+                                             ctx)) {
+        return Status(STATUS_FAILED, "Failed to get affine coordinates");
+    }
+    bytevec x_bytestring(kAffinePointLength);
+    bytevec y_bytestring(kAffinePointLength);
+    if (BN_bn2binpad(&x, x_bytestring.data(), kAffinePointLength) != kAffinePointLength) {
+        return Status(STATUS_FAILED, "Wrote incorrect number of bytes for x coordinate");
+    }
+    if (BN_bn2binpad(&y, y_bytestring.data(), kAffinePointLength) != kAffinePointLength) {
+        return Status(STATUS_FAILED, "Wrote incorrect number of bytes for y coordinate");
+    }
+    BN_CTX_free(ctx);
+    return std::make_pair(x_bytestring, y_bytestring);
+}
+
+cppbor::Array buildCertReqRecipients(const bytevec& pubkey, const bytevec& kid) {
+    return cppbor::Array()                   // Array of recipients
+            .add(cppbor::Array()             // Recipient
+                         .add(cppbor::Map()  // Protected
+                                      .add(ALGORITHM, ECDH_ES_HKDF_256)
+                                      .canonicalize()
+                                      .encode())
+                         .add(cppbor::Map()  // Unprotected
+                                      .add(COSE_KEY, cppbor::Map()
+                                                             .add(CoseKey::KEY_TYPE, OCTET_KEY_PAIR)
+                                                             .add(CoseKey::CURVE, cppcose::X25519)
+                                                             .add(CoseKey::PUBKEY_X, pubkey)
+                                                             .canonicalize())
+                                      .add(KEY_ID, kid)
+                                      .canonicalize())
+                         .add(cppbor::Null()));  // No ciphertext
+}
+
+static keymaster_key_param_t kKeyMintEcdsaP256Params[] = {
+        Authorization(TAG_PURPOSE, KM_PURPOSE_SIGN), Authorization(TAG_ALGORITHM, KM_ALGORITHM_EC),
+        Authorization(TAG_KEY_SIZE, 256), Authorization(TAG_DIGEST, KM_DIGEST_SHA_2_256),
+        Authorization(TAG_EC_CURVE, KM_EC_CURVE_P_256), Authorization(TAG_NO_AUTH_REQUIRED),
+        // The certificate generated by KM will be discarded, these values don't matter.
+        Authorization(TAG_CERTIFICATE_NOT_BEFORE, 0), Authorization(TAG_CERTIFICATE_NOT_AFTER, 0)};
+
+}  // namespace
+
+RemotelyProvisionedComponent::RemotelyProvisionedComponent(
+        std::shared_ptr<keymint::AndroidKeyMintDevice> keymint) {
+    std::tie(devicePrivKey_, bcc_) = generateBcc();
+    impl_ = keymint->getKeymasterImpl();
+}
+
+RemotelyProvisionedComponent::~RemotelyProvisionedComponent() {}
+
+ScopedAStatus RemotelyProvisionedComponent::generateEcdsaP256KeyPair(bool testMode,
+                                                                     MacedPublicKey* macedPublicKey,
+                                                                     bytevec* privateKeyHandle) {
+    // TODO(jbires): The following should move from ->GenerateKey to ->GenerateRKPKey and everything
+    //              after the GenerateKey call should basically be moved into that new function call
+    //              as well once the issue with libcppbor in system/keymaster is sorted out
+    GenerateKeyRequest request(impl_->message_version());
+    request.key_description.Reinitialize(kKeyMintEcdsaP256Params,
+                                         array_length(kKeyMintEcdsaP256Params));
+    GenerateKeyResponse response(impl_->message_version());
+    impl_->GenerateKey(request, &response);
+    if (response.error != KM_ERROR_OK) {
+        return km_utils::kmError2ScopedAStatus(response.error);
+    }
+
+    if (response.certificate_chain.entry_count != 1) {
+        // Error: Need the single non-signed certificate with the public key in it.
+        return Status(STATUS_FAILED,
+                      "Expected to receive a single certificate from GenerateKey. Instead got: " +
+                              std::to_string(response.certificate_chain.entry_count));
+    }
+    auto affineCoords = buildCosePublicKeyFromKmCert(response.certificate_chain.begin());
+    if (!affineCoords.isOk()) return affineCoords.moveError();
+    cppbor::Map cosePublicKeyMap = cppbor::Map()
+                                           .add(CoseKey::KEY_TYPE, EC2)
+                                           .add(CoseKey::ALGORITHM, ES256)
+                                           .add(CoseKey::CURVE, cppcose::P256)
+                                           .add(CoseKey::PUBKEY_X, affineCoords->first)
+                                           .add(CoseKey::PUBKEY_Y, affineCoords->second);
+    if (testMode) {
+        cosePublicKeyMap.add(CoseKey::TEST_KEY, cppbor::Null());
+    }
+
+    bytevec cosePublicKey = cosePublicKeyMap.canonicalize().encode();
+
+    auto macedKey = constructCoseMac0(testMode ? remote_prov::kTestMacKey : macKey_,
+                                      {} /* externalAad */, cosePublicKey);
+    if (!macedKey) return Status(macedKey.moveMessage());
+
+    macedPublicKey->macedKey = macedKey->encode();
+    *privateKeyHandle = km_utils::kmBlob2vector(response.key_blob);
+    return ScopedAStatus::ok();
+}
+
+ScopedAStatus RemotelyProvisionedComponent::generateCertificateRequest(
+        bool testMode, const vector<MacedPublicKey>& keysToSign,
+        const bytevec& endpointEncCertChain, const bytevec& challenge, bytevec* keysToSignMac,
+        ProtectedData* protectedData) {
+    auto pubKeysToSign = validateAndExtractPubkeys(testMode, keysToSign,
+                                                   testMode ? remote_prov::kTestMacKey : macKey_);
+    if (!pubKeysToSign.isOk()) return pubKeysToSign.moveError();
+
+    bytevec ephemeralMacKey = remote_prov::randomBytes(SHA256_DIGEST_LENGTH);
+
+    auto pubKeysToSignMac = generateCoseMac0Mac(ephemeralMacKey, bytevec{}, *pubKeysToSign);
+    if (!pubKeysToSignMac) return Status(pubKeysToSignMac.moveMessage());
+    *keysToSignMac = *std::move(pubKeysToSignMac);
+
+    bytevec devicePrivKey;
+    cppbor::Array bcc;
+    if (testMode) {
+        std::tie(devicePrivKey, bcc) = generateBcc();
+    } else {
+        devicePrivKey = devicePrivKey_;
+        bcc = bcc_.clone();
+    }
+
+    auto signedMac = constructCoseSign1(devicePrivKey /* Signing key */,  //
+                                        ephemeralMacKey /* Payload */,
+                                        cppbor::Array() /* AAD */
+                                                .add(challenge)
+                                                .add(createDeviceInfo())
+                                                .encode());
+    if (!signedMac) return Status(signedMac.moveMessage());
+
+    bytevec ephemeralPrivKey(X25519_PRIVATE_KEY_LEN);
+    bytevec ephemeralPubKey(X25519_PUBLIC_VALUE_LEN);
+    X25519_keypair(ephemeralPubKey.data(), ephemeralPrivKey.data());
+
+    auto eek = validateAndExtractEekPubAndId(testMode, endpointEncCertChain);
+    if (!eek.isOk()) return eek.moveError();
+
+    auto sessionKey = x25519_HKDF_DeriveKey(ephemeralPubKey, ephemeralPrivKey, eek->first,
+                                            true /* senderIsA */);
+    if (!sessionKey) return Status(sessionKey.moveMessage());
+
+    auto coseEncrypted =
+            constructCoseEncrypt(*sessionKey, remote_prov::randomBytes(kAesGcmNonceLength),
+                                 cppbor::Array()  // payload
+                                         .add(signedMac.moveValue())
+                                         .add(std::move(bcc))
+                                         .encode(),
+                                 {},  // aad
+                                 buildCertReqRecipients(ephemeralPubKey, eek->second));
+
+    if (!coseEncrypted) return Status(coseEncrypted.moveMessage());
+    protectedData->protectedData = coseEncrypted->encode();
+
+    return ScopedAStatus::ok();
+}
+
+bytevec RemotelyProvisionedComponent::deriveBytesFromHbk(const string& context,
+                                                         size_t numBytes) const {
+    bytevec fakeHbk(32, 0);
+    bytevec result(numBytes);
+
+    // TODO(swillden): Figure out if HKDF can fail.  It doesn't seem like it should be able to,
+    // but the function does return an error code.
+    HKDF(result.data(), numBytes,               //
+         EVP_sha256(),                          //
+         fakeHbk.data(), fakeHbk.size(),        //
+         nullptr /* salt */, 0 /* salt len */,  //
+         reinterpret_cast<const uint8_t*>(context.data()), context.size());
+
+    return result;
+}
+
+bytevec RemotelyProvisionedComponent::createDeviceInfo() const {
+    return cppbor::Map().encode();
+}
+
+std::pair<bytevec /* privKey */, cppbor::Array /* BCC */>
+RemotelyProvisionedComponent::generateBcc() {
+    bytevec privKey(ED25519_PRIVATE_KEY_LEN);
+    bytevec pubKey(ED25519_PUBLIC_KEY_LEN);
+
+    ED25519_keypair(pubKey.data(), privKey.data());
+
+    auto coseKey = cppbor::Map()
+                           .add(CoseKey::KEY_TYPE, OCTET_KEY_PAIR)
+                           .add(CoseKey::ALGORITHM, EDDSA)
+                           .add(CoseKey::CURVE, ED25519)
+                           .add(CoseKey::KEY_OPS, VERIFY)
+                           .add(CoseKey::PUBKEY_X, pubKey)
+                           .canonicalize()
+                           .encode();
+    auto sign1Payload = cppbor::Map()
+                                .add(1 /* Issuer */, "Issuer")
+                                .add(2 /* Subject */, "Subject")
+                                .add(-4670552 /* Subject Pub Key */, coseKey)
+                                .add(-4670553 /* Key Usage */,
+                                     std::vector<uint8_t>(0x05) /* Big endian order */)
+                                .canonicalize()
+                                .encode();
+    auto coseSign1 = constructCoseSign1(privKey,       /* signing key */
+                                        cppbor::Map(), /* extra protected */
+                                        sign1Payload, {} /* AAD */);
+    assert(coseSign1);
+
+    return {privKey, cppbor::Array().add(coseKey).add(coseSign1.moveValue())};
+}
+
+}  // namespace aidl::android::hardware::security::keymint
diff --git a/security/keymint/aidl/default/RemotelyProvisionedComponent.h b/security/keymint/aidl/default/RemotelyProvisionedComponent.h
new file mode 100644
index 0000000..e8d2343
--- /dev/null
+++ b/security/keymint/aidl/default/RemotelyProvisionedComponent.h
@@ -0,0 +1,57 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include <AndroidKeyMintDevice.h>
+#include <aidl/android/hardware/security/keymint/BnRemotelyProvisionedComponent.h>
+#include <aidl/android/hardware/security/keymint/SecurityLevel.h>
+#include <cppbor.h>
+#include <keymaster/UniquePtr.h>
+#include <keymaster/android_keymaster.h>
+
+namespace aidl::android::hardware::security::keymint {
+
+using ::ndk::ScopedAStatus;
+
+class RemotelyProvisionedComponent : public BnRemotelyProvisionedComponent {
+  public:
+    explicit RemotelyProvisionedComponent(std::shared_ptr<keymint::AndroidKeyMintDevice> keymint);
+    virtual ~RemotelyProvisionedComponent();
+
+    ScopedAStatus generateEcdsaP256KeyPair(bool testMode, MacedPublicKey* macedPublicKey,
+                                           std::vector<uint8_t>* privateKeyHandle) override;
+
+    ScopedAStatus generateCertificateRequest(bool testMode,
+                                             const std::vector<MacedPublicKey>& keysToSign,
+                                             const std::vector<uint8_t>& endpointEncCertChain,
+                                             const std::vector<uint8_t>& challenge,
+                                             std::vector<uint8_t>* keysToSignMac,
+                                             ProtectedData* protectedData) override;
+
+  private:
+    // TODO(swillden): Move these into an appropriate Context class.
+    std::vector<uint8_t> deriveBytesFromHbk(const std::string& context, size_t numBytes) const;
+    std::vector<uint8_t> createDeviceInfo() const;
+    std::pair<std::vector<uint8_t>, cppbor::Array> generateBcc();
+
+    std::vector<uint8_t> macKey_ = deriveBytesFromHbk("Key to MAC public keys", 32);
+    std::vector<uint8_t> devicePrivKey_;
+    cppbor::Array bcc_;
+    std::shared_ptr<::keymaster::AndroidKeymaster> impl_;
+};
+
+}  // namespace aidl::android::hardware::security::keymint
diff --git a/security/keymint/aidl/default/android.hardware.security.keymint-service.xml b/security/keymint/aidl/default/android.hardware.security.keymint-service.xml
index 73d15a8..4aa05ef 100644
--- a/security/keymint/aidl/default/android.hardware.security.keymint-service.xml
+++ b/security/keymint/aidl/default/android.hardware.security.keymint-service.xml
@@ -3,4 +3,8 @@
         <name>android.hardware.security.keymint</name>
         <fqname>IKeyMintDevice/default</fqname>
     </hal>
+    <hal format="aidl">
+        <name>android.hardware.security.keymint</name>
+        <fqname>IRemotelyProvisionedComponent/default</fqname>
+    </hal>
 </manifest>
diff --git a/security/keymint/aidl/default/android.hardware.security.secureclock-service.xml b/security/keymint/aidl/default/android.hardware.security.secureclock-service.xml
new file mode 100644
index 0000000..c0ff775
--- /dev/null
+++ b/security/keymint/aidl/default/android.hardware.security.secureclock-service.xml
@@ -0,0 +1,6 @@
+<manifest version="1.0" type="device">
+    <hal format="aidl">
+        <name>android.hardware.security.secureclock</name>
+        <fqname>ISecureClock/default</fqname>
+    </hal>
+</manifest>
diff --git a/security/keymint/aidl/default/android.hardware.security.sharedsecret-service.xml b/security/keymint/aidl/default/android.hardware.security.sharedsecret-service.xml
new file mode 100644
index 0000000..d37981f
--- /dev/null
+++ b/security/keymint/aidl/default/android.hardware.security.sharedsecret-service.xml
@@ -0,0 +1,6 @@
+<manifest version="1.0" type="device">
+    <hal format="aidl">
+        <name>android.hardware.security.sharedsecret</name>
+        <fqname>ISharedSecret/default</fqname>
+    </hal>
+</manifest>
diff --git a/security/keymint/aidl/default/service.cpp b/security/keymint/aidl/default/service.cpp
index a710535..bcebbaf 100644
--- a/security/keymint/aidl/default/service.cpp
+++ b/security/keymint/aidl/default/service.cpp
@@ -21,25 +21,42 @@
 #include <android/binder_process.h>
 
 #include <AndroidKeyMintDevice.h>
+#include <AndroidSecureClock.h>
+#include <AndroidSharedSecret.h>
 #include <keymaster/soft_keymaster_logger.h>
 
+#include "RemotelyProvisionedComponent.h"
+
 using aidl::android::hardware::security::keymint::AndroidKeyMintDevice;
+using aidl::android::hardware::security::keymint::RemotelyProvisionedComponent;
 using aidl::android::hardware::security::keymint::SecurityLevel;
+using aidl::android::hardware::security::secureclock::AndroidSecureClock;
+using aidl::android::hardware::security::sharedsecret::AndroidSharedSecret;
+
+template <typename T, class... Args>
+std::shared_ptr<T> addService(Args&&... args) {
+    std::shared_ptr<T> ser = ndk::SharedRefBase::make<T>(std::forward<Args>(args)...);
+    auto instanceName = std::string(T::descriptor) + "/default";
+    LOG(INFO) << "adding keymint service instance: " << instanceName;
+    binder_status_t status =
+            AServiceManager_addService(ser->asBinder().get(), instanceName.c_str());
+    CHECK(status == STATUS_OK);
+    return ser;
+}
 
 int main() {
     // Zero threads seems like a useless pool, but below we'll join this thread to it, increasing
     // the pool size to 1.
     ABinderProcess_setThreadPoolMaxThreadCount(0);
+    // Add Keymint Service
     std::shared_ptr<AndroidKeyMintDevice> keyMint =
-            ndk::SharedRefBase::make<AndroidKeyMintDevice>(SecurityLevel::SOFTWARE);
-
-    keymaster::SoftKeymasterLogger logger;
-    const auto instanceName = std::string(AndroidKeyMintDevice::descriptor) + "/default";
-    LOG(INFO) << "instance: " << instanceName;
-    binder_status_t status =
-            AServiceManager_addService(keyMint->asBinder().get(), instanceName.c_str());
-    CHECK(status == STATUS_OK);
-
+            addService<AndroidKeyMintDevice>(SecurityLevel::SOFTWARE);
+    // Add Secure Clock Service
+    addService<AndroidSecureClock>(keyMint);
+    // Add Shared Secret Service
+    addService<AndroidSharedSecret>(keyMint);
+    // Add Remotely Provisioned Component Service
+    addService<RemotelyProvisionedComponent>(keyMint);
     ABinderProcess_joinThreadPool();
     return EXIT_FAILURE;  // should not reach
 }
diff --git a/security/keymint/aidl/vts/functional/Android.bp b/security/keymint/aidl/vts/functional/Android.bp
index f4ba9e7..24fe616 100644
--- a/security/keymint/aidl/vts/functional/Android.bp
+++ b/security/keymint/aidl/vts/functional/Android.bp
@@ -21,6 +21,7 @@
         "use_libaidlvintf_gtest_helper_static",
     ],
     srcs: [
+        "AttestKeyTest.cpp",
         "KeyMintTest.cpp",
     ],
     shared_libs: [
@@ -62,6 +63,36 @@
     static_libs: [
         "android.hardware.security.keymint-V1-ndk_platform",
         "android.hardware.security.secureclock-V1-ndk_platform",
-        "libcppbor",
+        "libcppbor_external",
+    ],
+}
+
+cc_test {
+    name: "VtsHalRemotelyProvisionedComponentTargetTest",
+    defaults: [
+        "VtsHalTargetTestDefaults",
+        "use_libaidlvintf_gtest_helper_static",
+    ],
+    srcs: [
+        "VtsRemotelyProvisionedComponentTests.cpp",
+    ],
+    shared_libs: [
+        "libbinder_ndk",
+        "libcppbor_external",
+        "libcrypto",
+        "libkeymaster_portable",
+        "libpuresoftkeymasterdevice",
+    ],
+    static_libs: [
+        "android.hardware.security.keymint-V1-ndk_platform",
+        "libcppcose",
+        "libgmock_ndk",
+        "libremote_provisioner",
+        "libkeymint",
+        "libkeymint_remote_prov_support",
+    ],
+    test_suites: [
+        "general-tests",
+        "vts",
     ],
 }
diff --git a/security/keymint/aidl/vts/functional/AttestKeyTest.cpp b/security/keymint/aidl/vts/functional/AttestKeyTest.cpp
new file mode 100644
index 0000000..7e7a466
--- /dev/null
+++ b/security/keymint/aidl/vts/functional/AttestKeyTest.cpp
@@ -0,0 +1,235 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "keymint_1_attest_key_test"
+#include <cutils/log.h>
+
+#include <keymint_support/key_param_output.h>
+#include <keymint_support/openssl_utils.h>
+
+#include "KeyMintAidlTestBase.h"
+
+namespace aidl::android::hardware::security::keymint::test {
+
+namespace {
+
+vector<uint8_t> make_name_from_str(const string& name) {
+    X509_NAME_Ptr x509_name(X509_NAME_new());
+    EXPECT_TRUE(x509_name.get() != nullptr);
+    if (!x509_name) return {};
+
+    EXPECT_EQ(1, X509_NAME_add_entry_by_txt(x509_name.get(),  //
+                                            "CN",             //
+                                            MBSTRING_ASC,
+                                            reinterpret_cast<const uint8_t*>(name.c_str()),
+                                            -1,  // len
+                                            -1,  // loc
+                                            0 /* set */));
+
+    int len = i2d_X509_NAME(x509_name.get(), nullptr /* only return length */);
+    EXPECT_GT(len, 0);
+
+    vector<uint8_t> retval(len);
+    uint8_t* p = retval.data();
+    i2d_X509_NAME(x509_name.get(), &p);
+
+    return retval;
+}
+
+bool IsSelfSigned(const vector<Certificate>& chain) {
+    if (chain.size() != 1) return false;
+    return ChainSignaturesAreValid(chain);
+}
+
+}  // namespace
+
+using AttestKeyTest = KeyMintAidlTestBase;
+
+TEST_P(AttestKeyTest, AllRsaSizes) {
+    for (auto size : ValidKeySizes(Algorithm::RSA)) {
+        /*
+         * Create attestaton key.
+         */
+        AttestationKey attest_key;
+        vector<KeyCharacteristics> attest_key_characteristics;
+        vector<Certificate> attest_key_cert_chain;
+        ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
+                                                     .RsaSigningKey(size, 65537)
+                                                     .AttestKey()
+                                                     .SetDefaultValidity(),
+                                             {} /* attestation signing key */, &attest_key.keyBlob,
+                                             &attest_key_characteristics, &attest_key_cert_chain));
+
+        EXPECT_EQ(attest_key_cert_chain.size(), 1);
+        EXPECT_TRUE(IsSelfSigned(attest_key_cert_chain)) << "Failed on size " << size;
+
+        /*
+         * Use attestation key to sign RSA key
+         */
+        attest_key.issuerSubjectName = make_name_from_str("Android Keystore Key");
+        vector<uint8_t> attested_key_blob;
+        vector<KeyCharacteristics> attested_key_characteristics;
+        vector<Certificate> attested_key_cert_chain;
+        EXPECT_EQ(ErrorCode::OK,
+                  GenerateKey(AuthorizationSetBuilder()
+                                      .RsaSigningKey(2048, 65537)
+                                      .Authorization(TAG_NO_AUTH_REQUIRED)
+                                      .AttestationChallenge("foo")
+                                      .AttestationApplicationId("bar")
+                                      .SetDefaultValidity(),
+                              attest_key, &attested_key_blob, &attested_key_characteristics,
+                              &attested_key_cert_chain));
+
+        CheckedDeleteKey(&attested_key_blob);
+
+        AuthorizationSet hw_enforced = HwEnforcedAuthorizations(attested_key_characteristics);
+        AuthorizationSet sw_enforced = SwEnforcedAuthorizations(attested_key_characteristics);
+        EXPECT_TRUE(verify_attestation_record("foo", "bar", sw_enforced, hw_enforced, SecLevel(),
+                                              attested_key_cert_chain[0].encodedCertificate));
+
+        // Attestation by itself is not valid (last entry is not self-signed).
+        EXPECT_FALSE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        // Appending the attest_key chain to the attested_key_chain should yield a valid chain.
+        if (attest_key_cert_chain.size() > 0) {
+            attested_key_cert_chain.push_back(attest_key_cert_chain[0]);
+        }
+        EXPECT_TRUE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        /*
+         * Use attestation key to sign EC key
+         */
+        EXPECT_EQ(ErrorCode::OK,
+                  GenerateKey(AuthorizationSetBuilder()
+                                      .EcdsaSigningKey(EcCurve::P_256)
+                                      .Authorization(TAG_NO_AUTH_REQUIRED)
+                                      .AttestationChallenge("foo")
+                                      .AttestationApplicationId("bar")
+                                      .SetDefaultValidity(),
+                              attest_key, &attested_key_blob, &attested_key_characteristics,
+                              &attested_key_cert_chain));
+
+        CheckedDeleteKey(&attested_key_blob);
+        CheckedDeleteKey(&attest_key.keyBlob);
+
+        hw_enforced = HwEnforcedAuthorizations(attested_key_characteristics);
+        sw_enforced = SwEnforcedAuthorizations(attested_key_characteristics);
+        EXPECT_TRUE(verify_attestation_record("foo", "bar", sw_enforced, hw_enforced, SecLevel(),
+                                              attested_key_cert_chain[0].encodedCertificate));
+
+        // Attestation by itself is not valid (last entry is not self-signed).
+        EXPECT_FALSE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        // Appending the attest_key chain to the attested_key_chain should yield a valid chain.
+        if (attest_key_cert_chain.size() > 0) {
+            attested_key_cert_chain.push_back(attest_key_cert_chain[0]);
+        }
+        EXPECT_TRUE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        // Bail early if anything failed.
+        if (HasFailure()) return;
+    }
+}
+
+TEST_P(AttestKeyTest, AllEcCurves) {
+    for (auto curve : ValidCurves()) {
+        /*
+         * Create attestaton key.
+         */
+        AttestationKey attest_key;
+        vector<KeyCharacteristics> attest_key_characteristics;
+        vector<Certificate> attest_key_cert_chain;
+        ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
+                                                     .EcdsaSigningKey(curve)
+                                                     .AttestKey()
+                                                     .SetDefaultValidity(),
+                                             {} /* attestation siging key */, &attest_key.keyBlob,
+                                             &attest_key_characteristics, &attest_key_cert_chain));
+
+        EXPECT_EQ(attest_key_cert_chain.size(), 1);
+        EXPECT_TRUE(IsSelfSigned(attest_key_cert_chain)) << "Failed on curve " << curve;
+
+        /*
+         * Use attestation key to sign RSA key
+         */
+        attest_key.issuerSubjectName = make_name_from_str("Android Keystore Key");
+        vector<uint8_t> attested_key_blob;
+        vector<KeyCharacteristics> attested_key_characteristics;
+        vector<Certificate> attested_key_cert_chain;
+        EXPECT_EQ(ErrorCode::OK,
+                  GenerateKey(AuthorizationSetBuilder()
+                                      .RsaSigningKey(2048, 65537)
+                                      .Authorization(TAG_NO_AUTH_REQUIRED)
+                                      .AttestationChallenge("foo")
+                                      .AttestationApplicationId("bar")
+                                      .SetDefaultValidity(),
+                              attest_key, &attested_key_blob, &attested_key_characteristics,
+                              &attested_key_cert_chain));
+
+        CheckedDeleteKey(&attested_key_blob);
+
+        AuthorizationSet hw_enforced = HwEnforcedAuthorizations(attested_key_characteristics);
+        AuthorizationSet sw_enforced = SwEnforcedAuthorizations(attested_key_characteristics);
+        EXPECT_TRUE(verify_attestation_record("foo", "bar", sw_enforced, hw_enforced, SecLevel(),
+                                              attested_key_cert_chain[0].encodedCertificate));
+
+        // Attestation by itself is not valid (last entry is not self-signed).
+        EXPECT_FALSE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        // Appending the attest_key chain to the attested_key_chain should yield a valid chain.
+        if (attest_key_cert_chain.size() > 0) {
+            attested_key_cert_chain.push_back(attest_key_cert_chain[0]);
+        }
+        EXPECT_TRUE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        /*
+         * Use attestation key to sign EC key
+         */
+        EXPECT_EQ(ErrorCode::OK,
+                  GenerateKey(AuthorizationSetBuilder()
+                                      .EcdsaSigningKey(EcCurve::P_256)
+                                      .Authorization(TAG_NO_AUTH_REQUIRED)
+                                      .AttestationChallenge("foo")
+                                      .AttestationApplicationId("bar")
+                                      .SetDefaultValidity(),
+                              attest_key, &attested_key_blob, &attested_key_characteristics,
+                              &attested_key_cert_chain));
+
+        CheckedDeleteKey(&attested_key_blob);
+        CheckedDeleteKey(&attest_key.keyBlob);
+
+        hw_enforced = HwEnforcedAuthorizations(attested_key_characteristics);
+        sw_enforced = SwEnforcedAuthorizations(attested_key_characteristics);
+        EXPECT_TRUE(verify_attestation_record("foo", "bar", sw_enforced, hw_enforced, SecLevel(),
+                                              attested_key_cert_chain[0].encodedCertificate));
+
+        // Attestation by itself is not valid (last entry is not self-signed).
+        EXPECT_FALSE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        // Appending the attest_key chain to the attested_key_chain should yield a valid chain.
+        if (attest_key_cert_chain.size() > 0) {
+            attested_key_cert_chain.push_back(attest_key_cert_chain[0]);
+        }
+        EXPECT_TRUE(ChainSignaturesAreValid(attested_key_cert_chain));
+
+        // Bail early if anything failed.
+        if (HasFailure()) return;
+    }
+}
+
+INSTANTIATE_KEYMINT_AIDL_TEST(AttestKeyTest);
+
+}  // namespace aidl::android::hardware::security::keymint::test
diff --git a/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.cpp b/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.cpp
index 6555157..d61a081 100644
--- a/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.cpp
+++ b/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.cpp
@@ -22,15 +22,23 @@
 
 #include <android-base/logging.h>
 #include <android/binder_manager.h>
+#include <cutils/properties.h>
+#include <openssl/mem.h>
 
+#include <keymint_support/attestation_record.h>
 #include <keymint_support/key_param_output.h>
 #include <keymint_support/keymint_utils.h>
+#include <keymint_support/openssl_utils.h>
 
 namespace aidl::android::hardware::security::keymint {
 
 using namespace std::literals::chrono_literals;
 using std::endl;
 using std::optional;
+using std::unique_ptr;
+using ::testing::AssertionFailure;
+using ::testing::AssertionResult;
+using ::testing::AssertionSuccess;
 
 ::std::ostream& operator<<(::std::ostream& os, const AuthorizationSet& set) {
     if (set.size() == 0)
@@ -45,7 +53,7 @@
 namespace test {
 
 namespace {
-
+typedef KeyMintAidlTestBase::KeyData KeyData;
 // Predicate for testing basic characteristics validity in generation or import.
 bool KeyCharacteristicsBasicallyValid(SecurityLevel secLevel,
                                       const vector<KeyCharacteristics>& key_characteristics) {
@@ -73,8 +81,67 @@
     return true;
 }
 
+// Extract attestation record from cert. Returned object is still part of cert; don't free it
+// separately.
+ASN1_OCTET_STRING* get_attestation_record(X509* certificate) {
+    ASN1_OBJECT_Ptr oid(OBJ_txt2obj(kAttestionRecordOid, 1 /* dotted string format */));
+    EXPECT_TRUE(!!oid.get());
+    if (!oid.get()) return nullptr;
+
+    int location = X509_get_ext_by_OBJ(certificate, oid.get(), -1 /* search from beginning */);
+    EXPECT_NE(-1, location) << "Attestation extension not found in certificate";
+    if (location == -1) return nullptr;
+
+    X509_EXTENSION* attest_rec_ext = X509_get_ext(certificate, location);
+    EXPECT_TRUE(!!attest_rec_ext)
+            << "Found attestation extension but couldn't retrieve it?  Probably a BoringSSL bug.";
+    if (!attest_rec_ext) return nullptr;
+
+    ASN1_OCTET_STRING* attest_rec = X509_EXTENSION_get_data(attest_rec_ext);
+    EXPECT_TRUE(!!attest_rec) << "Attestation extension contained no data";
+    return attest_rec;
+}
+
+bool avb_verification_enabled() {
+    char value[PROPERTY_VALUE_MAX];
+    return property_get("ro.boot.vbmeta.device_state", value, "") != 0;
+}
+
+char nibble2hex[16] = {'0', '1', '2', '3', '4', '5', '6', '7',
+                       '8', '9', 'a', 'b', 'c', 'd', 'e', 'f'};
+
+// Attestations don't contain everything in key authorization lists, so we need to filter the key
+// lists to produce the lists that we expect to match the attestations.
+auto kTagsToFilter = {
+        Tag::BLOB_USAGE_REQUIREMENTS,  //
+        Tag::CREATION_DATETIME,        //
+        Tag::EC_CURVE,
+        Tag::HARDWARE_TYPE,
+        Tag::INCLUDE_UNIQUE_ID,
+};
+
+AuthorizationSet filtered_tags(const AuthorizationSet& set) {
+    AuthorizationSet filtered;
+    std::remove_copy_if(
+            set.begin(), set.end(), std::back_inserter(filtered), [](const auto& entry) -> bool {
+                return std::find(kTagsToFilter.begin(), kTagsToFilter.end(), entry.tag) !=
+                       kTagsToFilter.end();
+            });
+    return filtered;
+}
+
+string x509NameToStr(X509_NAME* name) {
+    char* s = X509_NAME_oneline(name, nullptr, 0);
+    string retval(s);
+    OPENSSL_free(s);
+    return retval;
+}
+
 }  // namespace
 
+bool KeyMintAidlTestBase::arm_deleteAllKeys = false;
+bool KeyMintAidlTestBase::dump_Attestations = false;
+
 ErrorCode KeyMintAidlTestBase::GetReturnErrorCode(const Status& result) {
     if (result.isOk()) return ErrorCode::OK;
 
@@ -110,48 +177,48 @@
 }
 
 ErrorCode KeyMintAidlTestBase::GenerateKey(const AuthorizationSet& key_desc,
+                                           const optional<AttestationKey>& attest_key,
                                            vector<uint8_t>* key_blob,
-                                           vector<KeyCharacteristics>* key_characteristics) {
+                                           vector<KeyCharacteristics>* key_characteristics,
+                                           vector<Certificate>* cert_chain) {
     EXPECT_NE(key_blob, nullptr) << "Key blob pointer must not be null.  Test bug";
     EXPECT_NE(key_characteristics, nullptr)
             << "Previous characteristics not deleted before generating key.  Test bug.";
 
-    // Aidl does not clear these output parameters if the function returns
-    // error.  This is different from hal where output parameter is always
-    // cleared due to hal returning void.  So now we need to do our own clearing
-    // of the output variables prior to calling keyMint aidl libraries.
-    key_blob->clear();
-    key_characteristics->clear();
-    cert_chain_.clear();
-
     KeyCreationResult creationResult;
-    Status result = keymint_->generateKey(key_desc.vector_data(), &creationResult);
-
+    Status result = keymint_->generateKey(key_desc.vector_data(), attest_key, &creationResult);
     if (result.isOk()) {
         EXPECT_PRED2(KeyCharacteristicsBasicallyValid, SecLevel(),
                      creationResult.keyCharacteristics);
         EXPECT_GT(creationResult.keyBlob.size(), 0);
         *key_blob = std::move(creationResult.keyBlob);
         *key_characteristics = std::move(creationResult.keyCharacteristics);
-        cert_chain_ = std::move(creationResult.certificateChain);
+        *cert_chain = std::move(creationResult.certificateChain);
 
         auto algorithm = key_desc.GetTagValue(TAG_ALGORITHM);
         EXPECT_TRUE(algorithm);
         if (algorithm &&
             (algorithm.value() == Algorithm::RSA || algorithm.value() == Algorithm::EC)) {
-            EXPECT_GE(cert_chain_.size(), 1);
-            if (key_desc.Contains(TAG_ATTESTATION_CHALLENGE)) EXPECT_GT(cert_chain_.size(), 1);
+            EXPECT_GE(cert_chain->size(), 1);
+            if (key_desc.Contains(TAG_ATTESTATION_CHALLENGE)) {
+                if (attest_key) {
+                    EXPECT_EQ(cert_chain->size(), 1);
+                } else {
+                    EXPECT_GT(cert_chain->size(), 1);
+                }
+            }
         } else {
             // For symmetric keys there should be no certificates.
-            EXPECT_EQ(cert_chain_.size(), 0);
+            EXPECT_EQ(cert_chain->size(), 0);
         }
     }
 
     return GetReturnErrorCode(result);
 }
 
-ErrorCode KeyMintAidlTestBase::GenerateKey(const AuthorizationSet& key_desc) {
-    return GenerateKey(key_desc, &key_blob_, &key_characteristics_);
+ErrorCode KeyMintAidlTestBase::GenerateKey(const AuthorizationSet& key_desc,
+                                           const optional<AttestationKey>& attest_key) {
+    return GenerateKey(key_desc, attest_key, &key_blob_, &key_characteristics_, &cert_chain_);
 }
 
 ErrorCode KeyMintAidlTestBase::ImportKey(const AuthorizationSet& key_desc, KeyFormat format,
@@ -166,7 +233,7 @@
     KeyCreationResult creationResult;
     result = keymint_->importKey(key_desc.vector_data(), format,
                                  vector<uint8_t>(key_material.begin(), key_material.end()),
-                                 &creationResult);
+                                 {} /* attestationSigningKeyBlob */, &creationResult);
 
     if (result.isOk()) {
         EXPECT_PRED2(KeyCharacteristicsBasicallyValid, SecLevel(),
@@ -461,6 +528,34 @@
     }
 }
 
+auto KeyMintAidlTestBase::ProcessMessage(const vector<uint8_t>& key_blob, KeyPurpose operation,
+                                         const string& message, const AuthorizationSet& in_params)
+        -> std::tuple<ErrorCode, string, AuthorizationSet /* out_params */> {
+    AuthorizationSet begin_out_params;
+    ErrorCode result = Begin(operation, key_blob, in_params, &begin_out_params);
+    AuthorizationSet out_params(std::move(begin_out_params));
+    if (result != ErrorCode::OK) {
+        return {result, {}, out_params};
+    }
+
+    string output;
+    int32_t consumed = 0;
+    AuthorizationSet update_params;
+    AuthorizationSet update_out_params;
+    result = Update(update_params, message, &update_out_params, &output, &consumed);
+    out_params.push_back(update_out_params);
+    if (result != ErrorCode::OK) {
+        return {result, output, out_params};
+    }
+
+    string unused;
+    AuthorizationSet finish_params;
+    AuthorizationSet finish_out_params;
+    result = Finish(finish_params, message.substr(consumed), unused, &finish_out_params, &output);
+    out_params.push_back(finish_out_params);
+    return {result, output, out_params};
+}
+
 string KeyMintAidlTestBase::ProcessMessage(const vector<uint8_t>& key_blob, KeyPurpose operation,
                                            const string& message, const AuthorizationSet& in_params,
                                            AuthorizationSet* out_params) {
@@ -859,6 +954,269 @@
     return authList;
 }
 
+ErrorCode KeyMintAidlTestBase::UseAesKey(const vector<uint8_t>& aesKeyBlob) {
+    auto [result, ciphertext, out_params] = ProcessMessage(
+            aesKeyBlob, KeyPurpose::ENCRYPT, "1234567890123456",
+            AuthorizationSetBuilder().BlockMode(BlockMode::ECB).Padding(PaddingMode::NONE));
+    return result;
+}
+
+ErrorCode KeyMintAidlTestBase::UseHmacKey(const vector<uint8_t>& hmacKeyBlob) {
+    auto [result, mac, out_params] = ProcessMessage(
+            hmacKeyBlob, KeyPurpose::SIGN, "1234567890123456",
+            AuthorizationSetBuilder().Authorization(TAG_MAC_LENGTH, 128).Digest(Digest::SHA_2_256));
+    return result;
+}
+
+ErrorCode KeyMintAidlTestBase::UseRsaKey(const vector<uint8_t>& rsaKeyBlob) {
+    std::string message(2048 / 8, 'a');
+    auto [result, signature, out_params] = ProcessMessage(
+            rsaKeyBlob, KeyPurpose::SIGN, message,
+            AuthorizationSetBuilder().Digest(Digest::NONE).Padding(PaddingMode::NONE));
+    return result;
+}
+
+ErrorCode KeyMintAidlTestBase::UseEcdsaKey(const vector<uint8_t>& ecdsaKeyBlob) {
+    auto [result, signature, out_params] =
+            ProcessMessage(ecdsaKeyBlob, KeyPurpose::SIGN, "a",
+                           AuthorizationSetBuilder().Digest(Digest::SHA_2_256));
+    return result;
+}
+
+bool verify_attestation_record(const string& challenge,                //
+                               const string& app_id,                   //
+                               AuthorizationSet expected_sw_enforced,  //
+                               AuthorizationSet expected_hw_enforced,  //
+                               SecurityLevel security_level,
+                               const vector<uint8_t>& attestation_cert) {
+    X509_Ptr cert(parse_cert_blob(attestation_cert));
+    EXPECT_TRUE(!!cert.get());
+    if (!cert.get()) return false;
+
+    ASN1_OCTET_STRING* attest_rec = get_attestation_record(cert.get());
+    EXPECT_TRUE(!!attest_rec);
+    if (!attest_rec) return false;
+
+    AuthorizationSet att_sw_enforced;
+    AuthorizationSet att_hw_enforced;
+    uint32_t att_attestation_version;
+    uint32_t att_keymaster_version;
+    SecurityLevel att_attestation_security_level;
+    SecurityLevel att_keymaster_security_level;
+    vector<uint8_t> att_challenge;
+    vector<uint8_t> att_unique_id;
+    vector<uint8_t> att_app_id;
+
+    auto error = parse_attestation_record(attest_rec->data,                 //
+                                          attest_rec->length,               //
+                                          &att_attestation_version,         //
+                                          &att_attestation_security_level,  //
+                                          &att_keymaster_version,           //
+                                          &att_keymaster_security_level,    //
+                                          &att_challenge,                   //
+                                          &att_sw_enforced,                 //
+                                          &att_hw_enforced,                 //
+                                          &att_unique_id);
+    EXPECT_EQ(ErrorCode::OK, error);
+    if (error != ErrorCode::OK) return false;
+
+    EXPECT_GE(att_attestation_version, 3U);
+
+    expected_sw_enforced.push_back(TAG_ATTESTATION_APPLICATION_ID,
+                                   vector<uint8_t>(app_id.begin(), app_id.end()));
+
+    EXPECT_GE(att_keymaster_version, 4U);
+    EXPECT_EQ(security_level, att_keymaster_security_level);
+    EXPECT_EQ(security_level, att_attestation_security_level);
+
+    EXPECT_EQ(challenge.length(), att_challenge.size());
+    EXPECT_EQ(0, memcmp(challenge.data(), att_challenge.data(), challenge.length()));
+
+    char property_value[PROPERTY_VALUE_MAX] = {};
+    // TODO(b/136282179): When running under VTS-on-GSI the TEE-backed
+    // keymaster implementation will report YYYYMM dates instead of YYYYMMDD
+    // for the BOOT_PATCH_LEVEL.
+    if (avb_verification_enabled()) {
+        for (int i = 0; i < att_hw_enforced.size(); i++) {
+            if (att_hw_enforced[i].tag == TAG_BOOT_PATCHLEVEL ||
+                att_hw_enforced[i].tag == TAG_VENDOR_PATCHLEVEL) {
+                std::string date =
+                        std::to_string(att_hw_enforced[i].value.get<KeyParameterValue::dateTime>());
+                // strptime seems to require delimiters, but the tag value will
+                // be YYYYMMDD
+                date.insert(6, "-");
+                date.insert(4, "-");
+                EXPECT_EQ(date.size(), 10);
+                struct tm time;
+                strptime(date.c_str(), "%Y-%m-%d", &time);
+
+                // Day of the month (0-31)
+                EXPECT_GE(time.tm_mday, 0);
+                EXPECT_LT(time.tm_mday, 32);
+                // Months since Jan (0-11)
+                EXPECT_GE(time.tm_mon, 0);
+                EXPECT_LT(time.tm_mon, 12);
+                // Years since 1900
+                EXPECT_GT(time.tm_year, 110);
+                EXPECT_LT(time.tm_year, 200);
+            }
+        }
+    }
+
+    // Check to make sure boolean values are properly encoded. Presence of a boolean tag
+    // indicates true. A provided boolean tag that can be pulled back out of the certificate
+    // indicates correct encoding. No need to check if it's in both lists, since the
+    // AuthorizationSet compare below will handle mismatches of tags.
+    if (security_level == SecurityLevel::SOFTWARE) {
+        EXPECT_TRUE(expected_sw_enforced.Contains(TAG_NO_AUTH_REQUIRED));
+    } else {
+        EXPECT_TRUE(expected_hw_enforced.Contains(TAG_NO_AUTH_REQUIRED));
+    }
+
+    // Alternatively this checks the opposite - a false boolean tag (one that isn't provided in
+    // the authorization list during key generation) isn't being attested to in the certificate.
+    EXPECT_FALSE(expected_sw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
+    EXPECT_FALSE(att_sw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
+    EXPECT_FALSE(expected_hw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
+    EXPECT_FALSE(att_hw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
+
+    if (att_hw_enforced.Contains(TAG_ALGORITHM, Algorithm::EC)) {
+        // For ECDSA keys, either an EC_CURVE or a KEY_SIZE can be specified, but one must be.
+        EXPECT_TRUE(att_hw_enforced.Contains(TAG_EC_CURVE) ||
+                    att_hw_enforced.Contains(TAG_KEY_SIZE));
+    }
+
+    // Test root of trust elements
+    vector<uint8_t> verified_boot_key;
+    VerifiedBoot verified_boot_state;
+    bool device_locked;
+    vector<uint8_t> verified_boot_hash;
+    error = parse_root_of_trust(attest_rec->data, attest_rec->length, &verified_boot_key,
+                                &verified_boot_state, &device_locked, &verified_boot_hash);
+    EXPECT_EQ(ErrorCode::OK, error);
+
+    if (avb_verification_enabled()) {
+        EXPECT_NE(property_get("ro.boot.vbmeta.digest", property_value, ""), 0);
+        string prop_string(property_value);
+        EXPECT_EQ(prop_string.size(), 64);
+        EXPECT_EQ(prop_string, bin2hex(verified_boot_hash));
+
+        EXPECT_NE(property_get("ro.boot.vbmeta.device_state", property_value, ""), 0);
+        if (!strcmp(property_value, "unlocked")) {
+            EXPECT_FALSE(device_locked);
+        } else {
+            EXPECT_TRUE(device_locked);
+        }
+
+        // Check that the device is locked if not debuggable, e.g., user build
+        // images in CTS. For VTS, debuggable images are used to allow adb root
+        // and the device is unlocked.
+        if (!property_get_bool("ro.debuggable", false)) {
+            EXPECT_TRUE(device_locked);
+        } else {
+            EXPECT_FALSE(device_locked);
+        }
+    }
+
+    // Verified boot key should be all 0's if the boot state is not verified or self signed
+    std::string empty_boot_key(32, '\0');
+    std::string verified_boot_key_str((const char*)verified_boot_key.data(),
+                                      verified_boot_key.size());
+    EXPECT_NE(property_get("ro.boot.verifiedbootstate", property_value, ""), 0);
+    if (!strcmp(property_value, "green")) {
+        EXPECT_EQ(verified_boot_state, VerifiedBoot::VERIFIED);
+        EXPECT_NE(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
+                            verified_boot_key.size()));
+    } else if (!strcmp(property_value, "yellow")) {
+        EXPECT_EQ(verified_boot_state, VerifiedBoot::SELF_SIGNED);
+        EXPECT_NE(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
+                            verified_boot_key.size()));
+    } else if (!strcmp(property_value, "orange")) {
+        EXPECT_EQ(verified_boot_state, VerifiedBoot::UNVERIFIED);
+        EXPECT_EQ(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
+                            verified_boot_key.size()));
+    } else if (!strcmp(property_value, "red")) {
+        EXPECT_EQ(verified_boot_state, VerifiedBoot::FAILED);
+    } else {
+        EXPECT_EQ(verified_boot_state, VerifiedBoot::UNVERIFIED);
+        EXPECT_NE(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
+                            verified_boot_key.size()));
+    }
+
+    att_sw_enforced.Sort();
+    expected_sw_enforced.Sort();
+    auto a = filtered_tags(expected_sw_enforced);
+    auto b = filtered_tags(att_sw_enforced);
+    EXPECT_EQ(a, b);
+
+    att_hw_enforced.Sort();
+    expected_hw_enforced.Sort();
+    EXPECT_EQ(filtered_tags(expected_hw_enforced), filtered_tags(att_hw_enforced));
+
+    return true;
+}
+
+string bin2hex(const vector<uint8_t>& data) {
+    string retval;
+    retval.reserve(data.size() * 2 + 1);
+    for (uint8_t byte : data) {
+        retval.push_back(nibble2hex[0x0F & (byte >> 4)]);
+        retval.push_back(nibble2hex[0x0F & byte]);
+    }
+    return retval;
+}
+
+AssertionResult ChainSignaturesAreValid(const vector<Certificate>& chain) {
+    std::stringstream cert_data;
+
+    for (size_t i = 0; i < chain.size(); ++i) {
+        cert_data << bin2hex(chain[i].encodedCertificate) << std::endl;
+
+        X509_Ptr key_cert(parse_cert_blob(chain[i].encodedCertificate));
+        X509_Ptr signing_cert;
+        if (i < chain.size() - 1) {
+            signing_cert = parse_cert_blob(chain[i + 1].encodedCertificate);
+        } else {
+            signing_cert = parse_cert_blob(chain[i].encodedCertificate);
+        }
+        if (!key_cert.get() || !signing_cert.get()) return AssertionFailure() << cert_data.str();
+
+        EVP_PKEY_Ptr signing_pubkey(X509_get_pubkey(signing_cert.get()));
+        if (!signing_pubkey.get()) return AssertionFailure() << cert_data.str();
+
+        if (!X509_verify(key_cert.get(), signing_pubkey.get())) {
+            return AssertionFailure()
+                   << "Verification of certificate " << i << " failed "
+                   << "OpenSSL error string: " << ERR_error_string(ERR_get_error(), NULL) << '\n'
+                   << cert_data.str();
+        }
+
+        string cert_issuer = x509NameToStr(X509_get_issuer_name(key_cert.get()));
+        string signer_subj = x509NameToStr(X509_get_subject_name(signing_cert.get()));
+        if (cert_issuer != signer_subj) {
+            return AssertionFailure() << "Cert " << i << " has wrong issuer.\n" << cert_data.str();
+        }
+
+        if (i == 0) {
+            string cert_sub = x509NameToStr(X509_get_subject_name(key_cert.get()));
+            if ("/CN=Android Keystore Key" != cert_sub) {
+                return AssertionFailure()
+                       << "Leaf cert has wrong subject, should be CN=Android Keystore Key, was "
+                       << cert_sub << '\n'
+                       << cert_data.str();
+            }
+        }
+    }
+
+    if (KeyMintAidlTestBase::dump_Attestations) std::cout << cert_data.str();
+    return AssertionSuccess();
+}
+
+X509_Ptr parse_cert_blob(const vector<uint8_t>& blob) {
+    const uint8_t* p = blob.data();
+    return X509_Ptr(d2i_X509(nullptr /* allocate new */, &p, blob.size()));
+}
+
 }  // namespace test
 
 }  // namespace aidl::android::hardware::security::keymint
diff --git a/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.h b/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.h
index 780971d..452d2b6 100644
--- a/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.h
+++ b/security/keymint/aidl/vts/functional/KeyMintAidlTestBase.h
@@ -21,20 +21,27 @@
 #include <binder/IServiceManager.h>
 #include <binder/ProcessState.h>
 #include <gtest/gtest.h>
+#include <openssl/x509.h>
 
 #include <aidl/android/hardware/security/keymint/ErrorCode.h>
 #include <aidl/android/hardware/security/keymint/IKeyMintDevice.h>
 
 #include <keymint_support/authorization_set.h>
+#include <keymint_support/openssl_utils.h>
 
 namespace aidl::android::hardware::security::keymint {
 
 ::std::ostream& operator<<(::std::ostream& os, const AuthorizationSet& set);
 
+inline bool operator==(const keymint::AuthorizationSet& a, const keymint::AuthorizationSet& b) {
+    return a.size() == b.size() && std::equal(a.begin(), a.end(), b.begin());
+}
+
 namespace test {
 
 using ::android::sp;
 using Status = ::ndk::ScopedAStatus;
+using ::std::optional;
 using ::std::shared_ptr;
 using ::std::string;
 using ::std::vector;
@@ -43,6 +50,14 @@
 
 class KeyMintAidlTestBase : public ::testing::TestWithParam<string> {
   public:
+    struct KeyData {
+        vector<uint8_t> blob;
+        vector<KeyCharacteristics> characteristics;
+    };
+
+    static bool arm_deleteAllKeys;
+    static bool dump_Attestations;
+
     void SetUp() override;
     void TearDown() override {
         if (key_blob_.size()) {
@@ -57,10 +72,18 @@
     uint32_t os_patch_level() { return os_patch_level_; }
 
     ErrorCode GetReturnErrorCode(const Status& result);
-    ErrorCode GenerateKey(const AuthorizationSet& key_desc, vector<uint8_t>* key_blob,
-                          vector<KeyCharacteristics>* key_characteristics);
 
-    ErrorCode GenerateKey(const AuthorizationSet& key_desc);
+    ErrorCode GenerateKey(const AuthorizationSet& key_desc, vector<uint8_t>* key_blob,
+                          vector<KeyCharacteristics>* key_characteristics) {
+        return GenerateKey(key_desc, std::nullopt /* attest_key */, key_blob, key_characteristics,
+                           &cert_chain_);
+    }
+    ErrorCode GenerateKey(const AuthorizationSet& key_desc,
+                          const optional<AttestationKey>& attest_key, vector<uint8_t>* key_blob,
+                          vector<KeyCharacteristics>* key_characteristics,
+                          vector<Certificate>* cert_chain);
+    ErrorCode GenerateKey(const AuthorizationSet& key_desc,
+                          const optional<AttestationKey>& attest_key = std::nullopt);
 
     ErrorCode ImportKey(const AuthorizationSet& key_desc, KeyFormat format,
                         const string& key_material, vector<uint8_t>* key_blob,
@@ -106,7 +129,9 @@
     string ProcessMessage(const vector<uint8_t>& key_blob, KeyPurpose operation,
                           const string& message, const AuthorizationSet& in_params,
                           AuthorizationSet* out_params);
-
+    std::tuple<ErrorCode, std::string /* processedMessage */, AuthorizationSet /* out_params */>
+    ProcessMessage(const vector<uint8_t>& key_blob, KeyPurpose operation,
+                   const std::string& message, const AuthorizationSet& in_params);
     string SignMessage(const vector<uint8_t>& key_blob, const string& message,
                        const AuthorizationSet& params);
     string SignMessage(const string& message, const AuthorizationSet& params);
@@ -149,6 +174,56 @@
 
     std::pair<ErrorCode, vector<uint8_t>> UpgradeKey(const vector<uint8_t>& key_blob);
 
+    template <typename TagType>
+    std::tuple<KeyData /* aesKey */, KeyData /* hmacKey */, KeyData /* rsaKey */,
+               KeyData /* ecdsaKey */>
+    CreateTestKeys(TagType tagToTest, ErrorCode expectedReturn) {
+        /* AES */
+        KeyData aesKeyData;
+        ErrorCode errorCode = GenerateKey(AuthorizationSetBuilder()
+                                                  .AesEncryptionKey(128)
+                                                  .Authorization(tagToTest)
+                                                  .BlockMode(BlockMode::ECB)
+                                                  .Padding(PaddingMode::NONE)
+                                                  .Authorization(TAG_NO_AUTH_REQUIRED),
+                                          &aesKeyData.blob, &aesKeyData.characteristics);
+        EXPECT_EQ(expectedReturn, errorCode);
+
+        /* HMAC */
+        KeyData hmacKeyData;
+        errorCode = GenerateKey(AuthorizationSetBuilder()
+                                        .HmacKey(128)
+                                        .Authorization(tagToTest)
+                                        .Digest(Digest::SHA_2_256)
+                                        .Authorization(TAG_MIN_MAC_LENGTH, 128)
+                                        .Authorization(TAG_NO_AUTH_REQUIRED),
+                                &hmacKeyData.blob, &hmacKeyData.characteristics);
+        EXPECT_EQ(expectedReturn, errorCode);
+
+        /* RSA */
+        KeyData rsaKeyData;
+        errorCode = GenerateKey(AuthorizationSetBuilder()
+                                        .RsaSigningKey(2048, 65537)
+                                        .Authorization(tagToTest)
+                                        .Digest(Digest::NONE)
+                                        .Padding(PaddingMode::NONE)
+                                        .Authorization(TAG_NO_AUTH_REQUIRED)
+                                        .SetDefaultValidity(),
+                                &rsaKeyData.blob, &rsaKeyData.characteristics);
+        EXPECT_EQ(expectedReturn, errorCode);
+
+        /* ECDSA */
+        KeyData ecdsaKeyData;
+        errorCode = GenerateKey(AuthorizationSetBuilder()
+                                        .EcdsaSigningKey(256)
+                                        .Authorization(tagToTest)
+                                        .Digest(Digest::SHA_2_256)
+                                        .Authorization(TAG_NO_AUTH_REQUIRED)
+                                        .SetDefaultValidity(),
+                                &ecdsaKeyData.blob, &ecdsaKeyData.characteristics);
+        EXPECT_EQ(expectedReturn, errorCode);
+        return {aesKeyData, hmacKeyData, rsaKeyData, ecdsaKeyData};
+    }
     bool IsSecure() const { return securityLevel_ != SecurityLevel::SOFTWARE; }
     SecurityLevel SecLevel() const { return securityLevel_; }
 
@@ -182,6 +257,10 @@
             const vector<KeyCharacteristics>& key_characteristics);
     AuthorizationSet SwEnforcedAuthorizations(
             const vector<KeyCharacteristics>& key_characteristics);
+    ErrorCode UseAesKey(const vector<uint8_t>& aesKeyBlob);
+    ErrorCode UseHmacKey(const vector<uint8_t>& hmacKeyBlob);
+    ErrorCode UseRsaKey(const vector<uint8_t>& rsaKeyBlob);
+    ErrorCode UseEcdsaKey(const vector<uint8_t>& ecdsaKeyBlob);
 
   private:
     std::shared_ptr<IKeyMintDevice> keymint_;
@@ -194,6 +273,16 @@
     long challenge_;
 };
 
+bool verify_attestation_record(const string& challenge,                //
+                               const string& app_id,                   //
+                               AuthorizationSet expected_sw_enforced,  //
+                               AuthorizationSet expected_hw_enforced,  //
+                               SecurityLevel security_level,
+                               const vector<uint8_t>& attestation_cert);
+string bin2hex(const vector<uint8_t>& data);
+X509_Ptr parse_cert_blob(const vector<uint8_t>& blob);
+::testing::AssertionResult ChainSignaturesAreValid(const vector<Certificate>& chain);
+
 #define INSTANTIATE_KEYMINT_AIDL_TEST(name)                                          \
     INSTANTIATE_TEST_SUITE_P(PerInstance, name,                                      \
                              testing::ValuesIn(KeyMintAidlTestBase::build_params()), \
diff --git a/security/keymint/aidl/vts/functional/KeyMintTest.cpp b/security/keymint/aidl/vts/functional/KeyMintTest.cpp
index c849bad..71aae90 100644
--- a/security/keymint/aidl/vts/functional/KeyMintTest.cpp
+++ b/security/keymint/aidl/vts/functional/KeyMintTest.cpp
@@ -14,7 +14,7 @@
  * limitations under the License.
  */
 
-#define LOG_TAG "keymint_5_test"
+#define LOG_TAG "keymint_1_test"
 #include <cutils/log.h>
 
 #include <signal.h>
@@ -23,34 +23,21 @@
 #include <openssl/ec.h>
 #include <openssl/evp.h>
 #include <openssl/mem.h>
-#include <openssl/x509.h>
 #include <openssl/x509v3.h>
 
 #include <cutils/properties.h>
 
 #include <aidl/android/hardware/security/keymint/KeyFormat.h>
 
-#include <keymint_support/attestation_record.h>
 #include <keymint_support/key_param_output.h>
 #include <keymint_support/openssl_utils.h>
 
 #include "KeyMintAidlTestBase.h"
 
-static bool arm_deleteAllKeys = false;
-static bool dump_Attestations = false;
-
 using aidl::android::hardware::security::keymint::AuthorizationSet;
 using aidl::android::hardware::security::keymint::KeyCharacteristics;
 using aidl::android::hardware::security::keymint::KeyFormat;
 
-namespace aidl::android::hardware::security::keymint {
-
-bool operator==(const keymint::AuthorizationSet& a, const keymint::AuthorizationSet& b) {
-    return a.size() == b.size() && std::equal(a.begin(), a.end(), b.begin());
-}
-
-}  // namespace aidl::android::hardware::security::keymint
-
 namespace std {
 
 using namespace aidl::android::hardware::security::keymint;
@@ -78,7 +65,8 @@
 namespace {
 
 template <TagType tag_type, Tag tag, typename ValueT>
-bool contains(vector<KeyParameter>& set, TypedTag<tag_type, tag> ttag, ValueT expected_value) {
+bool contains(const vector<KeyParameter>& set, TypedTag<tag_type, tag> ttag,
+              ValueT expected_value) {
     auto it = std::find_if(set.begin(), set.end(), [&](const KeyParameter& param) {
         if (auto p = authorizationValue(ttag, param)) {
             return *p == expected_value;
@@ -89,7 +77,7 @@
 }
 
 template <TagType tag_type, Tag tag>
-bool contains(vector<KeyParameter>& set, TypedTag<tag_type, tag>) {
+bool contains(const vector<KeyParameter>& set, TypedTag<tag_type, tag>) {
     auto it = std::find_if(set.begin(), set.end(),
                            [&](const KeyParameter& param) { return param.tag == tag; });
     return (it != set.end());
@@ -182,281 +170,6 @@
     void operator()(RSA* p) { RSA_free(p); }
 };
 
-char nibble2hex[16] = {'0', '1', '2', '3', '4', '5', '6', '7',
-                       '8', '9', 'a', 'b', 'c', 'd', 'e', 'f'};
-
-string bin2hex(const vector<uint8_t>& data) {
-    string retval;
-    retval.reserve(data.size() * 2 + 1);
-    for (uint8_t byte : data) {
-        retval.push_back(nibble2hex[0x0F & (byte >> 4)]);
-        retval.push_back(nibble2hex[0x0F & byte]);
-    }
-    return retval;
-}
-
-X509* parse_cert_blob(const vector<uint8_t>& blob) {
-    const uint8_t* p = blob.data();
-    return d2i_X509(nullptr, &p, blob.size());
-}
-
-bool verify_chain(const vector<Certificate>& chain) {
-    for (size_t i = 0; i < chain.size(); ++i) {
-        X509_Ptr key_cert(parse_cert_blob(chain[i].encodedCertificate));
-        X509_Ptr signing_cert;
-        if (i < chain.size() - 1) {
-            signing_cert.reset(parse_cert_blob(chain[i + 1].encodedCertificate));
-        } else {
-            signing_cert.reset(parse_cert_blob(chain[i].encodedCertificate));
-        }
-        EXPECT_TRUE(!!key_cert.get() && !!signing_cert.get());
-        if (!key_cert.get() || !signing_cert.get()) return false;
-
-        EVP_PKEY_Ptr signing_pubkey(X509_get_pubkey(signing_cert.get()));
-        EXPECT_TRUE(!!signing_pubkey.get());
-        if (!signing_pubkey.get()) return false;
-
-        EXPECT_EQ(1, X509_verify(key_cert.get(), signing_pubkey.get()))
-                << "Verification of certificate " << i << " failed "
-                << "OpenSSL error string: " << ERR_error_string(ERR_get_error(), NULL);
-
-        char* cert_issuer =  //
-                X509_NAME_oneline(X509_get_issuer_name(key_cert.get()), nullptr, 0);
-        char* signer_subj =
-                X509_NAME_oneline(X509_get_subject_name(signing_cert.get()), nullptr, 0);
-        EXPECT_STREQ(cert_issuer, signer_subj) << "Cert " << i << " has wrong issuer.";
-        if (i == 0) {
-            char* cert_sub = X509_NAME_oneline(X509_get_subject_name(key_cert.get()), nullptr, 0);
-            EXPECT_STREQ("/CN=Android Keystore Key", cert_sub)
-                    << "Cert " << i << " has wrong subject.";
-            OPENSSL_free(cert_sub);
-        }
-
-        OPENSSL_free(cert_issuer);
-        OPENSSL_free(signer_subj);
-
-        if (dump_Attestations) std::cout << bin2hex(chain[i].encodedCertificate) << std::endl;
-    }
-
-    return true;
-}
-
-// Extract attestation record from cert. Returned object is still part of cert; don't free it
-// separately.
-ASN1_OCTET_STRING* get_attestation_record(X509* certificate) {
-    ASN1_OBJECT_Ptr oid(OBJ_txt2obj(kAttestionRecordOid, 1 /* dotted string format */));
-    EXPECT_TRUE(!!oid.get());
-    if (!oid.get()) return nullptr;
-
-    int location = X509_get_ext_by_OBJ(certificate, oid.get(), -1 /* search from beginning */);
-    EXPECT_NE(-1, location) << "Attestation extension not found in certificate";
-    if (location == -1) return nullptr;
-
-    X509_EXTENSION* attest_rec_ext = X509_get_ext(certificate, location);
-    EXPECT_TRUE(!!attest_rec_ext)
-            << "Found attestation extension but couldn't retrieve it?  Probably a BoringSSL bug.";
-    if (!attest_rec_ext) return nullptr;
-
-    ASN1_OCTET_STRING* attest_rec = X509_EXTENSION_get_data(attest_rec_ext);
-    EXPECT_TRUE(!!attest_rec) << "Attestation extension contained no data";
-    return attest_rec;
-}
-
-bool tag_in_list(const KeyParameter& entry) {
-    // Attestations don't contain everything in key authorization lists, so we need to filter
-    // the key lists to produce the lists that we expect to match the attestations.
-    auto tag_list = {
-            Tag::BLOB_USAGE_REQUIREMENTS,  //
-            Tag::CREATION_DATETIME,        //
-            Tag::EC_CURVE,
-            Tag::HARDWARE_TYPE,
-            Tag::INCLUDE_UNIQUE_ID,
-    };
-    return std::find(tag_list.begin(), tag_list.end(), entry.tag) != tag_list.end();
-}
-
-AuthorizationSet filtered_tags(const AuthorizationSet& set) {
-    AuthorizationSet filtered;
-    std::remove_copy_if(set.begin(), set.end(), std::back_inserter(filtered), tag_in_list);
-    return filtered;
-}
-
-bool avb_verification_enabled() {
-    char value[PROPERTY_VALUE_MAX];
-    return property_get("ro.boot.vbmeta.device_state", value, "") != 0;
-}
-
-bool verify_attestation_record(const string& challenge,                //
-                               const string& app_id,                   //
-                               AuthorizationSet expected_sw_enforced,  //
-                               AuthorizationSet expected_hw_enforced,  //
-                               SecurityLevel security_level,
-                               const vector<uint8_t>& attestation_cert) {
-    X509_Ptr cert(parse_cert_blob(attestation_cert));
-    EXPECT_TRUE(!!cert.get());
-    if (!cert.get()) return false;
-
-    ASN1_OCTET_STRING* attest_rec = get_attestation_record(cert.get());
-    EXPECT_TRUE(!!attest_rec);
-    if (!attest_rec) return false;
-
-    AuthorizationSet att_sw_enforced;
-    AuthorizationSet att_hw_enforced;
-    uint32_t att_attestation_version;
-    uint32_t att_keymaster_version;
-    SecurityLevel att_attestation_security_level;
-    SecurityLevel att_keymaster_security_level;
-    vector<uint8_t> att_challenge;
-    vector<uint8_t> att_unique_id;
-    vector<uint8_t> att_app_id;
-
-    auto error = parse_attestation_record(attest_rec->data,                 //
-                                          attest_rec->length,               //
-                                          &att_attestation_version,         //
-                                          &att_attestation_security_level,  //
-                                          &att_keymaster_version,           //
-                                          &att_keymaster_security_level,    //
-                                          &att_challenge,                   //
-                                          &att_sw_enforced,                 //
-                                          &att_hw_enforced,                 //
-                                          &att_unique_id);
-    EXPECT_EQ(ErrorCode::OK, error);
-    if (error != ErrorCode::OK) return false;
-
-    EXPECT_GE(att_attestation_version, 3U);
-
-    expected_sw_enforced.push_back(TAG_ATTESTATION_APPLICATION_ID,
-                                   vector<uint8_t>(app_id.begin(), app_id.end()));
-
-    EXPECT_GE(att_keymaster_version, 4U);
-    EXPECT_EQ(security_level, att_keymaster_security_level);
-    EXPECT_EQ(security_level, att_attestation_security_level);
-
-    EXPECT_EQ(challenge.length(), att_challenge.size());
-    EXPECT_EQ(0, memcmp(challenge.data(), att_challenge.data(), challenge.length()));
-
-    char property_value[PROPERTY_VALUE_MAX] = {};
-    // TODO(b/136282179): When running under VTS-on-GSI the TEE-backed
-    // keymaster implementation will report YYYYMM dates instead of YYYYMMDD
-    // for the BOOT_PATCH_LEVEL.
-    if (avb_verification_enabled()) {
-        for (int i = 0; i < att_hw_enforced.size(); i++) {
-            if (att_hw_enforced[i].tag == TAG_BOOT_PATCHLEVEL ||
-                att_hw_enforced[i].tag == TAG_VENDOR_PATCHLEVEL) {
-                std::string date =
-                        std::to_string(att_hw_enforced[i].value.get<KeyParameterValue::dateTime>());
-                // strptime seems to require delimiters, but the tag value will
-                // be YYYYMMDD
-                date.insert(6, "-");
-                date.insert(4, "-");
-                EXPECT_EQ(date.size(), 10);
-                struct tm time;
-                strptime(date.c_str(), "%Y-%m-%d", &time);
-
-                // Day of the month (0-31)
-                EXPECT_GE(time.tm_mday, 0);
-                EXPECT_LT(time.tm_mday, 32);
-                // Months since Jan (0-11)
-                EXPECT_GE(time.tm_mon, 0);
-                EXPECT_LT(time.tm_mon, 12);
-                // Years since 1900
-                EXPECT_GT(time.tm_year, 110);
-                EXPECT_LT(time.tm_year, 200);
-            }
-        }
-    }
-
-    // Check to make sure boolean values are properly encoded. Presence of a boolean tag indicates
-    // true. A provided boolean tag that can be pulled back out of the certificate indicates correct
-    // encoding. No need to check if it's in both lists, since the AuthorizationSet compare below
-    // will handle mismatches of tags.
-    if (security_level == SecurityLevel::SOFTWARE) {
-        EXPECT_TRUE(expected_sw_enforced.Contains(TAG_NO_AUTH_REQUIRED));
-    } else {
-        EXPECT_TRUE(expected_hw_enforced.Contains(TAG_NO_AUTH_REQUIRED));
-    }
-
-    // Alternatively this checks the opposite - a false boolean tag (one that isn't provided in
-    // the authorization list during key generation) isn't being attested to in the certificate.
-    EXPECT_FALSE(expected_sw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
-    EXPECT_FALSE(att_sw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
-    EXPECT_FALSE(expected_hw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
-    EXPECT_FALSE(att_hw_enforced.Contains(TAG_TRUSTED_USER_PRESENCE_REQUIRED));
-
-    if (att_hw_enforced.Contains(TAG_ALGORITHM, Algorithm::EC)) {
-        // For ECDSA keys, either an EC_CURVE or a KEY_SIZE can be specified, but one must be.
-        EXPECT_TRUE(att_hw_enforced.Contains(TAG_EC_CURVE) ||
-                    att_hw_enforced.Contains(TAG_KEY_SIZE));
-    }
-
-    // Test root of trust elements
-    vector<uint8_t> verified_boot_key;
-    VerifiedBoot verified_boot_state;
-    bool device_locked;
-    vector<uint8_t> verified_boot_hash;
-    error = parse_root_of_trust(attest_rec->data, attest_rec->length, &verified_boot_key,
-                                &verified_boot_state, &device_locked, &verified_boot_hash);
-    EXPECT_EQ(ErrorCode::OK, error);
-
-    if (avb_verification_enabled()) {
-        EXPECT_NE(property_get("ro.boot.vbmeta.digest", property_value, ""), 0);
-        string prop_string(property_value);
-        EXPECT_EQ(prop_string.size(), 64);
-        EXPECT_EQ(prop_string, bin2hex(verified_boot_hash));
-
-        EXPECT_NE(property_get("ro.boot.vbmeta.device_state", property_value, ""), 0);
-        if (!strcmp(property_value, "unlocked")) {
-            EXPECT_FALSE(device_locked);
-        } else {
-            EXPECT_TRUE(device_locked);
-        }
-
-        // Check that the device is locked if not debuggable, e.g., user build
-        // images in CTS. For VTS, debuggable images are used to allow adb root
-        // and the device is unlocked.
-        if (!property_get_bool("ro.debuggable", false)) {
-            EXPECT_TRUE(device_locked);
-        } else {
-            EXPECT_FALSE(device_locked);
-        }
-    }
-
-    // Verified boot key should be all 0's if the boot state is not verified or self signed
-    std::string empty_boot_key(32, '\0');
-    std::string verified_boot_key_str((const char*)verified_boot_key.data(),
-                                      verified_boot_key.size());
-    EXPECT_NE(property_get("ro.boot.verifiedbootstate", property_value, ""), 0);
-    if (!strcmp(property_value, "green")) {
-        EXPECT_EQ(verified_boot_state, VerifiedBoot::VERIFIED);
-        EXPECT_NE(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
-                            verified_boot_key.size()));
-    } else if (!strcmp(property_value, "yellow")) {
-        EXPECT_EQ(verified_boot_state, VerifiedBoot::SELF_SIGNED);
-        EXPECT_NE(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
-                            verified_boot_key.size()));
-    } else if (!strcmp(property_value, "orange")) {
-        EXPECT_EQ(verified_boot_state, VerifiedBoot::UNVERIFIED);
-        EXPECT_EQ(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
-                            verified_boot_key.size()));
-    } else if (!strcmp(property_value, "red")) {
-        EXPECT_EQ(verified_boot_state, VerifiedBoot::FAILED);
-    } else {
-        EXPECT_EQ(verified_boot_state, VerifiedBoot::UNVERIFIED);
-        EXPECT_NE(0, memcmp(verified_boot_key.data(), empty_boot_key.data(),
-                            verified_boot_key.size()));
-    }
-
-    att_sw_enforced.Sort();
-    expected_sw_enforced.Sort();
-    EXPECT_EQ(filtered_tags(expected_sw_enforced), filtered_tags(att_sw_enforced));
-
-    att_hw_enforced.Sort();
-    expected_hw_enforced.Sort();
-    EXPECT_EQ(filtered_tags(expected_hw_enforced), filtered_tags(att_hw_enforced));
-
-    return true;
-}
-
 std::string make_string(const uint8_t* data, size_t length) {
     return std::string(reinterpret_cast<const char*>(data), length);
 }
@@ -544,7 +257,8 @@
         ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                      .RsaSigningKey(key_size, 65537)
                                                      .Digest(Digest::NONE)
-                                                     .Padding(PaddingMode::NONE),
+                                                     .Padding(PaddingMode::NONE)
+                                                     .SetDefaultValidity(),
                                              &key_blob, &key_characteristics));
 
         ASSERT_GT(key_blob.size(), 0U);
@@ -580,7 +294,8 @@
                                                      .Padding(PaddingMode::NONE)
                                                      .AttestationChallenge(challenge)
                                                      .AttestationApplicationId(app_id)
-                                                     .Authorization(TAG_NO_AUTH_REQUIRED),
+                                                     .Authorization(TAG_NO_AUTH_REQUIRED)
+                                                     .SetDefaultValidity(),
                                              &key_blob, &key_characteristics));
 
         ASSERT_GT(key_blob.size(), 0U);
@@ -593,7 +308,7 @@
                 << "Key size " << key_size << "missing";
         EXPECT_TRUE(crypto_params.Contains(TAG_RSA_PUBLIC_EXPONENT, 65537U));
 
-        EXPECT_TRUE(verify_chain(cert_chain_));
+        EXPECT_TRUE(ChainSignaturesAreValid(cert_chain_));
         ASSERT_GT(cert_chain_.size(), 0);
 
         AuthorizationSet hw_enforced = HwEnforcedAuthorizations(key_characteristics);
@@ -620,7 +335,8 @@
                                                      .RsaSigningKey(key_size, 65537)
                                                      .Digest(Digest::NONE)
                                                      .Padding(PaddingMode::NONE)
-                                                     .Authorization(TAG_USAGE_COUNT_LIMIT, 1),
+                                                     .Authorization(TAG_USAGE_COUNT_LIMIT, 1)
+                                                     .SetDefaultValidity(),
                                              &key_blob, &key_characteristics));
 
         ASSERT_GT(key_blob.size(), 0U);
@@ -665,7 +381,8 @@
                                                      .AttestationChallenge(challenge)
                                                      .AttestationApplicationId(app_id)
                                                      .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                     .Authorization(TAG_USAGE_COUNT_LIMIT, 1),
+                                                     .Authorization(TAG_USAGE_COUNT_LIMIT, 1)
+                                                     .SetDefaultValidity(),
                                              &key_blob, &key_characteristics));
 
         ASSERT_GT(key_blob.size(), 0U);
@@ -687,7 +404,7 @@
                 << "key usage count limit " << 1U << " missing";
 
         // Check the usage count limit tag also appears in the attestation.
-        EXPECT_TRUE(verify_chain(cert_chain_));
+        EXPECT_TRUE(ChainSignaturesAreValid(cert_chain_));
         ASSERT_GT(cert_chain_.size(), 0);
 
         AuthorizationSet hw_enforced = HwEnforcedAuthorizations(key_characteristics);
@@ -713,7 +430,8 @@
                   GenerateKey(AuthorizationSetBuilder()
                                       .RsaSigningKey(key_size, 65537)
                                       .Digest(Digest::NONE)
-                                      .Padding(PaddingMode::NONE),
+                                      .Padding(PaddingMode::NONE)
+                                      .SetDefaultValidity(),
                               &key_blob, &key_characteristics));
     }
 }
@@ -729,7 +447,8 @@
               GenerateKey(AuthorizationSetBuilder()
                                   .Authorization(TAG_ALGORITHM, Algorithm::RSA)
                                   .Authorization(TAG_RSA_PUBLIC_EXPONENT, 3U)
-                                  .SigningKey()));
+                                  .SigningKey()
+                                  .SetDefaultValidity()));
 }
 
 /*
@@ -742,10 +461,11 @@
     for (auto key_size : ValidKeySizes(Algorithm::EC)) {
         vector<uint8_t> key_blob;
         vector<KeyCharacteristics> key_characteristics;
-        ASSERT_EQ(ErrorCode::OK,
-                  GenerateKey(
-                          AuthorizationSetBuilder().EcdsaSigningKey(key_size).Digest(Digest::NONE),
-                          &key_blob, &key_characteristics));
+        ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
+                                                     .EcdsaSigningKey(key_size)
+                                                     .Digest(Digest::NONE)
+                                                     .SetDefaultValidity(),
+                                             &key_blob, &key_characteristics));
         ASSERT_GT(key_blob.size(), 0U);
         CheckBaseParams(key_characteristics);
 
@@ -772,7 +492,8 @@
         ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                      .EcdsaSigningKey(key_size)
                                                      .Digest(Digest::NONE)
-                                                     .Authorization(TAG_USAGE_COUNT_LIMIT, 1),
+                                                     .Authorization(TAG_USAGE_COUNT_LIMIT, 1)
+                                                     .SetDefaultValidity(),
                                              &key_blob, &key_characteristics));
 
         ASSERT_GT(key_blob.size(), 0U);
@@ -807,7 +528,8 @@
               GenerateKey(AuthorizationSetBuilder()
                                   .Authorization(TAG_ALGORITHM, Algorithm::EC)
                                   .SigningKey()
-                                  .Digest(Digest::NONE)));
+                                  .Digest(Digest::NONE)
+                                  .SetDefaultValidity()));
 }
 
 /*
@@ -820,14 +542,17 @@
     for (auto key_size : InvalidKeySizes(Algorithm::EC)) {
         vector<uint8_t> key_blob;
         vector<KeyCharacteristics> key_characteristics;
-        ASSERT_EQ(ErrorCode::UNSUPPORTED_KEY_SIZE,
-                  GenerateKey(
-                          AuthorizationSetBuilder().EcdsaSigningKey(key_size).Digest(Digest::NONE),
-                          &key_blob, &key_characteristics));
+        ASSERT_EQ(ErrorCode::UNSUPPORTED_KEY_SIZE, GenerateKey(AuthorizationSetBuilder()
+                                                                       .EcdsaSigningKey(key_size)
+                                                                       .Digest(Digest::NONE)
+                                                                       .SetDefaultValidity(),
+                                                               &key_blob, &key_characteristics));
     }
 
-    ASSERT_EQ(ErrorCode::UNSUPPORTED_KEY_SIZE,
-              GenerateKey(AuthorizationSetBuilder().EcdsaSigningKey(190).Digest(Digest::NONE)));
+    ASSERT_EQ(ErrorCode::UNSUPPORTED_KEY_SIZE, GenerateKey(AuthorizationSetBuilder()
+                                                                   .EcdsaSigningKey(190)
+                                                                   .Digest(Digest::NONE)
+                                                                   .SetDefaultValidity()));
 }
 
 /*
@@ -843,7 +568,8 @@
               GenerateKey(AuthorizationSetBuilder()
                                   .EcdsaSigningKey(224)
                                   .Authorization(TAG_EC_CURVE, EcCurve::P_256)
-                                  .Digest(Digest::NONE)));
+                                  .Digest(Digest::NONE)
+                                  .SetDefaultValidity()));
 }
 
 /*
@@ -854,8 +580,10 @@
 TEST_P(NewKeyGenerationTest, EcdsaAllValidSizes) {
     auto valid_sizes = ValidKeySizes(Algorithm::EC);
     for (size_t size : valid_sizes) {
-        EXPECT_EQ(ErrorCode::OK,
-                  GenerateKey(AuthorizationSetBuilder().EcdsaSigningKey(size).Digest(Digest::NONE)))
+        EXPECT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
+                                                     .EcdsaSigningKey(size)
+                                                     .Digest(Digest::NONE)
+                                                     .SetDefaultValidity()))
                 << "Failed to generate size: " << size;
         CheckedDeleteKey();
     }
@@ -874,8 +602,10 @@
         digest = Digest::SHA_2_512;
     }
     for (auto curve : ValidCurves()) {
-        EXPECT_EQ(ErrorCode::OK,
-                  GenerateKey(AuthorizationSetBuilder().EcdsaSigningKey(curve).Digest(digest)))
+        EXPECT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
+                                                     .EcdsaSigningKey(curve)
+                                                     .Digest(digest)
+                                                     .SetDefaultValidity()))
                 << "Failed to generate key on curve: " << curve;
         CheckedDeleteKey();
     }
@@ -1058,7 +788,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
                                                  .Padding(PaddingMode::NONE)
-                                                 .Authorization(TAG_NO_AUTH_REQUIRED)));
+                                                 .Authorization(TAG_NO_AUTH_REQUIRED)
+                                                 .SetDefaultValidity()));
     string message = "12345678901234567890123456789012";
     string signature = SignMessage(
             message, AuthorizationSetBuilder().Digest(Digest::NONE).Padding(PaddingMode::NONE));
@@ -1076,7 +807,8 @@
                                                  .Digest(Digest::NONE)
                                                  .Padding(PaddingMode::NONE)
                                                  .Authorization(TAG_APPLICATION_ID, "clientid")
-                                                 .Authorization(TAG_APPLICATION_DATA, "appdata")));
+                                                 .Authorization(TAG_APPLICATION_DATA, "appdata")
+                                                 .SetDefaultValidity()));
     EXPECT_EQ(ErrorCode::INVALID_KEY_BLOB,
               Begin(KeyPurpose::SIGN,
                     AuthorizationSetBuilder().Digest(Digest::NONE).Padding(PaddingMode::NONE)));
@@ -1112,7 +844,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::SHA_2_256)
                                                  .Padding(PaddingMode::RSA_PSS)
-                                                 .Authorization(TAG_NO_AUTH_REQUIRED)));
+                                                 .Authorization(TAG_NO_AUTH_REQUIRED)
+                                                 .SetDefaultValidity()));
     // Use large message, which won't work without digesting.
     string message(1024, 'a');
     string signature = SignMessage(
@@ -1131,7 +864,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
     string message = "12345678901234567890123456789012";
     string signature;
 
@@ -1150,13 +884,13 @@
  */
 TEST_P(SigningOperationsTest, NoUserConfirmation) {
     if (SecLevel() == SecurityLevel::STRONGBOX) return;
-    ASSERT_EQ(ErrorCode::OK,
-              GenerateKey(AuthorizationSetBuilder()
-                                  .RsaSigningKey(1024, 65537)
-                                  .Digest(Digest::NONE)
-                                  .Padding(PaddingMode::NONE)
-                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                  .Authorization(TAG_TRUSTED_CONFIRMATION_REQUIRED)));
+    ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
+                                                 .RsaSigningKey(1024, 65537)
+                                                 .Digest(Digest::NONE)
+                                                 .Padding(PaddingMode::NONE)
+                                                 .Authorization(TAG_NO_AUTH_REQUIRED)
+                                                 .Authorization(TAG_TRUSTED_CONFIRMATION_REQUIRED)
+                                                 .SetDefaultValidity()));
 
     const string message = "12345678901234567890123456789012";
     EXPECT_EQ(ErrorCode::OK,
@@ -1176,7 +910,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::SHA_2_256)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)));
+                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)
+                                                 .SetDefaultValidity()));
     string message(1024, 'a');
     string signature = SignMessage(message, AuthorizationSetBuilder()
                                                     .Digest(Digest::SHA_2_256)
@@ -1193,7 +928,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)));
+                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)
+                                                 .SetDefaultValidity()));
     string message(53, 'a');
     string signature = SignMessage(message, AuthorizationSetBuilder()
                                                     .Digest(Digest::NONE)
@@ -1211,7 +947,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)));
+                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)
+                                                 .SetDefaultValidity()));
     string message(257, 'a');
 
     EXPECT_EQ(ErrorCode::OK,
@@ -1241,7 +978,8 @@
                                                  .RsaSigningKey(1024, 65537)
                                                  .Digest(Digest::SHA_2_512)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                 .Padding(PaddingMode::RSA_PSS)));
+                                                 .Padding(PaddingMode::RSA_PSS)
+                                                 .SetDefaultValidity()));
     EXPECT_EQ(ErrorCode::INCOMPATIBLE_DIGEST,
               Begin(KeyPurpose::SIGN, AuthorizationSetBuilder()
                                               .Digest(Digest::SHA_2_512)
@@ -1259,7 +997,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)));
+                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)
+                                                 .SetDefaultValidity()));
     // One byte too long
     string message(2048 / 8 + 1, 'a');
     ASSERT_EQ(ErrorCode::OK,
@@ -1293,7 +1032,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
 
     ASSERT_EQ(ErrorCode::OK,
               Begin(KeyPurpose::SIGN,
@@ -1318,7 +1058,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .Digest(Digest::SHA_2_256 /* supported digest */)
-                                                 .Padding(PaddingMode::PKCS7)));
+                                                 .Padding(PaddingMode::PKCS7)
+                                                 .SetDefaultValidity()));
     ASSERT_EQ(
             ErrorCode::UNSUPPORTED_PADDING_MODE,
             Begin(KeyPurpose::SIGN,
@@ -1335,7 +1076,8 @@
                                                  .RsaSigningKey(2048, 65537)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .Digest(Digest::NONE)
-                                                 .Padding(PaddingMode::RSA_PSS)));
+                                                 .Padding(PaddingMode::RSA_PSS)
+                                                 .SetDefaultValidity()));
     ASSERT_EQ(ErrorCode::INCOMPATIBLE_DIGEST,
               Begin(KeyPurpose::SIGN,
                     AuthorizationSetBuilder().Digest(Digest::NONE).Padding(PaddingMode::RSA_PSS)));
@@ -1356,7 +1098,8 @@
                                                  .RsaKey(2048, 65537)
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .SigningKey()
-                                                 .Digest(Digest::NONE)));
+                                                 .Digest(Digest::NONE)
+                                                 .SetDefaultValidity()));
     ASSERT_EQ(ErrorCode::UNSUPPORTED_PADDING_MODE,
               Begin(KeyPurpose::SIGN, AuthorizationSetBuilder().Digest(Digest::NONE)));
 }
@@ -1371,7 +1114,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
 
     // Barely shorter
     string message(2048 / 8 - 1, 'a');
@@ -1392,7 +1136,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
                                                  .Digest(Digest::NONE)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
     ASSERT_EQ(ErrorCode::INCOMPATIBLE_PURPOSE,
               Begin(KeyPurpose::SIGN,
                     AuthorizationSetBuilder().Digest(Digest::NONE).Padding(PaddingMode::NONE)));
@@ -1409,7 +1154,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
 
     // Largest possible message will always be larger than the public modulus.
     string message(2048 / 8, static_cast<char>(0xff));
@@ -1432,7 +1178,8 @@
             ErrorCode error = GenerateKey(AuthorizationSetBuilder()
                                                   .Authorization(TAG_NO_AUTH_REQUIRED)
                                                   .EcdsaSigningKey(key_size)
-                                                  .Digest(digest));
+                                                  .Digest(digest)
+                                                  .SetDefaultValidity());
             EXPECT_EQ(ErrorCode::OK, error) << "Failed to generate ECDSA key with size " << key_size
                                             << " and digest " << digest;
             if (error != ErrorCode::OK) continue;
@@ -1455,7 +1202,8 @@
         ErrorCode error = GenerateKey(AuthorizationSetBuilder()
                                               .Authorization(TAG_NO_AUTH_REQUIRED)
                                               .EcdsaSigningKey(curve)
-                                              .Digest(Digest::SHA_2_256));
+                                              .Digest(Digest::SHA_2_256)
+                                              .SetDefaultValidity());
         EXPECT_EQ(ErrorCode::OK, error) << "Failed to generate ECDSA key with curve " << curve;
         if (error != ErrorCode::OK) continue;
 
@@ -1477,7 +1225,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .EcdsaSigningKey(256)
-                                                 .Digest(Digest::NONE)));
+                                                 .Digest(Digest::NONE)
+                                                 .SetDefaultValidity()));
     string message(1 * 1024, 'a');
     SignMessage(message, AuthorizationSetBuilder().Digest(Digest::NONE));
 }
@@ -1493,7 +1242,8 @@
                                                  .EcdsaSigningKey(256)
                                                  .Digest(Digest::NONE)
                                                  .Authorization(TAG_APPLICATION_ID, "clientid")
-                                                 .Authorization(TAG_APPLICATION_DATA, "appdata")));
+                                                 .Authorization(TAG_APPLICATION_DATA, "appdata")
+                                                 .SetDefaultValidity()));
     EXPECT_EQ(ErrorCode::INVALID_KEY_BLOB,
               Begin(KeyPurpose::SIGN, AuthorizationSetBuilder().Digest(Digest::NONE)));
     AbortIfNeeded();
@@ -1682,7 +1432,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaSigningKey(2048, 65537)
                                                  .Digest(Digest::NONE)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
     string message = "12345678901234567890123456789012";
     string signature = SignMessage(
             message, AuthorizationSetBuilder().Digest(Digest::NONE).Padding(PaddingMode::NONE));
@@ -1702,7 +1453,8 @@
                                   .Digest(ValidDigests(true /* withNone */, true /* withMD5 */))
                                   .Padding(PaddingMode::NONE)
                                   .Padding(PaddingMode::RSA_PSS)
-                                  .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN);
+                                  .Padding(PaddingMode::RSA_PKCS1_1_5_SIGN)
+                                  .SetDefaultValidity();
 
     ASSERT_EQ(ErrorCode::OK, GenerateKey(authorizations));
 
@@ -1799,7 +1551,8 @@
         ErrorCode error = GenerateKey(AuthorizationSetBuilder()
                                               .Authorization(TAG_NO_AUTH_REQUIRED)
                                               .EcdsaSigningKey(curve)
-                                              .Digest(digests));
+                                              .Digest(digests)
+                                              .SetDefaultValidity());
         EXPECT_EQ(ErrorCode::OK, error) << "Failed to generate key for EC curve " << curve;
         if (error != ErrorCode::OK) {
             continue;
@@ -1962,7 +1715,8 @@
                                                .Authorization(TAG_NO_AUTH_REQUIRED)
                                                .RsaSigningKey(1024, 65537)
                                                .Digest(Digest::SHA_2_256)
-                                               .Padding(PaddingMode::RSA_PSS),
+                                               .Padding(PaddingMode::RSA_PSS)
+                                               .SetDefaultValidity(),
                                        KeyFormat::PKCS8, rsa_key));
 
     CheckCryptoParam(TAG_ALGORITHM, Algorithm::RSA);
@@ -1989,7 +1743,8 @@
               ImportKey(AuthorizationSetBuilder()
                                 .RsaSigningKey(2048 /* Doesn't match key */, 65537)
                                 .Digest(Digest::NONE)
-                                .Padding(PaddingMode::NONE),
+                                .Padding(PaddingMode::NONE)
+                                .SetDefaultValidity(),
                         KeyFormat::PKCS8, rsa_key));
 }
 
@@ -2004,7 +1759,8 @@
               ImportKey(AuthorizationSetBuilder()
                                 .RsaSigningKey(1024, 3 /* Doesn't match key */)
                                 .Digest(Digest::NONE)
-                                .Padding(PaddingMode::NONE),
+                                .Padding(PaddingMode::NONE)
+                                .SetDefaultValidity(),
                         KeyFormat::PKCS8, rsa_key));
 }
 
@@ -2017,7 +1773,8 @@
     ASSERT_EQ(ErrorCode::OK, ImportKey(AuthorizationSetBuilder()
                                                .Authorization(TAG_NO_AUTH_REQUIRED)
                                                .EcdsaSigningKey(256)
-                                               .Digest(Digest::SHA_2_256),
+                                               .Digest(Digest::SHA_2_256)
+                                               .SetDefaultValidity(),
                                        KeyFormat::PKCS8, ec_256_key));
 
     CheckCryptoParam(TAG_ALGORITHM, Algorithm::EC);
@@ -2043,7 +1800,8 @@
     ASSERT_EQ(ErrorCode::OK, ImportKey(AuthorizationSetBuilder()
                                                .Authorization(TAG_NO_AUTH_REQUIRED)
                                                .EcdsaSigningKey(256)
-                                               .Digest(Digest::SHA_2_256),
+                                               .Digest(Digest::SHA_2_256)
+                                               .SetDefaultValidity(),
                                        KeyFormat::PKCS8, ec_256_key_rfc5915));
 
     CheckCryptoParam(TAG_ALGORITHM, Algorithm::EC);
@@ -2068,7 +1826,8 @@
     ASSERT_EQ(ErrorCode::OK, ImportKey(AuthorizationSetBuilder()
                                                .Authorization(TAG_NO_AUTH_REQUIRED)
                                                .EcdsaSigningKey(256)
-                                               .Digest(Digest::SHA_2_256),
+                                               .Digest(Digest::SHA_2_256)
+                                               .SetDefaultValidity(),
                                        KeyFormat::PKCS8, ec_256_key_sec1));
 
     CheckCryptoParam(TAG_ALGORITHM, Algorithm::EC);
@@ -2094,7 +1853,8 @@
     ASSERT_EQ(ErrorCode::OK, ImportKey(AuthorizationSetBuilder()
                                                .Authorization(TAG_NO_AUTH_REQUIRED)
                                                .EcdsaSigningKey(521)
-                                               .Digest(Digest::SHA_2_256),
+                                               .Digest(Digest::SHA_2_256)
+                                               .SetDefaultValidity(),
                                        KeyFormat::PKCS8, ec_521_key));
 
     CheckCryptoParam(TAG_ALGORITHM, Algorithm::EC);
@@ -2119,7 +1879,8 @@
     ASSERT_EQ(ErrorCode::IMPORT_PARAMETER_MISMATCH,
               ImportKey(AuthorizationSetBuilder()
                                 .EcdsaSigningKey(224 /* Doesn't match key */)
-                                .Digest(Digest::NONE),
+                                .Digest(Digest::NONE)
+                                .SetDefaultValidity(),
                         KeyFormat::PKCS8, ec_256_key));
 }
 
@@ -2133,7 +1894,8 @@
     ASSERT_EQ(ErrorCode::IMPORT_PARAMETER_MISMATCH,
               ImportKey(AuthorizationSetBuilder()
                                 .EcdsaSigningKey(EcCurve::P_224 /* Doesn't match key */)
-                                .Digest(Digest::NONE),
+                                .Digest(Digest::NONE)
+                                .SetDefaultValidity(),
                         KeyFormat::PKCS8, ec_256_key));
 }
 
@@ -2254,7 +2016,8 @@
                                      .RsaEncryptionKey(2048, 65537)
                                      .Digest(Digest::SHA_2_256)
                                      .Padding(PaddingMode::RSA_OAEP)
-                                     .Authorization(TAG_PURPOSE, KeyPurpose::WRAP_KEY);
+                                     .Authorization(TAG_PURPOSE, KeyPurpose::WRAP_KEY)
+                                     .SetDefaultValidity();
 
     ASSERT_EQ(ErrorCode::OK,
               ImportWrappedKey(wrapped_key, wrapping_key, wrapping_key_desc, zero_masking_key,
@@ -2274,7 +2037,8 @@
                                      .RsaEncryptionKey(2048, 65537)
                                      .Digest(Digest::SHA_2_256)
                                      .Padding(PaddingMode::RSA_OAEP)
-                                     .Authorization(TAG_PURPOSE, KeyPurpose::WRAP_KEY);
+                                     .Authorization(TAG_PURPOSE, KeyPurpose::WRAP_KEY)
+                                     .SetDefaultValidity();
 
     ASSERT_EQ(ErrorCode::OK,
               ImportWrappedKey(wrapped_key_masked, wrapping_key, wrapping_key_desc, masking_key,
@@ -2288,7 +2052,8 @@
                                      .RsaEncryptionKey(2048, 65537)
                                      .Digest(Digest::SHA_2_256)
                                      .Padding(PaddingMode::RSA_OAEP)
-                                     .Authorization(TAG_PURPOSE, KeyPurpose::WRAP_KEY);
+                                     .Authorization(TAG_PURPOSE, KeyPurpose::WRAP_KEY)
+                                     .SetDefaultValidity();
 
     ASSERT_EQ(
             ErrorCode::VERIFICATION_FAILED,
@@ -2302,7 +2067,8 @@
     auto wrapping_key_desc = AuthorizationSetBuilder()
                                      .RsaEncryptionKey(2048, 65537)
                                      .Digest(Digest::SHA_2_256)
-                                     .Padding(PaddingMode::RSA_OAEP);
+                                     .Padding(PaddingMode::RSA_OAEP)
+                                     .SetDefaultValidity();
 
     ASSERT_EQ(
             ErrorCode::INCOMPATIBLE_PURPOSE,
@@ -2325,7 +2091,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
 
     string message = string(2048 / 8, 'a');
     auto params = AuthorizationSetBuilder().Padding(PaddingMode::NONE);
@@ -2348,7 +2115,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
 
     string message = "1";
     auto params = AuthorizationSetBuilder().Padding(PaddingMode::NONE);
@@ -2377,7 +2145,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
 
     string message(2048 / 8 + 1, 'a');
 
@@ -2410,7 +2179,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(key_size, 65537)
                                                  .Padding(PaddingMode::RSA_OAEP)
-                                                 .Digest(digests)));
+                                                 .Digest(digests)
+                                                 .SetDefaultValidity()));
 
     string message = "Hello";
 
@@ -2458,7 +2228,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
                                                  .Padding(PaddingMode::RSA_OAEP)
-                                                 .Digest(Digest::NONE)));
+                                                 .Digest(Digest::NONE)
+                                                 .SetDefaultValidity()));
     string message = "Hello World!";
 
     auto params = AuthorizationSetBuilder().Padding(PaddingMode::RSA_OAEP).Digest(Digest::NONE);
@@ -2478,7 +2249,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(1024, 65537)
                                                  .Padding(PaddingMode::RSA_OAEP)
-                                                 .Digest(Digest::SHA_2_224, Digest::SHA_2_256)));
+                                                 .Digest(Digest::SHA_2_224, Digest::SHA_2_256)
+                                                 .SetDefaultValidity()));
     string message = "Hello World!";
     string ciphertext = EncryptMessage(
             message,
@@ -2503,7 +2275,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
                                                  .Padding(PaddingMode::RSA_OAEP)
-                                                 .Digest(Digest::SHA_2_256)));
+                                                 .Digest(Digest::SHA_2_256)
+                                                 .SetDefaultValidity()));
     constexpr size_t digest_size = 256 /* SHA_2_256 */ / 8;
     constexpr size_t oaep_overhead = 2 * digest_size + 2;
     string message(2048 / 8 - oaep_overhead + 1, 'a');
@@ -2531,7 +2304,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(key_size, 65537)
                                                  .Padding(PaddingMode::RSA_OAEP)
-                                                 .Digest(Digest::SHA_2_256)));
+                                                 .Digest(Digest::SHA_2_256)
+                                                 .SetDefaultValidity()));
 
     string message = "Hello";
 
@@ -2584,7 +2358,8 @@
                                   .Authorization(TAG_NO_AUTH_REQUIRED)
                                   .RsaEncryptionKey(2048, 65537)
                                   .Padding(PaddingMode::RSA_OAEP)
-                                  .Digest(Digest::SHA_2_256)));
+                                  .Digest(Digest::SHA_2_256)
+                                  .SetDefaultValidity()));
     string message = "Hello World!";
 
     auto params = AuthorizationSetBuilder()
@@ -2607,7 +2382,8 @@
                                   .Authorization(TAG_NO_AUTH_REQUIRED)
                                   .RsaEncryptionKey(2048, 65537)
                                   .Padding(PaddingMode::RSA_OAEP)
-                                  .Digest(Digest::SHA_2_256)));
+                                  .Digest(Digest::SHA_2_256)
+                                  .SetDefaultValidity()));
     string message = "Hello World!";
 
     auto params = AuthorizationSetBuilder()
@@ -2626,7 +2402,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
-                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_ENCRYPT)));
+                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_ENCRYPT)
+                                                 .SetDefaultValidity()));
 
     string message = "Hello World!";
     auto params = AuthorizationSetBuilder().Padding(PaddingMode::RSA_PKCS1_1_5_ENCRYPT);
@@ -2665,7 +2442,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
-                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_ENCRYPT)));
+                                                 .Padding(PaddingMode::RSA_PKCS1_1_5_ENCRYPT)
+                                                 .SetDefaultValidity()));
     string message(2048 / 8 - 10, 'a');
 
     auto params = AuthorizationSetBuilder().Padding(PaddingMode::RSA_PKCS1_1_5_ENCRYPT);
@@ -2685,7 +2463,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .EcdsaSigningKey(256)
-                                                 .Digest(Digest::NONE)));
+                                                 .Digest(Digest::NONE)
+                                                 .SetDefaultValidity()));
     auto params = AuthorizationSetBuilder().Digest(Digest::NONE);
     ASSERT_EQ(ErrorCode::UNSUPPORTED_PURPOSE, Begin(KeyPurpose::ENCRYPT, params));
     ASSERT_EQ(ErrorCode::UNSUPPORTED_PURPOSE, Begin(KeyPurpose::DECRYPT, params));
@@ -4333,7 +4112,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaSigningKey(1024, 65537)
                                                  .NoDigestOrPadding()
-                                                 .Authorization(TAG_MAX_USES_PER_BOOT, 3)));
+                                                 .Authorization(TAG_MAX_USES_PER_BOOT, 3)
+                                                 .SetDefaultValidity()));
 
     string message = "1234567890123456";
 
@@ -4452,7 +4232,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaSigningKey(1024, 65537)
                                                  .NoDigestOrPadding()
-                                                 .Authorization(TAG_USAGE_COUNT_LIMIT, 1)));
+                                                 .Authorization(TAG_USAGE_COUNT_LIMIT, 1)
+                                                 .SetDefaultValidity()));
 
     // Check the usage count limit tag appears in the authorizations.
     AuthorizationSet auths;
@@ -4495,7 +4276,8 @@
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaSigningKey(1024, 65537)
                                                  .NoDigestOrPadding()
-                                                 .Authorization(TAG_USAGE_COUNT_LIMIT, 3)));
+                                                 .Authorization(TAG_USAGE_COUNT_LIMIT, 3)
+                                                 .SetDefaultValidity()));
 
     // Check the usage count limit tag appears in the authorizations.
     AuthorizationSet auths;
@@ -4527,6 +4309,57 @@
     }
 }
 
+/*
+ * UsageCountLimitTest.TestSingleUseKeyAndRollbackResistance
+ *
+ * Verifies that when rollback resistance is supported by the KeyMint implementation with
+ * the secure hardware, the single use key with usage count limit tag = 1 must also be enforced
+ * in hardware.
+ */
+TEST_P(UsageCountLimitTest, TestSingleUseKeyAndRollbackResistance) {
+    if (SecLevel() == SecurityLevel::STRONGBOX) return;
+
+    auto error = GenerateKey(AuthorizationSetBuilder()
+                                     .RsaSigningKey(2048, 65537)
+                                     .Digest(Digest::NONE)
+                                     .Padding(PaddingMode::NONE)
+                                     .Authorization(TAG_NO_AUTH_REQUIRED)
+                                     .Authorization(TAG_ROLLBACK_RESISTANCE)
+                                     .SetDefaultValidity());
+    ASSERT_TRUE(error == ErrorCode::ROLLBACK_RESISTANCE_UNAVAILABLE || error == ErrorCode::OK);
+
+    if (error == ErrorCode::OK) {
+        // Rollback resistance is supported by KeyMint, verify it is enforced in hardware.
+        AuthorizationSet hardwareEnforced(SecLevelAuthorizations());
+        ASSERT_TRUE(hardwareEnforced.Contains(TAG_ROLLBACK_RESISTANCE));
+        ASSERT_EQ(ErrorCode::OK, DeleteKey());
+
+        // The KeyMint should also enforce single use key in hardware when it supports rollback
+        // resistance.
+        ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
+                                                     .Authorization(TAG_NO_AUTH_REQUIRED)
+                                                     .RsaSigningKey(1024, 65537)
+                                                     .NoDigestOrPadding()
+                                                     .Authorization(TAG_USAGE_COUNT_LIMIT, 1)
+                                                     .SetDefaultValidity()));
+
+        // Check the usage count limit tag appears in the hardware authorizations.
+        AuthorizationSet hardware_auths = HwEnforcedAuthorizations(key_characteristics_);
+        EXPECT_TRUE(hardware_auths.Contains(TAG_USAGE_COUNT_LIMIT, 1U))
+                << "key usage count limit " << 1U << " missing";
+
+        string message = "1234567890123456";
+        auto params = AuthorizationSetBuilder().NoDigestOrPadding();
+
+        // First usage of RSA key should work.
+        SignMessage(message, params);
+
+        // Usage count limit tag is enforced by hardware. After using the key, the key blob
+        // must be invalidated from secure storage (such as RPMB partition).
+        EXPECT_EQ(ErrorCode::INVALID_KEY_BLOB, Begin(KeyPurpose::SIGN, params));
+    }
+}
+
 INSTANTIATE_KEYMINT_AIDL_TEST(UsageCountLimitTest);
 
 typedef KeyMintAidlTestBase AddEntropyTest;
@@ -4576,7 +4409,8 @@
                                      .Digest(Digest::NONE)
                                      .Padding(PaddingMode::NONE)
                                      .Authorization(TAG_NO_AUTH_REQUIRED)
-                                     .Authorization(TAG_ROLLBACK_RESISTANCE));
+                                     .Authorization(TAG_ROLLBACK_RESISTANCE)
+                                     .SetDefaultValidity());
     ASSERT_TRUE(error == ErrorCode::ROLLBACK_RESISTANCE_UNAVAILABLE || error == ErrorCode::OK);
 
     // Delete must work if rollback protection is implemented
@@ -4609,7 +4443,8 @@
                                      .Digest(Digest::NONE)
                                      .Padding(PaddingMode::NONE)
                                      .Authorization(TAG_NO_AUTH_REQUIRED)
-                                     .Authorization(TAG_ROLLBACK_RESISTANCE));
+                                     .Authorization(TAG_ROLLBACK_RESISTANCE)
+                                     .SetDefaultValidity());
     ASSERT_TRUE(error == ErrorCode::ROLLBACK_RESISTANCE_UNAVAILABLE || error == ErrorCode::OK);
 
     // Delete must work if rollback protection is implemented
@@ -4704,7 +4539,8 @@
     ASSERT_EQ(ErrorCode::OK, GenerateKey(AuthorizationSetBuilder()
                                                  .Authorization(TAG_NO_AUTH_REQUIRED)
                                                  .RsaEncryptionKey(2048, 65537)
-                                                 .Padding(PaddingMode::NONE)));
+                                                 .Padding(PaddingMode::NONE)
+                                                 .SetDefaultValidity()));
 
     auto params = AuthorizationSetBuilder().Padding(PaddingMode::NONE);
     constexpr size_t max_operations = 100;  // set to arbituary large number
@@ -4835,7 +4671,8 @@
                                         .Authorization(TAG_PURPOSE, KeyPurpose::AGREE_KEY)
                                         .Authorization(TAG_ALGORITHM, Algorithm::EC)
                                         .Authorization(TAG_ATTESTATION_APPLICATION_ID, {0x61, 0x62})
-                                        .Authorization(TAG_ATTESTATION_CHALLENGE, challenge)))
+                                        .Authorization(TAG_ATTESTATION_CHALLENGE, challenge)
+                                        .SetDefaultValidity()))
                     << "Failed to generate key";
             ASSERT_GT(cert_chain_.size(), 0);
             X509_Ptr kmKeyCert(parse_cert_blob(cert_chain_[0].encodedCertificate));
@@ -4890,17 +4727,122 @@
 
 INSTANTIATE_KEYMINT_AIDL_TEST(KeyAgreementTest);
 
+typedef KeyMintAidlTestBase EarlyBootKeyTest;
+
+TEST_P(EarlyBootKeyTest, CreateEarlyBootKeys) {
+    auto [aesKeyData, hmacKeyData, rsaKeyData, ecdsaKeyData] =
+            CreateTestKeys(TAG_EARLY_BOOT_ONLY, ErrorCode::OK);
+
+    CheckedDeleteKey(&aesKeyData.blob);
+    CheckedDeleteKey(&hmacKeyData.blob);
+    CheckedDeleteKey(&rsaKeyData.blob);
+    CheckedDeleteKey(&ecdsaKeyData.blob);
+}
+
+// This is a more comprenhensive test, but it can only be run on a machine which is still in early
+// boot stage, which no proper Android device is by the time we can run VTS.  To use this,
+// un-disable it and modify vold to remove the call to earlyBootEnded().  Running the test will end
+// early boot, so you'll have to reboot between runs.
+TEST_P(EarlyBootKeyTest, DISABLED_FullTest) {
+    auto [aesKeyData, hmacKeyData, rsaKeyData, ecdsaKeyData] =
+            CreateTestKeys(TAG_EARLY_BOOT_ONLY, ErrorCode::OK);
+    // TAG_EARLY_BOOT_ONLY should be in hw-enforced.
+    EXPECT_TRUE(HwEnforcedAuthorizations(aesKeyData.characteristics).Contains(TAG_EARLY_BOOT_ONLY));
+    EXPECT_TRUE(
+            HwEnforcedAuthorizations(hmacKeyData.characteristics).Contains(TAG_EARLY_BOOT_ONLY));
+    EXPECT_TRUE(HwEnforcedAuthorizations(rsaKeyData.characteristics).Contains(TAG_EARLY_BOOT_ONLY));
+    EXPECT_TRUE(
+            HwEnforcedAuthorizations(ecdsaKeyData.characteristics).Contains(TAG_EARLY_BOOT_ONLY));
+
+    // Should be able to use keys, since early boot has not ended
+    EXPECT_EQ(ErrorCode::OK, UseAesKey(aesKeyData.blob));
+    EXPECT_EQ(ErrorCode::OK, UseHmacKey(hmacKeyData.blob));
+    EXPECT_EQ(ErrorCode::OK, UseRsaKey(rsaKeyData.blob));
+    EXPECT_EQ(ErrorCode::OK, UseEcdsaKey(ecdsaKeyData.blob));
+
+    // End early boot
+    ErrorCode earlyBootResult = GetReturnErrorCode(keyMint().earlyBootEnded());
+    EXPECT_EQ(earlyBootResult, ErrorCode::OK);
+
+    // Should not be able to use already-created keys.
+    EXPECT_EQ(ErrorCode::EARLY_BOOT_ENDED, UseAesKey(aesKeyData.blob));
+    EXPECT_EQ(ErrorCode::EARLY_BOOT_ENDED, UseHmacKey(hmacKeyData.blob));
+    EXPECT_EQ(ErrorCode::EARLY_BOOT_ENDED, UseRsaKey(rsaKeyData.blob));
+    EXPECT_EQ(ErrorCode::EARLY_BOOT_ENDED, UseEcdsaKey(ecdsaKeyData.blob));
+
+    CheckedDeleteKey(&aesKeyData.blob);
+    CheckedDeleteKey(&hmacKeyData.blob);
+    CheckedDeleteKey(&rsaKeyData.blob);
+    CheckedDeleteKey(&ecdsaKeyData.blob);
+
+    // Should not be able to create new keys
+    std::tie(aesKeyData, hmacKeyData, rsaKeyData, ecdsaKeyData) =
+            CreateTestKeys(TAG_EARLY_BOOT_ONLY, ErrorCode::EARLY_BOOT_ENDED);
+
+    CheckedDeleteKey(&aesKeyData.blob);
+    CheckedDeleteKey(&hmacKeyData.blob);
+    CheckedDeleteKey(&rsaKeyData.blob);
+    CheckedDeleteKey(&ecdsaKeyData.blob);
+}
+INSTANTIATE_KEYMINT_AIDL_TEST(EarlyBootKeyTest);
+
+typedef KeyMintAidlTestBase UnlockedDeviceRequiredTest;
+
+// This may be a problematic test.  It can't be run repeatedly without unlocking the device in
+// between runs... and on most test devices there are no enrolled credentials so it can't be
+// unlocked at all, meaning the only way to get the test to pass again on a properly-functioning
+// device is to reboot it.  For that reason, this is disabled by default.  It can be used as part of
+// a manual test process, which includes unlocking between runs, which is why it's included here.
+// Well, that and the fact that it's the only test we can do without also making calls into the
+// Gatekeeper HAL.  We haven't written any cross-HAL tests, and don't know what all of the
+// implications might be, so that may or may not be a solution.
+TEST_P(UnlockedDeviceRequiredTest, DISABLED_KeysBecomeUnusable) {
+    auto [aesKeyData, hmacKeyData, rsaKeyData, ecdsaKeyData] =
+            CreateTestKeys(TAG_UNLOCKED_DEVICE_REQUIRED, ErrorCode::OK);
+
+    EXPECT_EQ(ErrorCode::OK, UseAesKey(aesKeyData.blob));
+    EXPECT_EQ(ErrorCode::OK, UseHmacKey(hmacKeyData.blob));
+    EXPECT_EQ(ErrorCode::OK, UseRsaKey(rsaKeyData.blob));
+    EXPECT_EQ(ErrorCode::OK, UseEcdsaKey(ecdsaKeyData.blob));
+
+    ErrorCode rc = GetReturnErrorCode(
+            keyMint().deviceLocked(false /* passwordOnly */, {} /* verificationToken */));
+    ASSERT_EQ(ErrorCode::OK, rc);
+    EXPECT_EQ(ErrorCode::DEVICE_LOCKED, UseAesKey(aesKeyData.blob));
+    EXPECT_EQ(ErrorCode::DEVICE_LOCKED, UseHmacKey(hmacKeyData.blob));
+    EXPECT_EQ(ErrorCode::DEVICE_LOCKED, UseRsaKey(rsaKeyData.blob));
+    EXPECT_EQ(ErrorCode::DEVICE_LOCKED, UseEcdsaKey(ecdsaKeyData.blob));
+
+    CheckedDeleteKey(&aesKeyData.blob);
+    CheckedDeleteKey(&hmacKeyData.blob);
+    CheckedDeleteKey(&rsaKeyData.blob);
+    CheckedDeleteKey(&ecdsaKeyData.blob);
+}
+INSTANTIATE_KEYMINT_AIDL_TEST(UnlockedDeviceRequiredTest);
+
 }  // namespace aidl::android::hardware::security::keymint::test
 
 int main(int argc, char** argv) {
+    std::cout << "Testing ";
+    auto halInstances =
+            aidl::android::hardware::security::keymint::test::KeyMintAidlTestBase::build_params();
+    std::cout << "HAL instances:\n";
+    for (auto& entry : halInstances) {
+        std::cout << "    " << entry << '\n';
+    }
+
     ::testing::InitGoogleTest(&argc, argv);
     for (int i = 1; i < argc; ++i) {
         if (argv[i][0] == '-') {
             if (std::string(argv[i]) == "--arm_deleteAllKeys") {
-                arm_deleteAllKeys = true;
+                aidl::android::hardware::security::keymint::test::KeyMintAidlTestBase::
+                        arm_deleteAllKeys = true;
             }
             if (std::string(argv[i]) == "--dump_attestations") {
-                dump_Attestations = true;
+                aidl::android::hardware::security::keymint::test::KeyMintAidlTestBase::
+                        dump_Attestations = true;
+            } else {
+                std::cout << "NOT dumping attestations" << std::endl;
             }
         }
     }
diff --git a/security/keymint/aidl/vts/functional/VtsRemotelyProvisionedComponentTests.cpp b/security/keymint/aidl/vts/functional/VtsRemotelyProvisionedComponentTests.cpp
new file mode 100644
index 0000000..45f9df6
--- /dev/null
+++ b/security/keymint/aidl/vts/functional/VtsRemotelyProvisionedComponentTests.cpp
@@ -0,0 +1,432 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "VtsRemotelyProvisionableComponentTests"
+
+#include <RemotelyProvisionedComponent.h>
+#include <aidl/Gtest.h>
+#include <aidl/Vintf.h>
+#include <aidl/android/hardware/security/keymint/IRemotelyProvisionedComponent.h>
+#include <aidl/android/hardware/security/keymint/SecurityLevel.h>
+#include <android/binder_manager.h>
+#include <cppbor_parse.h>
+#include <cppcose/cppcose.h>
+#include <gmock/gmock.h>
+#include <gtest/gtest.h>
+#include <keymaster/keymaster_configuration.h>
+#include <remote_prov/remote_prov_utils.h>
+
+namespace aidl::android::hardware::security::keymint::test {
+
+using ::std::string;
+using ::std::vector;
+
+namespace {
+
+#define INSTANTIATE_REM_PROV_AIDL_TEST(name)                                         \
+    INSTANTIATE_TEST_SUITE_P(                                                        \
+            PerInstance, name,                                                       \
+            testing::ValuesIn(VtsRemotelyProvisionedComponentTests::build_params()), \
+            ::android::PrintInstanceNameToString)
+
+using bytevec = std::vector<uint8_t>;
+using testing::MatchesRegex;
+using namespace remote_prov;
+using namespace keymaster;
+
+bytevec string_to_bytevec(const char* s) {
+    const uint8_t* p = reinterpret_cast<const uint8_t*>(s);
+    return bytevec(p, p + strlen(s));
+}
+
+}  // namespace
+
+class VtsRemotelyProvisionedComponentTests : public testing::TestWithParam<std::string> {
+  public:
+    virtual void SetUp() override {
+        if (AServiceManager_isDeclared(GetParam().c_str())) {
+            ::ndk::SpAIBinder binder(AServiceManager_waitForService(GetParam().c_str()));
+            provisionable_ = IRemotelyProvisionedComponent::fromBinder(binder);
+        }
+        ASSERT_NE(provisionable_, nullptr);
+    }
+
+    static vector<string> build_params() {
+        auto params = ::android::getAidlHalInstanceNames(IRemotelyProvisionedComponent::descriptor);
+        return params;
+    }
+
+  protected:
+    std::shared_ptr<IRemotelyProvisionedComponent> provisionable_;
+};
+
+using GenerateKeyTests = VtsRemotelyProvisionedComponentTests;
+
+INSTANTIATE_REM_PROV_AIDL_TEST(GenerateKeyTests);
+
+/**
+ * Generate and validate a production-mode key.  MAC tag can't be verified.
+ */
+TEST_P(GenerateKeyTests, DISABLED_generateEcdsaP256Key_prodMode) {
+    MacedPublicKey macedPubKey;
+    bytevec privateKeyBlob;
+    bool testMode = false;
+    auto status = provisionable_->generateEcdsaP256KeyPair(testMode, &macedPubKey, &privateKeyBlob);
+    ASSERT_TRUE(status.isOk());
+
+    auto [coseMac0, _, mac0ParseErr] = cppbor::parse(macedPubKey.macedKey);
+    ASSERT_TRUE(coseMac0) << "COSE Mac0 parse failed " << mac0ParseErr;
+
+    ASSERT_NE(coseMac0->asArray(), nullptr);
+    ASSERT_EQ(coseMac0->asArray()->size(), kCoseMac0EntryCount);
+
+    auto protParms = coseMac0->asArray()->get(kCoseMac0ProtectedParams)->asBstr();
+    ASSERT_NE(protParms, nullptr);
+    ASSERT_EQ(cppbor::prettyPrint(protParms->value()), "{\n  1 : 5,\n}");
+
+    auto unprotParms = coseMac0->asArray()->get(kCoseMac0UnprotectedParams)->asBstr();
+    ASSERT_NE(unprotParms, nullptr);
+    ASSERT_EQ(unprotParms->value().size(), 0);
+
+    auto payload = coseMac0->asArray()->get(kCoseMac0Payload)->asBstr();
+    ASSERT_NE(payload, nullptr);
+    auto [parsedPayload, __, payloadParseErr] = cppbor::parse(payload->value());
+    ASSERT_TRUE(parsedPayload) << "Key parse failed: " << payloadParseErr;
+    EXPECT_THAT(cppbor::prettyPrint(parsedPayload.get()),
+                MatchesRegex("{\n"
+                             "  1 : 2,\n"
+                             "  3 : -7,\n"
+                             "  -1 : 1,\n"
+                             // The regex {(0x[0-9a-f]{2}, ){31}0x[0-9a-f]{2}} matches a sequence of
+                             // 32 hexadecimal bytes, enclosed in braces and separated by commas.
+                             // In this case, some Ed25519 public key.
+                             "  -2 : {(0x[0-9a-f]{2}, ){31}0x[0-9a-f]{2}},\n"
+                             "  -3 : {(0x[0-9a-f]{2}, ){31}0x[0-9a-f]{2}},\n"
+                             "}"));
+
+    auto coseMac0Tag = coseMac0->asArray()->get(kCoseMac0Tag)->asBstr();
+    ASSERT_TRUE(coseMac0Tag);
+    auto extractedTag = coseMac0Tag->value();
+    EXPECT_EQ(extractedTag.size(), 32U);
+
+    // Compare with tag generated with kTestMacKey.  Shouldn't match.
+    auto testTag = cppcose::generateCoseMac0Mac(remote_prov::kTestMacKey, {} /* external_aad */,
+                                                payload->value());
+    ASSERT_TRUE(testTag) << "Tag calculation failed: " << testTag.message();
+
+    EXPECT_NE(*testTag, extractedTag);
+}
+
+/**
+ * Generate and validate a test-mode key.
+ */
+TEST_P(GenerateKeyTests, DISABLED_generateEcdsaP256Key_testMode) {
+    MacedPublicKey macedPubKey;
+    bytevec privateKeyBlob;
+    bool testMode = true;
+    auto status = provisionable_->generateEcdsaP256KeyPair(testMode, &macedPubKey, &privateKeyBlob);
+    ASSERT_TRUE(status.isOk());
+
+    auto [coseMac0, _, mac0ParseErr] = cppbor::parse(macedPubKey.macedKey);
+    ASSERT_TRUE(coseMac0) << "COSE Mac0 parse failed " << mac0ParseErr;
+
+    ASSERT_NE(coseMac0->asArray(), nullptr);
+    ASSERT_EQ(coseMac0->asArray()->size(), kCoseMac0EntryCount);
+
+    auto protParms = coseMac0->asArray()->get(kCoseMac0ProtectedParams)->asBstr();
+    ASSERT_NE(protParms, nullptr);
+    ASSERT_EQ(cppbor::prettyPrint(protParms->value()), "{\n  1 : 5,\n}");
+
+    auto unprotParms = coseMac0->asArray()->get(kCoseMac0UnprotectedParams)->asBstr();
+    ASSERT_NE(unprotParms, nullptr);
+    ASSERT_EQ(unprotParms->value().size(), 0);
+
+    auto payload = coseMac0->asArray()->get(kCoseMac0Payload)->asBstr();
+    ASSERT_NE(payload, nullptr);
+    auto [parsedPayload, __, payloadParseErr] = cppbor::parse(payload->value());
+    ASSERT_TRUE(parsedPayload) << "Key parse failed: " << payloadParseErr;
+    EXPECT_THAT(cppbor::prettyPrint(parsedPayload.get()),
+                MatchesRegex("{\n"
+                             "  1 : 2,\n"
+                             "  3 : -7,\n"
+                             "  -1 : 1,\n"
+                             // The regex {(0x[0-9a-f]{2}, ){31}0x[0-9a-f]{2}} matches a sequence of
+                             // 32 hexadecimal bytes, enclosed in braces and separated by commas.
+                             // In this case, some Ed25519 public key.
+                             "  -2 : {(0x[0-9a-f]{2}, ){31}0x[0-9a-f]{2}},\n"
+                             "  -3 : {(0x[0-9a-f]{2}, ){31}0x[0-9a-f]{2}},\n"
+                             "  -70000 : null,\n"
+                             "}"));
+
+    auto coseMac0Tag = coseMac0->asArray()->get(kCoseMac0Tag)->asBstr();
+    ASSERT_TRUE(coseMac0);
+    auto extractedTag = coseMac0Tag->value();
+    EXPECT_EQ(extractedTag.size(), 32U);
+
+    // Compare with tag generated with kTestMacKey.  Should match.
+    auto testTag = cppcose::generateCoseMac0Mac(remote_prov::kTestMacKey, {} /* external_aad */,
+                                                payload->value());
+    ASSERT_TRUE(testTag) << testTag.message();
+
+    EXPECT_EQ(*testTag, extractedTag);
+}
+
+class CertificateRequestTest : public VtsRemotelyProvisionedComponentTests {
+  protected:
+    CertificateRequestTest() : eekId_(string_to_bytevec("eekid")) {
+        auto chain = generateEekChain(3, eekId_);
+        EXPECT_TRUE(chain) << chain.message();
+        if (chain) eekChain_ = chain.moveValue();
+    }
+
+    void generateKeys(bool testMode, size_t numKeys) {
+        keysToSign_ = std::vector<MacedPublicKey>(numKeys);
+        cborKeysToSign_ = cppbor::Array();
+
+        for (auto& key : keysToSign_) {
+            bytevec privateKeyBlob;
+            auto status = provisionable_->generateEcdsaP256KeyPair(testMode, &key, &privateKeyBlob);
+            ASSERT_TRUE(status.isOk()) << status.getMessage();
+
+            auto [parsedMacedKey, _, parseErr] = cppbor::parse(key.macedKey);
+            ASSERT_TRUE(parsedMacedKey) << "Failed parsing MACed key: " << parseErr;
+            ASSERT_TRUE(parsedMacedKey->asArray()) << "COSE_Mac0 not an array?";
+            ASSERT_EQ(parsedMacedKey->asArray()->size(), kCoseMac0EntryCount);
+
+            auto& payload = parsedMacedKey->asArray()->get(kCoseMac0Payload);
+            ASSERT_TRUE(payload);
+            ASSERT_TRUE(payload->asBstr());
+
+            cborKeysToSign_.add(cppbor::EncodedItem(payload->asBstr()->value()));
+        }
+    }
+
+    bytevec eekId_;
+    EekChain eekChain_;
+    std::vector<MacedPublicKey> keysToSign_;
+    cppbor::Array cborKeysToSign_;
+};
+
+/**
+ * Generate an empty certificate request in test mode, and decrypt and verify the structure and
+ * content.
+ */
+TEST_P(CertificateRequestTest, DISABLED_EmptyRequest_testMode) {
+    bool testMode = true;
+    bytevec keysToSignMac;
+    ProtectedData protectedData;
+    auto challenge = randomBytes(32);
+    auto status = provisionable_->generateCertificateRequest(testMode, {} /* keysToSign */,
+                                                             eekChain_.chain, challenge,
+                                                             &keysToSignMac, &protectedData);
+    ASSERT_TRUE(status.isOk()) << status.getMessage();
+
+    auto [parsedProtectedData, _, protDataErrMsg] = cppbor::parse(protectedData.protectedData);
+    ASSERT_TRUE(parsedProtectedData) << protDataErrMsg;
+    ASSERT_TRUE(parsedProtectedData->asArray());
+    ASSERT_EQ(parsedProtectedData->asArray()->size(), kCoseEncryptEntryCount);
+
+    auto senderPubkey = getSenderPubKeyFromCoseEncrypt(parsedProtectedData);
+    ASSERT_TRUE(senderPubkey) << senderPubkey.message();
+    EXPECT_EQ(senderPubkey->second, eekId_);
+
+    auto sessionKey = x25519_HKDF_DeriveKey(eekChain_.last_pubkey, eekChain_.last_privkey,
+                                            senderPubkey->first, false /* senderIsA */);
+    ASSERT_TRUE(sessionKey) << sessionKey.message();
+
+    auto protectedDataPayload =
+            decryptCoseEncrypt(*sessionKey, parsedProtectedData.get(), bytevec{} /* aad */);
+    ASSERT_TRUE(protectedDataPayload) << protectedDataPayload.message();
+
+    auto [parsedPayload, __, payloadErrMsg] = cppbor::parse(*protectedDataPayload);
+    ASSERT_TRUE(parsedPayload) << "Failed to parse payload: " << payloadErrMsg;
+    ASSERT_TRUE(parsedPayload->asArray());
+    EXPECT_EQ(parsedPayload->asArray()->size(), 2U);
+
+    auto& signedMac = parsedPayload->asArray()->get(0);
+    auto& bcc = parsedPayload->asArray()->get(1);
+    ASSERT_TRUE(signedMac && signedMac->asArray());
+    ASSERT_TRUE(bcc && bcc->asArray());
+
+    // BCC is [ pubkey, + BccEntry]
+    auto bccContents = validateBcc(bcc->asArray());
+    ASSERT_TRUE(bccContents) << "\n" << bccContents.message() << "\n" << prettyPrint(bcc.get());
+    ASSERT_GT(bccContents->size(), 0U);
+
+    auto& signingKey = bccContents->back().pubKey;
+    auto macKey = verifyAndParseCoseSign1(testMode, signedMac->asArray(), signingKey,
+                                          cppbor::Array()          // DeviceInfo
+                                                  .add(challenge)  //
+                                                  .add(cppbor::Map())
+                                                  .encode());
+    ASSERT_TRUE(macKey) << macKey.message();
+
+    auto coseMac0 = cppbor::Array()
+                            .add(cppbor::Map()  // protected
+                                         .add(ALGORITHM, HMAC_256)
+                                         .canonicalize()
+                                         .encode())
+                            .add(cppbor::Bstr())             // unprotected
+                            .add(cppbor::Array().encode())   // payload (keysToSign)
+                            .add(std::move(keysToSignMac));  // tag
+
+    auto macPayload = verifyAndParseCoseMac0(&coseMac0, *macKey);
+    ASSERT_TRUE(macPayload) << macPayload.message();
+}
+
+/**
+ * Generate an empty certificate request in prod mode.  Generation will fail because we don't have a
+ * valid GEEK.
+ *
+ * TODO(swillden): Get a valid GEEK and use it so the generation can succeed, though we won't be
+ * able to decrypt.
+ */
+TEST_P(CertificateRequestTest, DISABLED_EmptyRequest_prodMode) {
+    bool testMode = false;
+    bytevec keysToSignMac;
+    ProtectedData protectedData;
+    auto challenge = randomBytes(32);
+    auto status = provisionable_->generateCertificateRequest(testMode, {} /* keysToSign */,
+                                                             eekChain_.chain, challenge,
+                                                             &keysToSignMac, &protectedData);
+    ASSERT_FALSE(status.isOk());
+    ASSERT_EQ(status.getServiceSpecificError(), BnRemotelyProvisionedComponent::STATUS_INVALID_EEK);
+}
+
+/**
+ * Generate a non-empty certificate request in test mode.  Decrypt, parse and validate the contents.
+ */
+TEST_P(CertificateRequestTest, DISABLED_NonEmptyRequest_testMode) {
+    bool testMode = true;
+    generateKeys(testMode, 4 /* numKeys */);
+
+    bytevec keysToSignMac;
+    ProtectedData protectedData;
+    auto challenge = randomBytes(32);
+    auto status = provisionable_->generateCertificateRequest(
+            testMode, keysToSign_, eekChain_.chain, challenge, &keysToSignMac, &protectedData);
+    ASSERT_TRUE(status.isOk()) << status.getMessage();
+
+    auto [parsedProtectedData, _, protDataErrMsg] = cppbor::parse(protectedData.protectedData);
+    ASSERT_TRUE(parsedProtectedData) << protDataErrMsg;
+    ASSERT_TRUE(parsedProtectedData->asArray());
+    ASSERT_EQ(parsedProtectedData->asArray()->size(), kCoseEncryptEntryCount);
+
+    auto senderPubkey = getSenderPubKeyFromCoseEncrypt(parsedProtectedData);
+    ASSERT_TRUE(senderPubkey) << senderPubkey.message();
+    EXPECT_EQ(senderPubkey->second, eekId_);
+
+    auto sessionKey = x25519_HKDF_DeriveKey(eekChain_.last_pubkey, eekChain_.last_privkey,
+                                            senderPubkey->first, false /* senderIsA */);
+    ASSERT_TRUE(sessionKey) << sessionKey.message();
+
+    auto protectedDataPayload =
+            decryptCoseEncrypt(*sessionKey, parsedProtectedData.get(), bytevec{} /* aad */);
+    ASSERT_TRUE(protectedDataPayload) << protectedDataPayload.message();
+
+    auto [parsedPayload, __, payloadErrMsg] = cppbor::parse(*protectedDataPayload);
+    ASSERT_TRUE(parsedPayload) << "Failed to parse payload: " << payloadErrMsg;
+    ASSERT_TRUE(parsedPayload->asArray());
+    EXPECT_EQ(parsedPayload->asArray()->size(), 2U);
+
+    auto& signedMac = parsedPayload->asArray()->get(0);
+    auto& bcc = parsedPayload->asArray()->get(1);
+    ASSERT_TRUE(signedMac && signedMac->asArray());
+    ASSERT_TRUE(bcc);
+
+    auto bccContents = validateBcc(bcc->asArray());
+    ASSERT_TRUE(bccContents) << "\n" << prettyPrint(bcc.get());
+    ASSERT_GT(bccContents->size(), 0U);
+
+    auto& signingKey = bccContents->back().pubKey;
+    auto macKey = verifyAndParseCoseSign1(testMode, signedMac->asArray(), signingKey,
+                                          cppbor::Array()          // DeviceInfo
+                                                  .add(challenge)  //
+                                                  .add(cppbor::Array())
+                                                  .encode());
+    ASSERT_TRUE(macKey) << macKey.message();
+
+    auto coseMac0 = cppbor::Array()
+                            .add(cppbor::Map()  // protected
+                                         .add(ALGORITHM, HMAC_256)
+                                         .canonicalize()
+                                         .encode())
+                            .add(cppbor::Bstr())             // unprotected
+                            .add(cborKeysToSign_.encode())   // payload
+                            .add(std::move(keysToSignMac));  // tag
+
+    auto macPayload = verifyAndParseCoseMac0(&coseMac0, *macKey);
+    ASSERT_TRUE(macPayload) << macPayload.message();
+}
+
+/**
+ * Generate a non-empty certificate request in prod mode.  Must fail because we don't have a valid
+ * GEEK.
+ *
+ * TODO(swillden): Get a valid GEEK and use it so the generation can succeed, though we won't be
+ * able to decrypt.
+ */
+TEST_P(CertificateRequestTest, DISABLED_NonEmptyRequest_prodMode) {
+    bool testMode = false;
+    generateKeys(testMode, 4 /* numKeys */);
+
+    bytevec keysToSignMac;
+    ProtectedData protectedData;
+    auto challenge = randomBytes(32);
+    auto status = provisionable_->generateCertificateRequest(
+            testMode, keysToSign_, eekChain_.chain, challenge, &keysToSignMac, &protectedData);
+    ASSERT_FALSE(status.isOk());
+    ASSERT_EQ(status.getServiceSpecificError(), BnRemotelyProvisionedComponent::STATUS_INVALID_EEK);
+}
+
+/**
+ * Generate a non-empty certificate request in test mode, with prod keys.  Must fail with
+ * STATUS_PRODUCTION_KEY_IN_TEST_REQUEST.
+ */
+TEST_P(CertificateRequestTest, DISABLED_NonEmptyRequest_prodKeyInTestCert) {
+    generateKeys(false /* testMode */, 2 /* numKeys */);
+
+    bytevec keysToSignMac;
+    ProtectedData protectedData;
+    auto challenge = randomBytes(32);
+    auto status = provisionable_->generateCertificateRequest(true /* testMode */, keysToSign_,
+                                                             eekChain_.chain, challenge,
+                                                             &keysToSignMac, &protectedData);
+    ASSERT_FALSE(status.isOk());
+    ASSERT_EQ(status.getServiceSpecificError(),
+              BnRemotelyProvisionedComponent::STATUS_PRODUCTION_KEY_IN_TEST_REQUEST);
+}
+
+/**
+ * Generate a non-empty certificate request in prod mode, with test keys.  Must fail with
+ * STATUS_TEST_KEY_IN_PRODUCTION_REQUEST.
+ */
+TEST_P(CertificateRequestTest, DISABLED_NonEmptyRequest_testKeyInProdCert) {
+    generateKeys(true /* testMode */, 2 /* numKeys */);
+
+    bytevec keysToSignMac;
+    ProtectedData protectedData;
+    auto status = provisionable_->generateCertificateRequest(
+            false /* testMode */, keysToSign_, eekChain_.chain, randomBytes(32) /* challenge */,
+            &keysToSignMac, &protectedData);
+    ASSERT_FALSE(status.isOk());
+    ASSERT_EQ(status.getServiceSpecificError(),
+              BnRemotelyProvisionedComponent::STATUS_TEST_KEY_IN_PRODUCTION_REQUEST);
+}
+
+INSTANTIATE_REM_PROV_AIDL_TEST(CertificateRequestTest);
+
+}  // namespace aidl::android::hardware::security::keymint::test
diff --git a/security/keymint/support/Android.bp b/security/keymint/support/Android.bp
index fde6b57..0255874 100644
--- a/security/keymint/support/Android.bp
+++ b/security/keymint/support/Android.bp
@@ -37,3 +37,40 @@
         "libutils",
     ],
 }
+
+cc_library {
+    name: "libkeymint_remote_prov_support",
+    vendor_available: true,
+    srcs: [
+        "remote_prov_utils.cpp",
+    ],
+    export_include_dirs: [
+        "include",
+    ],
+    shared_libs: [
+        "libcppcose",
+        "libcppbor_external",
+        "libcrypto",
+    ],
+}
+
+cc_library {
+    name: "libcppcose",
+    vendor_available: true,
+    srcs: [
+        "cppcose.cpp",
+    ],
+    export_include_dirs: [
+        "include",
+    ],
+    shared_libs: [
+        "libbinder_ndk",
+        "libcppbor_external",
+        "libcrypto",
+        "liblog",
+    ],
+    static_libs: [
+        // TODO(swillden): Remove keymint NDK
+        "android.hardware.security.keymint-V1-ndk_platform",
+    ],
+}
diff --git a/security/keymint/support/authorization_set.cpp b/security/keymint/support/authorization_set.cpp
index 3d44dff..25eace3 100644
--- a/security/keymint/support/authorization_set.cpp
+++ b/security/keymint/support/authorization_set.cpp
@@ -191,6 +191,10 @@
     return Authorization(TAG_PURPOSE, KeyPurpose::DECRYPT);
 }
 
+AuthorizationSetBuilder& AuthorizationSetBuilder::AttestKey() {
+    return Authorization(TAG_PURPOSE, KeyPurpose::ATTEST_KEY);
+}
+
 AuthorizationSetBuilder& AuthorizationSetBuilder::NoDigestOrPadding() {
     Authorization(TAG_DIGEST, Digest::NONE);
     return Authorization(TAG_PADDING, PaddingMode::NONE);
@@ -243,4 +247,12 @@
     return *this;
 }
 
+AuthorizationSetBuilder& AuthorizationSetBuilder::SetDefaultValidity() {
+    // Per RFC 5280 4.1.2.5, an undefined expiration (not-after) field should be set to
+    // GeneralizedTime 999912312359559, which is 253402300799000 ms from Jan 1, 1970.
+    constexpr uint64_t kUndefinedExpirationDateTime = 253402300799000;
+    Authorization(TAG_CERTIFICATE_NOT_BEFORE, 0);
+    return Authorization(TAG_CERTIFICATE_NOT_AFTER, kUndefinedExpirationDateTime);
+}
+
 }  // namespace aidl::android::hardware::security::keymint
diff --git a/security/keymint/support/cppcose.cpp b/security/keymint/support/cppcose.cpp
new file mode 100644
index 0000000..c626ade
--- /dev/null
+++ b/security/keymint/support/cppcose.cpp
@@ -0,0 +1,467 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <cppcose/cppcose.h>
+
+#include <stdio.h>
+#include <iostream>
+
+#include <cppbor.h>
+#include <cppbor_parse.h>
+
+#include <openssl/err.h>
+
+namespace cppcose {
+
+namespace {
+
+ErrMsgOr<bssl::UniquePtr<EVP_CIPHER_CTX>> aesGcmInitAndProcessAad(const bytevec& key,
+                                                                  const bytevec& nonce,
+                                                                  const bytevec& aad,
+                                                                  bool encrypt) {
+    if (key.size() != kAesGcmKeySize) return "Invalid key size";
+
+    bssl::UniquePtr<EVP_CIPHER_CTX> ctx(EVP_CIPHER_CTX_new());
+    if (!ctx) return "Failed to allocate cipher context";
+
+    if (!EVP_CipherInit_ex(ctx.get(), EVP_aes_256_gcm(), nullptr /* engine */, key.data(),
+                           nonce.data(), encrypt ? 1 : 0)) {
+        return "Failed to initialize cipher";
+    }
+
+    int outlen;
+    if (!aad.empty() && !EVP_CipherUpdate(ctx.get(), nullptr /* out; null means AAD */, &outlen,
+                                          aad.data(), aad.size())) {
+        return "Failed to process AAD";
+    }
+
+    return std::move(ctx);
+}
+
+}  // namespace
+
+ErrMsgOr<bytevec> generateCoseMac0Mac(const bytevec& macKey, const bytevec& externalAad,
+                                      const bytevec& payload) {
+    auto macStructure = cppbor::Array()
+                                .add("MAC0")
+                                .add(cppbor::Map().add(ALGORITHM, HMAC_256).canonicalize().encode())
+                                .add(externalAad)
+                                .add(payload)
+                                .encode();
+
+    bytevec macTag(SHA256_DIGEST_LENGTH);
+    uint8_t* out = macTag.data();
+    unsigned int outLen;
+    out = HMAC(EVP_sha256(),                              //
+               macKey.data(), macKey.size(),              //
+               macStructure.data(), macStructure.size(),  //
+               out, &outLen);
+
+    assert(out != nullptr && outLen == macTag.size());
+    if (out == nullptr || outLen != macTag.size()) {
+        return "Error computing public key MAC";
+    }
+
+    return macTag;
+}
+
+ErrMsgOr<cppbor::Array> constructCoseMac0(const bytevec& macKey, const bytevec& externalAad,
+                                          const bytevec& payload) {
+    auto tag = generateCoseMac0Mac(macKey, externalAad, payload);
+    if (!tag) return tag.moveMessage();
+
+    return cppbor::Array()
+            .add(cppbor::Map().add(ALGORITHM, HMAC_256).canonicalize().encode())
+            .add(cppbor::Bstr() /* unprotected */)
+            .add(payload)
+            .add(tag.moveValue());
+}
+
+ErrMsgOr<bytevec /* payload */> parseCoseMac0(const cppbor::Item* macItem) {
+    auto mac = macItem ? macItem->asArray() : nullptr;
+    if (!mac || mac->size() != kCoseMac0EntryCount) {
+        return "Invalid COSE_Mac0";
+    }
+
+    auto protectedParms = mac->get(kCoseMac0ProtectedParams)->asBstr();
+    auto unprotectedParms = mac->get(kCoseMac0UnprotectedParams)->asBstr();
+    auto payload = mac->get(kCoseMac0Payload)->asBstr();
+    auto tag = mac->get(kCoseMac0Tag)->asBstr();
+    if (!protectedParms || !unprotectedParms || !payload || !tag) {
+        return "Invalid COSE_Mac0 contents";
+    }
+
+    return payload->value();
+}
+
+ErrMsgOr<bytevec /* payload */> verifyAndParseCoseMac0(const cppbor::Item* macItem,
+                                                       const bytevec& macKey) {
+    auto mac = macItem ? macItem->asArray() : nullptr;
+    if (!mac || mac->size() != kCoseMac0EntryCount) {
+        return "Invalid COSE_Mac0";
+    }
+
+    auto protectedParms = mac->get(kCoseMac0ProtectedParams)->asBstr();
+    auto unprotectedParms = mac->get(kCoseMac0UnprotectedParams)->asBstr();
+    auto payload = mac->get(kCoseMac0Payload)->asBstr();
+    auto tag = mac->get(kCoseMac0Tag)->asBstr();
+    if (!protectedParms || !unprotectedParms || !payload || !tag) {
+        return "Invalid COSE_Mac0 contents";
+    }
+
+    auto [protectedMap, _, errMsg] = cppbor::parse(protectedParms);
+    if (!protectedMap || !protectedMap->asMap()) {
+        return "Invalid Mac0 protected: " + errMsg;
+    }
+    auto& algo = protectedMap->asMap()->get(ALGORITHM);
+    if (!algo || !algo->asInt() || algo->asInt()->value() != HMAC_256) {
+        return "Unsupported Mac0 algorithm";
+    }
+
+    auto macTag = generateCoseMac0Mac(macKey, {} /* external_aad */, payload->value());
+    if (!macTag) return macTag.moveMessage();
+
+    if (macTag->size() != tag->value().size() ||
+        CRYPTO_memcmp(macTag->data(), tag->value().data(), macTag->size()) != 0) {
+        return "MAC tag mismatch";
+    }
+
+    return payload->value();
+}
+
+ErrMsgOr<bytevec> createCoseSign1Signature(const bytevec& key, const bytevec& protectedParams,
+                                           const bytevec& payload, const bytevec& aad) {
+    bytevec signatureInput = cppbor::Array()
+                                     .add("Signature1")  //
+                                     .add(protectedParams)
+                                     .add(aad)
+                                     .add(payload)
+                                     .encode();
+
+    if (key.size() != ED25519_PRIVATE_KEY_LEN) return "Invalid signing key";
+    bytevec signature(ED25519_SIGNATURE_LEN);
+    if (!ED25519_sign(signature.data(), signatureInput.data(), signatureInput.size(), key.data())) {
+        return "Signing failed";
+    }
+
+    return signature;
+}
+
+ErrMsgOr<cppbor::Array> constructCoseSign1(const bytevec& key, cppbor::Map protectedParams,
+                                           const bytevec& payload, const bytevec& aad) {
+    bytevec protParms = protectedParams.add(ALGORITHM, EDDSA).canonicalize().encode();
+    auto signature = createCoseSign1Signature(key, protParms, payload, aad);
+    if (!signature) return signature.moveMessage();
+
+    return cppbor::Array()
+            .add(protParms)
+            .add(bytevec{} /* unprotected parameters */)
+            .add(payload)
+            .add(*signature);
+}
+
+ErrMsgOr<cppbor::Array> constructCoseSign1(const bytevec& key, const bytevec& payload,
+                                           const bytevec& aad) {
+    return constructCoseSign1(key, {} /* protectedParams */, payload, aad);
+}
+
+ErrMsgOr<bytevec> verifyAndParseCoseSign1(bool ignoreSignature, const cppbor::Array* coseSign1,
+                                          const bytevec& signingCoseKey, const bytevec& aad) {
+    if (!coseSign1 || coseSign1->size() != kCoseSign1EntryCount) {
+        return "Invalid COSE_Sign1";
+    }
+
+    const cppbor::Bstr* protectedParams = coseSign1->get(kCoseSign1ProtectedParams)->asBstr();
+    const cppbor::Bstr* unprotectedParams = coseSign1->get(kCoseSign1UnprotectedParams)->asBstr();
+    const cppbor::Bstr* payload = coseSign1->get(kCoseSign1Payload)->asBstr();
+    const cppbor::Bstr* signature = coseSign1->get(kCoseSign1Signature)->asBstr();
+
+    if (!protectedParams || !unprotectedParams || !payload || !signature) {
+        return "Invalid COSE_Sign1";
+    }
+
+    auto [parsedProtParams, _, errMsg] = cppbor::parse(protectedParams);
+    if (!parsedProtParams) {
+        return errMsg + " when parsing protected params.";
+    }
+    if (!parsedProtParams->asMap()) {
+        return "Protected params must be a map";
+    }
+
+    auto& algorithm = parsedProtParams->asMap()->get(ALGORITHM);
+    if (!algorithm || !algorithm->asInt() || algorithm->asInt()->value() != EDDSA) {
+        return "Unsupported signature algorithm";
+    }
+
+    if (!ignoreSignature) {
+        bool selfSigned = signingCoseKey.empty();
+        auto key = CoseKey::parseEd25519(selfSigned ? payload->value() : signingCoseKey);
+        if (!key) return "Bad signing key: " + key.moveMessage();
+
+        bytevec signatureInput = cppbor::Array()
+                                         .add("Signature1")
+                                         .add(*protectedParams)
+                                         .add(aad)
+                                         .add(*payload)
+                                         .encode();
+
+        if (!ED25519_verify(signatureInput.data(), signatureInput.size(), signature->value().data(),
+                            key->getBstrValue(CoseKey::PUBKEY_X)->data())) {
+            return "Signature verification failed";
+        }
+    }
+
+    return payload->value();
+}
+
+ErrMsgOr<bytevec> createCoseEncryptCiphertext(const bytevec& key, const bytevec& nonce,
+                                              const bytevec& protectedParams,
+                                              const bytevec& plaintextPayload, const bytevec& aad) {
+    auto ciphertext = aesGcmEncrypt(key, nonce,
+                                    cppbor::Array()                // Enc strucure as AAD
+                                            .add("Encrypt")        // Context
+                                            .add(protectedParams)  // Protected
+                                            .add(aad)              // External AAD
+                                            .encode(),
+                                    plaintextPayload);
+
+    if (!ciphertext) return ciphertext.moveMessage();
+    return ciphertext.moveValue();
+}
+
+ErrMsgOr<cppbor::Array> constructCoseEncrypt(const bytevec& key, const bytevec& nonce,
+                                             const bytevec& plaintextPayload, const bytevec& aad,
+                                             cppbor::Array recipients) {
+    auto encryptProtectedHeader = cppbor::Map()  //
+                                          .add(ALGORITHM, AES_GCM_256)
+                                          .canonicalize()
+                                          .encode();
+
+    auto ciphertext =
+            createCoseEncryptCiphertext(key, nonce, encryptProtectedHeader, plaintextPayload, aad);
+    if (!ciphertext) return ciphertext.moveMessage();
+
+    return cppbor::Array()
+            .add(encryptProtectedHeader)                       // Protected
+            .add(cppbor::Map().add(IV, nonce).canonicalize())  // Unprotected
+            .add(*ciphertext)                                  // Payload
+            .add(std::move(recipients));
+}
+
+ErrMsgOr<std::pair<bytevec /* pubkey */, bytevec /* key ID */>> getSenderPubKeyFromCoseEncrypt(
+        const cppbor::Item* coseEncrypt) {
+    if (!coseEncrypt || !coseEncrypt->asArray() ||
+        coseEncrypt->asArray()->size() != kCoseEncryptEntryCount) {
+        return "Invalid COSE_Encrypt";
+    }
+
+    auto& recipients = coseEncrypt->asArray()->get(kCoseEncryptRecipients);
+    if (!recipients || !recipients->asArray() || recipients->asArray()->size() != 1) {
+        return "Invalid recipients list";
+    }
+
+    auto& recipient = recipients->asArray()->get(0);
+    if (!recipient || !recipient->asArray() || recipient->asArray()->size() != 3) {
+        return "Invalid COSE_recipient";
+    }
+
+    auto& ciphertext = recipient->asArray()->get(2);
+    if (!ciphertext->asSimple() || !ciphertext->asSimple()->asNull()) {
+        return "Unexpected value in recipients ciphertext field " +
+               cppbor::prettyPrint(ciphertext.get());
+    }
+
+    auto& protParms = recipient->asArray()->get(0);
+    if (!protParms || !protParms->asBstr()) return "Invalid protected params";
+    auto [parsedProtParms, _, errMsg] = cppbor::parse(protParms->asBstr());
+    if (!parsedProtParms) return "Failed to parse protected params: " + errMsg;
+    if (!parsedProtParms->asMap()) return "Invalid protected params";
+
+    auto& algorithm = parsedProtParms->asMap()->get(ALGORITHM);
+    if (!algorithm || !algorithm->asInt() || algorithm->asInt()->value() != ECDH_ES_HKDF_256) {
+        return "Invalid algorithm";
+    }
+
+    auto& unprotParms = recipient->asArray()->get(1);
+    if (!unprotParms || !unprotParms->asMap()) return "Invalid unprotected params";
+
+    auto& senderCoseKey = unprotParms->asMap()->get(COSE_KEY);
+    if (!senderCoseKey || !senderCoseKey->asMap()) return "Invalid sender COSE_Key";
+
+    auto& keyType = senderCoseKey->asMap()->get(CoseKey::KEY_TYPE);
+    if (!keyType || !keyType->asInt() || keyType->asInt()->value() != OCTET_KEY_PAIR) {
+        return "Invalid key type";
+    }
+
+    auto& curve = senderCoseKey->asMap()->get(CoseKey::CURVE);
+    if (!curve || !curve->asInt() || curve->asInt()->value() != X25519) {
+        return "Unsupported curve";
+    }
+
+    auto& pubkey = senderCoseKey->asMap()->get(CoseKey::PUBKEY_X);
+    if (!pubkey || !pubkey->asBstr() ||
+        pubkey->asBstr()->value().size() != X25519_PUBLIC_VALUE_LEN) {
+        return "Invalid X25519 public key";
+    }
+
+    auto& key_id = unprotParms->asMap()->get(KEY_ID);
+    if (key_id && key_id->asBstr()) {
+        return std::make_pair(pubkey->asBstr()->value(), key_id->asBstr()->value());
+    }
+
+    // If no key ID, just return an empty vector.
+    return std::make_pair(pubkey->asBstr()->value(), bytevec{});
+}
+
+ErrMsgOr<bytevec> decryptCoseEncrypt(const bytevec& key, const cppbor::Item* coseEncrypt,
+                                     const bytevec& external_aad) {
+    if (!coseEncrypt || !coseEncrypt->asArray() ||
+        coseEncrypt->asArray()->size() != kCoseEncryptEntryCount) {
+        return "Invalid COSE_Encrypt";
+    }
+
+    auto& protParms = coseEncrypt->asArray()->get(kCoseEncryptProtectedParams);
+    auto& unprotParms = coseEncrypt->asArray()->get(kCoseEncryptUnprotectedParams);
+    auto& ciphertext = coseEncrypt->asArray()->get(kCoseEncryptPayload);
+    auto& recipients = coseEncrypt->asArray()->get(kCoseEncryptRecipients);
+
+    if (!protParms || !protParms->asBstr() || !unprotParms || !ciphertext || !recipients) {
+        return "Invalid COSE_Encrypt";
+    }
+
+    auto [parsedProtParams, _, errMsg] = cppbor::parse(protParms->asBstr()->value());
+    if (!parsedProtParams) {
+        return errMsg + " when parsing protected params.";
+    }
+    if (!parsedProtParams->asMap()) {
+        return "Protected params must be a map";
+    }
+
+    auto& algorithm = parsedProtParams->asMap()->get(ALGORITHM);
+    if (!algorithm || !algorithm->asInt() || algorithm->asInt()->value() != AES_GCM_256) {
+        return "Unsupported encryption algorithm";
+    }
+
+    if (!unprotParms->asMap() || unprotParms->asMap()->size() != 1) {
+        return "Invalid unprotected params";
+    }
+
+    auto& nonce = unprotParms->asMap()->get(IV);
+    if (!nonce || !nonce->asBstr() || nonce->asBstr()->value().size() != kAesGcmNonceLength) {
+        return "Invalid nonce";
+    }
+
+    if (!ciphertext->asBstr()) return "Invalid ciphertext";
+
+    auto aad = cppbor::Array()                             // Enc strucure as AAD
+                       .add("Encrypt")                     // Context
+                       .add(protParms->asBstr()->value())  // Protected
+                       .add(external_aad)                  // External AAD
+                       .encode();
+
+    return aesGcmDecrypt(key, nonce->asBstr()->value(), aad, ciphertext->asBstr()->value());
+}
+
+ErrMsgOr<bytevec> x25519_HKDF_DeriveKey(const bytevec& pubKeyA, const bytevec& privKeyA,
+                                        const bytevec& pubKeyB, bool senderIsA) {
+    bytevec rawSharedKey(X25519_SHARED_KEY_LEN);
+    if (!::X25519(rawSharedKey.data(), privKeyA.data(), pubKeyB.data())) {
+        return "ECDH operation failed";
+    }
+
+    bytevec kdfContext = cppbor::Array()
+                                 .add(AES_GCM_256)
+                                 .add(cppbor::Array()  // Sender Info
+                                              .add(cppbor::Bstr("client"))
+                                              .add(bytevec{} /* nonce */)
+                                              .add(senderIsA ? pubKeyA : pubKeyB))
+                                 .add(cppbor::Array()  // Recipient Info
+                                              .add(cppbor::Bstr("server"))
+                                              .add(bytevec{} /* nonce */)
+                                              .add(senderIsA ? pubKeyB : pubKeyA))
+                                 .add(cppbor::Array()           // SuppPubInfo
+                                              .add(128)         // output key length
+                                              .add(bytevec{}))  // protected
+                                 .encode();
+
+    bytevec retval(SHA256_DIGEST_LENGTH);
+    bytevec salt{};
+    if (!HKDF(retval.data(), retval.size(),              //
+              EVP_sha256(),                              //
+              rawSharedKey.data(), rawSharedKey.size(),  //
+              salt.data(), salt.size(),                  //
+              kdfContext.data(), kdfContext.size())) {
+        return "ECDH HKDF failed";
+    }
+
+    return retval;
+}
+
+ErrMsgOr<bytevec> aesGcmEncrypt(const bytevec& key, const bytevec& nonce, const bytevec& aad,
+                                const bytevec& plaintext) {
+    auto ctx = aesGcmInitAndProcessAad(key, nonce, aad, true /* encrypt */);
+    if (!ctx) return ctx.moveMessage();
+
+    bytevec ciphertext(plaintext.size() + kAesGcmTagSize);
+    int outlen;
+    if (!EVP_CipherUpdate(ctx->get(), ciphertext.data(), &outlen, plaintext.data(),
+                          plaintext.size())) {
+        return "Failed to encrypt plaintext";
+    }
+    assert(plaintext.size() == outlen);
+
+    if (!EVP_CipherFinal_ex(ctx->get(), ciphertext.data() + outlen, &outlen)) {
+        return "Failed to finalize encryption";
+    }
+    assert(outlen == 0);
+
+    if (!EVP_CIPHER_CTX_ctrl(ctx->get(), EVP_CTRL_GCM_GET_TAG, kAesGcmTagSize,
+                             ciphertext.data() + plaintext.size())) {
+        return "Failed to retrieve tag";
+    }
+
+    return ciphertext;
+}
+
+ErrMsgOr<bytevec> aesGcmDecrypt(const bytevec& key, const bytevec& nonce, const bytevec& aad,
+                                const bytevec& ciphertextWithTag) {
+    auto ctx = aesGcmInitAndProcessAad(key, nonce, aad, false /* encrypt */);
+    if (!ctx) return ctx.moveMessage();
+
+    if (ciphertextWithTag.size() < kAesGcmTagSize) return "Missing tag";
+
+    bytevec plaintext(ciphertextWithTag.size() - kAesGcmTagSize);
+    int outlen;
+    if (!EVP_CipherUpdate(ctx->get(), plaintext.data(), &outlen, ciphertextWithTag.data(),
+                          ciphertextWithTag.size() - kAesGcmTagSize)) {
+        return "Failed to decrypt plaintext";
+    }
+    assert(plaintext.size() == outlen);
+
+    bytevec tag(ciphertextWithTag.end() - kAesGcmTagSize, ciphertextWithTag.end());
+    if (!EVP_CIPHER_CTX_ctrl(ctx->get(), EVP_CTRL_GCM_SET_TAG, kAesGcmTagSize, tag.data())) {
+        return "Failed to set tag: " + std::to_string(ERR_peek_last_error());
+    }
+
+    if (!EVP_CipherFinal_ex(ctx->get(), nullptr, &outlen)) {
+        return "Failed to finalize encryption";
+    }
+    assert(outlen == 0);
+
+    return plaintext;
+}
+
+}  // namespace cppcose
diff --git a/security/keymint/support/include/cppcose/cppcose.h b/security/keymint/support/include/cppcose/cppcose.h
new file mode 100644
index 0000000..a936bfd
--- /dev/null
+++ b/security/keymint/support/include/cppcose/cppcose.h
@@ -0,0 +1,288 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+#include <cppbor.h>
+#include <cppbor_parse.h>
+
+#include <openssl/cipher.h>
+#include <openssl/curve25519.h>
+#include <openssl/digest.h>
+#include <openssl/hkdf.h>
+#include <openssl/hmac.h>
+#include <openssl/mem.h>
+#include <openssl/sha.h>
+
+namespace cppcose {
+
+using bytevec = std::vector<uint8_t>;
+
+constexpr int kCoseSign1EntryCount = 4;
+constexpr int kCoseSign1ProtectedParams = 0;
+constexpr int kCoseSign1UnprotectedParams = 1;
+constexpr int kCoseSign1Payload = 2;
+constexpr int kCoseSign1Signature = 3;
+
+constexpr int kCoseMac0EntryCount = 4;
+constexpr int kCoseMac0ProtectedParams = 0;
+constexpr int kCoseMac0UnprotectedParams = 1;
+constexpr int kCoseMac0Payload = 2;
+constexpr int kCoseMac0Tag = 3;
+
+constexpr int kCoseEncryptEntryCount = 4;
+constexpr int kCoseEncryptProtectedParams = 0;
+constexpr int kCoseEncryptUnprotectedParams = 1;
+constexpr int kCoseEncryptPayload = 2;
+constexpr int kCoseEncryptRecipients = 3;
+
+enum Label : int {
+    ALGORITHM = 1,
+    KEY_ID = 4,
+    IV = 5,
+    COSE_KEY = -1,
+};
+
+enum CoseKeyAlgorithm : int {
+    AES_GCM_256 = 3,
+    HMAC_256 = 5,
+    ES256 = -7,  // ECDSA with SHA-256
+    EDDSA = -8,
+    ECDH_ES_HKDF_256 = -25,
+};
+
+enum CoseKeyCurve : int { P256 = 1, X25519 = 4, ED25519 = 6 };
+enum CoseKeyType : int { OCTET_KEY_PAIR = 1, EC2 = 2, SYMMETRIC_KEY = 4 };
+enum CoseKeyOps : int { SIGN = 1, VERIFY = 2, ENCRYPT = 3, DECRYPT = 4 };
+
+constexpr int kAesGcmNonceLength = 12;
+constexpr int kAesGcmTagSize = 16;
+constexpr int kAesGcmKeySize = 32;
+
+template <typename T>
+class ErrMsgOr {
+  public:
+    ErrMsgOr(std::string errMsg) : errMsg_(std::move(errMsg)) {}
+    ErrMsgOr(const char* errMsg) : errMsg_(errMsg) {}
+    ErrMsgOr(T val) : value_(std::move(val)) {}
+
+    operator bool() const { return value_.has_value(); }
+
+    T* operator->() & {
+        assert(value_);
+        return &value_.value();
+    }
+    T& operator*() & {
+        assert(value_);
+        return value_.value();
+    };
+    T&& operator*() && {
+        assert(value_);
+        return std::move(value_).value();
+    };
+
+    const std::string& message() { return errMsg_; }
+    std::string moveMessage() { return std::move(errMsg_); }
+
+    T moveValue() {
+        assert(value_);
+        return std::move(value_).value();
+    }
+
+  private:
+    std::string errMsg_;
+    std::optional<T> value_;
+};
+
+class CoseKey {
+  public:
+    CoseKey() {}
+    CoseKey(const CoseKey&) = delete;
+    CoseKey(CoseKey&&) = default;
+
+    enum Label : int {
+        KEY_TYPE = 1,
+        KEY_ID = 2,
+        ALGORITHM = 3,
+        KEY_OPS = 4,
+        CURVE = -1,
+        PUBKEY_X = -2,
+        PUBKEY_Y = -3,
+        PRIVATE_KEY = -4,
+        TEST_KEY = -70000  // Application-defined
+    };
+
+    static ErrMsgOr<CoseKey> parse(const bytevec& coseKey) {
+        auto [parsedKey, _, errMsg] = cppbor::parse(coseKey);
+        if (!parsedKey) return errMsg + " when parsing key";
+        if (!parsedKey->asMap()) return "CoseKey must be a map";
+        return CoseKey(static_cast<cppbor::Map*>(parsedKey.release()));
+    }
+
+    static ErrMsgOr<CoseKey> parse(const bytevec& coseKey, CoseKeyType expectedKeyType,
+                                   CoseKeyAlgorithm expectedAlgorithm, CoseKeyCurve expectedCurve) {
+        auto key = parse(coseKey);
+        if (!key) return key;
+
+        if (!key->checkIntValue(CoseKey::KEY_TYPE, expectedKeyType) ||
+            !key->checkIntValue(CoseKey::ALGORITHM, expectedAlgorithm) ||
+            !key->checkIntValue(CoseKey::CURVE, expectedCurve)) {
+            return "Unexpected key type:";
+        }
+
+        return key;
+    }
+
+    static ErrMsgOr<CoseKey> parseEd25519(const bytevec& coseKey) {
+        auto key = parse(coseKey, OCTET_KEY_PAIR, EDDSA, ED25519);
+        if (!key) return key;
+
+        auto& pubkey = key->getMap().get(PUBKEY_X);
+        if (!pubkey || !pubkey->asBstr() ||
+            pubkey->asBstr()->value().size() != ED25519_PUBLIC_KEY_LEN) {
+            return "Invalid Ed25519 public key";
+        }
+
+        return key;
+    }
+
+    static ErrMsgOr<CoseKey> parseX25519(const bytevec& coseKey, bool requireKid) {
+        auto key = parse(coseKey, OCTET_KEY_PAIR, ECDH_ES_HKDF_256, X25519);
+        if (!key) return key;
+
+        auto& pubkey = key->getMap().get(PUBKEY_X);
+        if (!pubkey || !pubkey->asBstr() ||
+            pubkey->asBstr()->value().size() != X25519_PUBLIC_VALUE_LEN) {
+            return "Invalid X25519 public key";
+        }
+
+        auto& kid = key->getMap().get(KEY_ID);
+        if (requireKid && (!kid || !kid->asBstr())) {
+            return "Missing KID";
+        }
+
+        return key;
+    }
+
+    static ErrMsgOr<CoseKey> parseP256(const bytevec& coseKey) {
+        auto key = parse(coseKey, EC2, ES256, P256);
+        if (!key) return key;
+
+        auto& pubkey_x = key->getMap().get(PUBKEY_X);
+        auto& pubkey_y = key->getMap().get(PUBKEY_Y);
+        if (!pubkey_x || !pubkey_y || !pubkey_x->asBstr() || !pubkey_y->asBstr() ||
+            pubkey_x->asBstr()->value().size() != 32 || pubkey_y->asBstr()->value().size() != 32) {
+            return "Invalid P256 public key";
+        }
+
+        return key;
+    }
+
+    std::optional<int> getIntValue(Label label) {
+        const auto& value = key_->get(label);
+        if (!value || !value->asInt()) return {};
+        return value->asInt()->value();
+    }
+
+    std::optional<bytevec> getBstrValue(Label label) {
+        const auto& value = key_->get(label);
+        if (!value || !value->asBstr()) return {};
+        return value->asBstr()->value();
+    }
+
+    const cppbor::Map& getMap() const { return *key_; }
+    cppbor::Map&& moveMap() { return std::move(*key_); }
+
+    bool checkIntValue(Label label, int expectedValue) {
+        const auto& value = key_->get(label);
+        return value && value->asInt() && value->asInt()->value() == expectedValue;
+    }
+
+    void add(Label label, int value) { key_->add(label, value); }
+    void add(Label label, bytevec value) { key_->add(label, std::move(value)); }
+
+    bytevec encode() { return key_->canonicalize().encode(); }
+
+  private:
+    CoseKey(cppbor::Map* parsedKey) : key_(parsedKey) {}
+
+    // This is the full parsed key structure.
+    std::unique_ptr<cppbor::Map> key_;
+};
+
+ErrMsgOr<bytevec> generateCoseMac0Mac(const bytevec& macKey, const bytevec& externalAad,
+                                      const bytevec& payload);
+ErrMsgOr<cppbor::Array> constructCoseMac0(const bytevec& macKey, const bytevec& externalAad,
+                                          const bytevec& payload);
+ErrMsgOr<bytevec /* payload */> parseCoseMac0(const cppbor::Item* macItem);
+ErrMsgOr<bytevec /* payload */> verifyAndParseCoseMac0(const cppbor::Item* macItem,
+                                                       const bytevec& macKey);
+
+ErrMsgOr<bytevec> createCoseSign1Signature(const bytevec& key, const bytevec& protectedParams,
+                                           const bytevec& payload, const bytevec& aad);
+ErrMsgOr<cppbor::Array> constructCoseSign1(const bytevec& key, const bytevec& payload,
+                                           const bytevec& aad);
+ErrMsgOr<cppbor::Array> constructCoseSign1(const bytevec& key, cppbor::Map extraProtectedFields,
+                                           const bytevec& payload, const bytevec& aad);
+/**
+ * Verify and parse a COSE_Sign1 message, returning the payload.
+ *
+ * @param ignoreSignature indicates whether signature verification should be skipped.  If true, no
+ *        verification of the signature will be done.
+ *
+ * @param coseSign1 is the COSE_Sign1 to verify and parse.
+ *
+ * @param signingCoseKey is a CBOR-encoded COSE_Key to use to verify the signature.  The bytevec may
+ *        be empty, in which case the function assumes that coseSign1's payload is the COSE_Key to
+ *        use, i.e. that coseSign1 is a self-signed "certificate".
+ */
+ErrMsgOr<bytevec /* payload */> verifyAndParseCoseSign1(bool ignoreSignature,
+                                                        const cppbor::Array* coseSign1,
+                                                        const bytevec& signingCoseKey,
+                                                        const bytevec& aad);
+
+ErrMsgOr<bytevec> createCoseEncryptCiphertext(const bytevec& key, const bytevec& nonce,
+                                              const bytevec& protectedParams, const bytevec& aad);
+ErrMsgOr<cppbor::Array> constructCoseEncrypt(const bytevec& key, const bytevec& nonce,
+                                             const bytevec& plaintextPayload, const bytevec& aad,
+                                             cppbor::Array recipients);
+ErrMsgOr<std::pair<bytevec /* pubkey */, bytevec /* key ID */>> getSenderPubKeyFromCoseEncrypt(
+        const cppbor::Item* encryptItem);
+inline ErrMsgOr<std::pair<bytevec /* pubkey */, bytevec /* key ID */>>
+getSenderPubKeyFromCoseEncrypt(const std::unique_ptr<cppbor::Item>& encryptItem) {
+    return getSenderPubKeyFromCoseEncrypt(encryptItem.get());
+}
+
+ErrMsgOr<bytevec /* plaintextPayload */> decryptCoseEncrypt(const bytevec& key,
+                                                            const cppbor::Item* encryptItem,
+                                                            const bytevec& aad);
+
+ErrMsgOr<bytevec> x25519_HKDF_DeriveKey(const bytevec& senderPubKey, const bytevec& senderPrivKey,
+                                        const bytevec& recipientPubKey, bool senderIsA);
+
+ErrMsgOr<bytevec /* ciphertextWithTag */> aesGcmEncrypt(const bytevec& key, const bytevec& nonce,
+                                                        const bytevec& aad,
+                                                        const bytevec& plaintext);
+ErrMsgOr<bytevec /* plaintext */> aesGcmDecrypt(const bytevec& key, const bytevec& nonce,
+                                                const bytevec& aad,
+                                                const bytevec& ciphertextWithTag);
+
+}  // namespace cppcose
diff --git a/security/keymint/support/include/keymint_support/authorization_set.h b/security/keymint/support/include/keymint_support/authorization_set.h
index 1407c5f..ca51b08 100644
--- a/security/keymint/support/include/keymint_support/authorization_set.h
+++ b/security/keymint/support/include/keymint_support/authorization_set.h
@@ -288,6 +288,7 @@
 
     AuthorizationSetBuilder& SigningKey();
     AuthorizationSetBuilder& EncryptionKey();
+    AuthorizationSetBuilder& AttestKey();
 
     AuthorizationSetBuilder& NoDigestOrPadding();
 
@@ -300,6 +301,8 @@
     AuthorizationSetBuilder& Digest(std::vector<Digest> digests);
     AuthorizationSetBuilder& Padding(std::initializer_list<PaddingMode> paddings);
 
+    AuthorizationSetBuilder& SetDefaultValidity();
+
     AuthorizationSetBuilder& AttestationChallenge(const std::string& challenge) {
         return Authorization(TAG_ATTESTATION_CHALLENGE, challenge);
     }
diff --git a/security/keymint/support/include/keymint_support/openssl_utils.h b/security/keymint/support/include/keymint_support/openssl_utils.h
index c3bc60b..a0212aa 100644
--- a/security/keymint/support/include/keymint_support/openssl_utils.h
+++ b/security/keymint/support/include/keymint_support/openssl_utils.h
@@ -34,13 +34,14 @@
     typedef std::unique_ptr<type, UniquePtrDeleter<type, type##_free>> type##_Ptr;
 
 MAKE_OPENSSL_PTR_TYPE(ASN1_OBJECT)
-MAKE_OPENSSL_PTR_TYPE(EC_KEY)
+MAKE_OPENSSL_PTR_TYPE(BN_CTX)
 MAKE_OPENSSL_PTR_TYPE(EC_GROUP)
+MAKE_OPENSSL_PTR_TYPE(EC_KEY)
 MAKE_OPENSSL_PTR_TYPE(EVP_PKEY)
 MAKE_OPENSSL_PTR_TYPE(EVP_PKEY_CTX)
 MAKE_OPENSSL_PTR_TYPE(RSA)
 MAKE_OPENSSL_PTR_TYPE(X509)
-MAKE_OPENSSL_PTR_TYPE(BN_CTX)
+MAKE_OPENSSL_PTR_TYPE(X509_NAME)
 
 typedef std::unique_ptr<BIGNUM, UniquePtrDeleter<BIGNUM, BN_free>> BIGNUM_Ptr;
 
diff --git a/security/keymint/support/include/remote_prov/remote_prov_utils.h b/security/keymint/support/include/remote_prov/remote_prov_utils.h
new file mode 100644
index 0000000..5e205a2
--- /dev/null
+++ b/security/keymint/support/include/remote_prov/remote_prov_utils.h
@@ -0,0 +1,60 @@
+/*
+ * Copyright (c) 2019, The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include <vector>
+
+#include <cppcose/cppcose.h>
+
+namespace aidl::android::hardware::security::keymint::remote_prov {
+
+using bytevec = std::vector<uint8_t>;
+using namespace cppcose;
+
+extern bytevec kTestMacKey;
+
+/**
+ * Generates random bytes.
+ */
+bytevec randomBytes(size_t numBytes);
+
+struct EekChain {
+    bytevec chain;
+    bytevec last_pubkey;
+    bytevec last_privkey;
+};
+
+/**
+ * Generates an X25518 EEK with the specified eekId and an Ed25519 chain of the
+ * specified length. All keys are generated randomly.
+ */
+ErrMsgOr<EekChain> generateEekChain(size_t length, const bytevec& eekId);
+
+struct BccEntryData {
+    bytevec pubKey;
+};
+
+/**
+ * Validates the provided CBOR-encoded BCC, returning a vector of BccEntryData
+ * structs containing the BCC entry contents.  If an entry contains no firmware
+ * digest, the corresponding BccEntryData.firmwareDigest will have length zero
+ * (there's no way to distinguish between an empty and missing firmware digest,
+ * which seems fine).
+ */
+ErrMsgOr<std::vector<BccEntryData>> validateBcc(const cppbor::Array* bcc);
+
+}  // namespace aidl::android::hardware::security::keymint::remote_prov
diff --git a/security/keymint/support/remote_prov_utils.cpp b/security/keymint/support/remote_prov_utils.cpp
new file mode 100644
index 0000000..111cb30
--- /dev/null
+++ b/security/keymint/support/remote_prov_utils.cpp
@@ -0,0 +1,169 @@
+/*
+ * Copyright (c) 2019, The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <remote_prov/remote_prov_utils.h>
+
+#include <openssl/rand.h>
+
+#include <cppbor.h>
+
+namespace aidl::android::hardware::security::keymint::remote_prov {
+
+bytevec kTestMacKey(32 /* count */, 0 /* byte value */);
+
+bytevec randomBytes(size_t numBytes) {
+    bytevec retval(numBytes);
+    RAND_bytes(retval.data(), numBytes);
+    return retval;
+}
+
+ErrMsgOr<EekChain> generateEekChain(size_t length, const bytevec& eekId) {
+    auto eekChain = cppbor::Array();
+
+    bytevec prev_priv_key;
+    for (size_t i = 0; i < length - 1; ++i) {
+        bytevec pub_key(ED25519_PUBLIC_KEY_LEN);
+        bytevec priv_key(ED25519_PRIVATE_KEY_LEN);
+
+        ED25519_keypair(pub_key.data(), priv_key.data());
+
+        // The first signing key is self-signed.
+        if (prev_priv_key.empty()) prev_priv_key = priv_key;
+
+        auto coseSign1 = constructCoseSign1(prev_priv_key,
+                                            cppbor::Map() /* payload CoseKey */
+                                                    .add(CoseKey::KEY_TYPE, OCTET_KEY_PAIR)
+                                                    .add(CoseKey::ALGORITHM, EDDSA)
+                                                    .add(CoseKey::CURVE, ED25519)
+                                                    .add(CoseKey::PUBKEY_X, pub_key)
+                                                    .canonicalize()
+                                                    .encode(),
+                                            {} /* AAD */);
+        if (!coseSign1) return coseSign1.moveMessage();
+        eekChain.add(coseSign1.moveValue());
+    }
+
+    bytevec pub_key(X25519_PUBLIC_VALUE_LEN);
+    bytevec priv_key(X25519_PRIVATE_KEY_LEN);
+    X25519_keypair(pub_key.data(), priv_key.data());
+
+    auto coseSign1 = constructCoseSign1(prev_priv_key,
+                                        cppbor::Map() /* payload CoseKey */
+                                                .add(CoseKey::KEY_TYPE, OCTET_KEY_PAIR)
+                                                .add(CoseKey::KEY_ID, eekId)
+                                                .add(CoseKey::ALGORITHM, ECDH_ES_HKDF_256)
+                                                .add(CoseKey::CURVE, cppcose::X25519)
+                                                .add(CoseKey::PUBKEY_X, pub_key)
+                                                .canonicalize()
+                                                .encode(),
+                                        {} /* AAD */);
+    if (!coseSign1) return coseSign1.moveMessage();
+    eekChain.add(coseSign1.moveValue());
+
+    return EekChain{eekChain.encode(), pub_key, priv_key};
+}
+
+ErrMsgOr<bytevec> verifyAndParseCoseSign1Cwt(bool ignoreSignature, const cppbor::Array* coseSign1,
+                                             const bytevec& signingCoseKey, const bytevec& aad) {
+    if (!coseSign1 || coseSign1->size() != kCoseSign1EntryCount) {
+        return "Invalid COSE_Sign1";
+    }
+
+    const cppbor::Bstr* protectedParams = coseSign1->get(kCoseSign1ProtectedParams)->asBstr();
+    const cppbor::Bstr* unprotectedParams = coseSign1->get(kCoseSign1UnprotectedParams)->asBstr();
+    const cppbor::Bstr* payload = coseSign1->get(kCoseSign1Payload)->asBstr();
+    const cppbor::Bstr* signature = coseSign1->get(kCoseSign1Signature)->asBstr();
+
+    if (!protectedParams || !unprotectedParams || !payload || !signature) {
+        return "Invalid COSE_Sign1";
+    }
+
+    auto [parsedProtParams, _, errMsg] = cppbor::parse(protectedParams);
+    if (!parsedProtParams) {
+        return errMsg + " when parsing protected params.";
+    }
+    if (!parsedProtParams->asMap()) {
+        return "Protected params must be a map";
+    }
+
+    auto& algorithm = parsedProtParams->asMap()->get(ALGORITHM);
+    if (!algorithm || !algorithm->asInt() || algorithm->asInt()->value() != EDDSA) {
+        return "Unsupported signature algorithm";
+    }
+
+    // TODO(jbires): Handle CWTs as the CoseSign1 payload in a less hacky way. Since the CWT payload
+    //               is extremely remote provisioning specific, probably just make a separate
+    //               function there.
+    auto [parsedPayload, __, payloadErrMsg] = cppbor::parse(payload);
+    if (!parsedPayload) return payloadErrMsg + " when parsing key";
+    if (!parsedPayload->asMap()) return "CWT must be a map";
+    auto serializedKey = parsedPayload->asMap()->get(-4670552)->clone();
+    if (!serializedKey || !serializedKey->asBstr()) return "Could not find key entry";
+
+    if (!ignoreSignature) {
+        bool selfSigned = signingCoseKey.empty();
+        auto key = CoseKey::parseEd25519(selfSigned ? serializedKey->asBstr()->value()
+                                                    : signingCoseKey);
+        if (!key) return "Bad signing key: " + key.moveMessage();
+
+        bytevec signatureInput = cppbor::Array()
+                                         .add("Signature1")
+                                         .add(*protectedParams)
+                                         .add(aad)
+                                         .add(*payload)
+                                         .encode();
+
+        if (!ED25519_verify(signatureInput.data(), signatureInput.size(), signature->value().data(),
+                            key->getBstrValue(CoseKey::PUBKEY_X)->data())) {
+            return "Signature verification failed";
+        }
+    }
+
+    return serializedKey->asBstr()->value();
+}
+ErrMsgOr<std::vector<BccEntryData>> validateBcc(const cppbor::Array* bcc) {
+    if (!bcc || bcc->size() == 0) return "Invalid BCC";
+
+    std::vector<BccEntryData> result;
+
+    bytevec prevKey;
+    // TODO(jbires): Actually process the pubKey at the start of the new bcc entry
+    for (size_t i = 1; i < bcc->size(); ++i) {
+        const cppbor::Array* entry = bcc->get(i)->asArray();
+        if (!entry || entry->size() != kCoseSign1EntryCount) {
+            return "Invalid BCC entry " + std::to_string(i) + ": " + prettyPrint(entry);
+        }
+        auto payload = verifyAndParseCoseSign1Cwt(false /* ignoreSignature */, entry,
+                                                  std::move(prevKey), bytevec{} /* AAD */);
+        if (!payload) {
+            return "Failed to verify entry " + std::to_string(i) + ": " + payload.moveMessage();
+        }
+
+        auto& certProtParms = entry->get(kCoseSign1ProtectedParams);
+        if (!certProtParms || !certProtParms->asBstr()) return "Invalid prot params";
+        auto [parsedProtParms, _, errMsg] = cppbor::parse(certProtParms->asBstr()->value());
+        if (!parsedProtParms || !parsedProtParms->asMap()) return "Invalid prot params";
+
+        result.push_back(BccEntryData{*payload});
+
+        // This entry's public key is the signing key for the next entry.
+        prevKey = payload.moveValue();
+    }
+
+    return result;
+}
+
+}  // namespace aidl::android::hardware::security::keymint::remote_prov
diff --git a/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/ISecureClock.aidl b/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/ISecureClock.aidl
index c16b312..3778897 100644
--- a/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/ISecureClock.aidl
+++ b/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/ISecureClock.aidl
@@ -1,4 +1,17 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
 // THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
 ///////////////////////////////////////////////////////////////////////////////
 
@@ -20,5 +33,5 @@
 @VintfStability
 interface ISecureClock {
   android.hardware.security.secureclock.TimeStampToken generateTimeStamp(in long challenge);
-  const String TIME_STAMP_MAC_LABEL = "Time Verification";
+  const String TIME_STAMP_MAC_LABEL = "Auth Verification";
 }
diff --git a/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/TimeStampToken.aidl b/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/TimeStampToken.aidl
index 21eeb74..00a8bb2 100644
--- a/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/TimeStampToken.aidl
+++ b/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/TimeStampToken.aidl
@@ -1,4 +1,18 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
 // THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
 ///////////////////////////////////////////////////////////////////////////////
 
diff --git a/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/Timestamp.aidl b/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/Timestamp.aidl
index f01fdc7..bebeb5c 100644
--- a/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/Timestamp.aidl
+++ b/security/secureclock/aidl/aidl_api/android.hardware.security.secureclock/current/android/hardware/security/secureclock/Timestamp.aidl
@@ -1,4 +1,18 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * Copyright 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *////////////////////////////////////////////////////////////////////////////////
 // THIS FILE IS IMMUTABLE. DO NOT EDIT IN ANY CASE.                          //
 ///////////////////////////////////////////////////////////////////////////////
 
diff --git a/security/secureclock/aidl/android/hardware/security/secureclock/ISecureClock.aidl b/security/secureclock/aidl/android/hardware/security/secureclock/ISecureClock.aidl
index 7d416dd..577dd8f 100644
--- a/security/secureclock/aidl/android/hardware/security/secureclock/ISecureClock.aidl
+++ b/security/secureclock/aidl/android/hardware/security/secureclock/ISecureClock.aidl
@@ -33,7 +33,7 @@
      * String used as context in the HMAC computation signing the generated time stamp.
      * See TimeStampToken.mac for details.
      */
-    const String TIME_STAMP_MAC_LABEL = "Time Verification";
+    const String TIME_STAMP_MAC_LABEL = "Auth Verification";
 
     /**
      * Generates an authenticated timestamp.
diff --git a/security/secureclock/aidl/android/hardware/security/secureclock/TimeStampToken.aidl b/security/secureclock/aidl/android/hardware/security/secureclock/TimeStampToken.aidl
index 3fb5860..dd95732 100644
--- a/security/secureclock/aidl/android/hardware/security/secureclock/TimeStampToken.aidl
+++ b/security/secureclock/aidl/android/hardware/security/secureclock/TimeStampToken.aidl
@@ -39,18 +39,20 @@
      * 32-byte HMAC-SHA256 of the above values, computed as:
      *
      *    HMAC(H,
-     *         ISecureClock.TIME_STAMP_MAC_LABEL || challenge || timestamp)
+     *         ISecureClock.TIME_STAMP_MAC_LABEL || challenge || timestamp || securityLevel )
      *
      * where:
      *
      *   ``ISecureClock.TIME_STAMP_MAC_LABEL'' is a sting constant defined in ISecureClock.aidl.
      *
-     *   ``H'' is the shared HMAC key (see computeSharedHmac() in ISharedHmacSecret).
+     *   ``H'' is the shared HMAC key (see computeSharedHmac() in ISharedSecret).
      *
      *   ``||'' represents concatenation
      *
      * The representation of challenge and timestamp is as 64-bit unsigned integers in big-endian
-     * order.  securityLevel is represented as a 32-bit unsigned integer in big-endian order.
+     * order. SecurityLevel is represented as a 32-bit unsigned integer in big-endian order as
+     * described in android.hardware.security.keymint.SecurityLevel. It represents the security
+     * level of the secure clock environment.
      */
     byte[] mac;
 }
diff --git a/security/secureclock/aidl/vts/functional/Android.bp b/security/secureclock/aidl/vts/functional/Android.bp
new file mode 100644
index 0000000..1619eab
--- /dev/null
+++ b/security/secureclock/aidl/vts/functional/Android.bp
@@ -0,0 +1,43 @@
+//
+// Copyright (C) 2020 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_test {
+    name: "VtsAidlSecureClockTargetTest",
+    defaults: [
+        "VtsHalTargetTestDefaults",
+        "use_libaidlvintf_gtest_helper_static",
+    ],
+    cflags: [
+        "-Wall",
+        "-Wextra",
+    ],
+    srcs: [
+        "SecureClockAidlTest.cpp",
+    ],
+    shared_libs: [
+        "libbinder_ndk",
+        "libcrypto",
+        "libkeymint",
+    ],
+    static_libs: [
+        "android.hardware.security.keymint-V1-ndk_platform",
+        "android.hardware.security.secureclock-V1-ndk_platform",
+    ],
+    test_suites: [
+        "general-tests",
+        "vts",
+    ],
+}
diff --git a/security/secureclock/aidl/vts/functional/AndroidTest.xml b/security/secureclock/aidl/vts/functional/AndroidTest.xml
new file mode 100644
index 0000000..4861c7c
--- /dev/null
+++ b/security/secureclock/aidl/vts/functional/AndroidTest.xml
@@ -0,0 +1,34 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Copyright (C) 2020 The Android Open Source Project
+
+     Licensed under the Apache License, Version 2.0 (the "License");
+     you may not use this file except in compliance with the License.
+     You may obtain a copy of the License at
+
+          http://www.apache.org/licenses/LICENSE-2.0
+
+     Unless required by applicable law or agreed to in writing, software
+     distributed under the License is distributed on an "AS IS" BASIS,
+     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+     See the License for the specific language governing permissions and
+     limitations under the License.
+-->
+<configuration description="Runs VtsAidlSecureClockTargetTest.">
+    <option name="test-suite-tag" value="apct" />
+    <option name="test-suite-tag" value="apct-native" />
+
+    <target_preparer class="com.android.tradefed.targetprep.RootTargetPreparer">
+    </target_preparer>
+
+    <target_preparer class="com.android.tradefed.targetprep.PushFilePreparer">
+        <option name="cleanup" value="true" />
+        <option name="push"
+                value="VtsAidlSecureClockTargetTest->/data/local/tmp/VtsAidlSecureClockTargetTest" />
+    </target_preparer>
+
+    <test class="com.android.tradefed.testtype.GTest" >
+        <option name="native-test-device-path" value="/data/local/tmp" />
+        <option name="module-name" value="VtsAidlSecureClockTargetTest" />
+        <option name="native-test-timeout" value="900000"/>
+    </test>
+</configuration>
diff --git a/security/secureclock/aidl/vts/functional/SecureClockAidlTest.cpp b/security/secureclock/aidl/vts/functional/SecureClockAidlTest.cpp
new file mode 100644
index 0000000..9ca1ee8
--- /dev/null
+++ b/security/secureclock/aidl/vts/functional/SecureClockAidlTest.cpp
@@ -0,0 +1,193 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#define LOG_TAG "secureclock_test"
+#include <android-base/logging.h>
+
+#include <aidl/Gtest.h>
+#include <aidl/Vintf.h>
+#include <aidl/android/hardware/security/keymint/ErrorCode.h>
+#include <aidl/android/hardware/security/secureclock/ISecureClock.h>
+#include <android/binder_manager.h>
+#include <binder/ProcessState.h>
+#include <gtest/gtest.h>
+#include <vector>
+
+namespace aidl::android::hardware::security::secureclock::test {
+using Status = ::ndk::ScopedAStatus;
+using ::aidl::android::hardware::security::keymint::ErrorCode;
+using ::std::shared_ptr;
+using ::std::string;
+using ::std::vector;
+
+class SecureClockAidlTest : public ::testing::TestWithParam<string> {
+  public:
+    struct TimestampTokenResult {
+        ErrorCode error;
+        TimeStampToken token;
+    };
+
+    TimestampTokenResult getTimestampToken(int64_t in_challenge) {
+        TimestampTokenResult result;
+        result.error =
+                GetReturnErrorCode(secureClock_->generateTimeStamp(in_challenge, &result.token));
+        return result;
+    }
+
+    uint64_t getTime() {
+        struct timespec timespec;
+        EXPECT_EQ(0, clock_gettime(CLOCK_BOOTTIME, &timespec));
+        return timespec.tv_sec * 1000 + timespec.tv_nsec / 1000000;
+    }
+
+    int sleep_ms(uint32_t milliseconds) {
+        struct timespec sleep_time = {static_cast<time_t>(milliseconds / 1000),
+                                      static_cast<long>(milliseconds % 1000) * 1000000};
+        while (sleep_time.tv_sec || sleep_time.tv_nsec) {
+            if (nanosleep(&sleep_time /* to wait */,
+                          &sleep_time /* remaining (on interrruption) */) == 0) {
+                sleep_time = {};
+            } else {
+                if (errno != EINTR) return errno;
+            }
+        }
+        return 0;
+    }
+
+    ErrorCode GetReturnErrorCode(const Status& result) {
+        if (result.isOk()) return ErrorCode::OK;
+
+        if (result.getExceptionCode() == EX_SERVICE_SPECIFIC) {
+            return static_cast<ErrorCode>(result.getServiceSpecificError());
+        }
+
+        return ErrorCode::UNKNOWN_ERROR;
+    }
+
+    void InitializeSecureClock(std::shared_ptr<ISecureClock> secureClock) {
+        ASSERT_NE(secureClock, nullptr);
+        secureClock_ = secureClock;
+    }
+
+    ISecureClock& secureClock() { return *secureClock_; }
+
+    static vector<string> build_params() {
+        auto params = ::android::getAidlHalInstanceNames(ISecureClock::descriptor);
+        return params;
+    }
+
+    void SetUp() override {
+        if (AServiceManager_isDeclared(GetParam().c_str())) {
+            ::ndk::SpAIBinder binder(AServiceManager_waitForService(GetParam().c_str()));
+            InitializeSecureClock(ISecureClock::fromBinder(binder));
+        } else {
+            InitializeSecureClock(nullptr);
+        }
+    }
+
+    void TearDown() override {}
+
+  private:
+    std::shared_ptr<ISecureClock> secureClock_;
+};
+
+/*
+ * The precise capabilities required to generate TimeStampToken will vary depending on the specific
+ * vendor implementations. The only thing we really can test is that tokens can be created by
+ * secureclock services, and that the timestamps increase as expected.
+ */
+TEST_P(SecureClockAidlTest, TestCreation) {
+    auto result1 = getTimestampToken(1 /* challenge */);
+    auto result1_time = getTime();
+    EXPECT_EQ(ErrorCode::OK, result1.error);
+    EXPECT_EQ(1U, result1.token.challenge);
+    EXPECT_GT(result1.token.timestamp.milliSeconds, 0U);
+
+    unsigned long time_to_sleep = 200;
+    sleep_ms(time_to_sleep);
+
+    auto result2 = getTimestampToken(2 /* challenge */);
+    auto result2_time = getTime();
+    EXPECT_EQ(ErrorCode::OK, result2.error);
+    EXPECT_EQ(2U, result2.token.challenge);
+    EXPECT_GT(result2.token.timestamp.milliSeconds, 0U);
+
+    auto host_time_delta = result2_time - result1_time;
+
+    EXPECT_GE(host_time_delta, time_to_sleep)
+            << "We slept for " << time_to_sleep << " ms, the clock must have advanced by that much";
+    EXPECT_LE(host_time_delta, time_to_sleep + 100)
+            << "The getTimestampToken call took " << (host_time_delta - time_to_sleep)
+            << " ms?  That's awful!";
+    EXPECT_GE(result2.token.timestamp.milliSeconds, result1.token.timestamp.milliSeconds);
+    unsigned long km_time_delta =
+            result2.token.timestamp.milliSeconds - result1.token.timestamp.milliSeconds;
+    // 20 ms of slop just to avoid test flakiness.
+    EXPECT_LE(host_time_delta, km_time_delta + 20);
+    EXPECT_LE(km_time_delta, host_time_delta + 20);
+    ASSERT_EQ(result1.token.mac.size(), result2.token.mac.size());
+    ASSERT_NE(0,
+              memcmp(result1.token.mac.data(), result2.token.mac.data(), result1.token.mac.size()));
+}
+
+/*
+ * Test that the mac changes when the time stamp changes. This is does not guarantee that the time
+ * stamp is included in the mac but on failure we know that it is not. Other than in the test
+ * case above we call getTimestampToken with the exact same set of parameters.
+ */
+TEST_P(SecureClockAidlTest, MacChangesOnChangingTimestamp) {
+    auto result1 = getTimestampToken(0 /* challenge */);
+    auto result1_time = getTime();
+    EXPECT_EQ(ErrorCode::OK, result1.error);
+    EXPECT_EQ(0U, result1.token.challenge);
+    EXPECT_GT(result1.token.timestamp.milliSeconds, 0U);
+
+    unsigned long time_to_sleep = 200;
+    sleep_ms(time_to_sleep);
+
+    auto result2 = getTimestampToken(1 /* challenge */);
+    auto result2_time = getTime();
+    EXPECT_EQ(ErrorCode::OK, result2.error);
+    EXPECT_EQ(1U, result2.token.challenge);
+    EXPECT_GT(result2.token.timestamp.milliSeconds, 0U);
+
+    auto host_time_delta = result2_time - result1_time;
+
+    EXPECT_GE(host_time_delta, time_to_sleep)
+            << "We slept for " << time_to_sleep << " ms, the clock must have advanced by that much";
+    EXPECT_LE(host_time_delta, time_to_sleep + 100)
+            << "The getTimestampToken call took " << (host_time_delta - time_to_sleep)
+            << " ms?  That's awful!";
+
+    EXPECT_GE(result2.token.timestamp.milliSeconds, result1.token.timestamp.milliSeconds);
+    unsigned long km_time_delta =
+            result2.token.timestamp.milliSeconds - result1.token.timestamp.milliSeconds;
+
+    EXPECT_LE(host_time_delta, km_time_delta + 20);
+    EXPECT_LE(km_time_delta, host_time_delta + 20);
+    ASSERT_EQ(result1.token.mac.size(), result2.token.mac.size());
+    ASSERT_NE(0,
+              memcmp(result1.token.mac.data(), result2.token.mac.data(), result1.token.mac.size()));
+}
+
+INSTANTIATE_TEST_SUITE_P(PerInstance, SecureClockAidlTest,
+                         testing::ValuesIn(SecureClockAidlTest::build_params()),
+                         ::android::PrintInstanceNameToString);
+}  // namespace aidl::android::hardware::security::secureclock::test
+
+int main(int argc, char** argv) {
+    ::testing::InitGoogleTest(&argc, argv);
+    return RUN_ALL_TESTS();
+}
\ No newline at end of file
diff --git a/security/sharedsecret/aidl/vts/functional/Android.bp b/security/sharedsecret/aidl/vts/functional/Android.bp
new file mode 100644
index 0000000..76bf7ff
--- /dev/null
+++ b/security/sharedsecret/aidl/vts/functional/Android.bp
@@ -0,0 +1,43 @@
+//
+// Copyright (C) 2020 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_test {
+    name: "VtsAidlSharedSecretTargetTest",
+    defaults: [
+        "VtsHalTargetTestDefaults",
+        "use_libaidlvintf_gtest_helper_static",
+    ],
+    srcs: [
+        "SharedSecretAidlTest.cpp",
+    ],
+    cflags: [
+        "-Wall",
+        "-Wextra",
+    ],
+    shared_libs: [
+        "libbinder_ndk",
+        "libcrypto",
+        "libkeymint",
+    ],
+    static_libs: [
+        "android.hardware.security.keymint-V1-ndk_platform",
+        "android.hardware.security.sharedsecret-V1-ndk_platform",
+    ],
+    test_suites: [
+        "general-tests",
+        "vts",
+    ],
+}
diff --git a/security/sharedsecret/aidl/vts/functional/AndroidTest.xml b/security/sharedsecret/aidl/vts/functional/AndroidTest.xml
new file mode 100644
index 0000000..c6697bc
--- /dev/null
+++ b/security/sharedsecret/aidl/vts/functional/AndroidTest.xml
@@ -0,0 +1,34 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Copyright (C) 2020 The Android Open Source Project
+
+     Licensed under the Apache License, Version 2.0 (the "License");
+     you may not use this file except in compliance with the License.
+     You may obtain a copy of the License at
+
+          http://www.apache.org/licenses/LICENSE-2.0
+
+     Unless required by applicable law or agreed to in writing, software
+     distributed under the License is distributed on an "AS IS" BASIS,
+     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+     See the License for the specific language governing permissions and
+     limitations under the License.
+-->
+<configuration description="Runs VtsAidlSharedSecretTargetTest.">
+    <option name="test-suite-tag" value="apct" />
+    <option name="test-suite-tag" value="apct-native" />
+
+    <target_preparer class="com.android.tradefed.targetprep.RootTargetPreparer">
+    </target_preparer>
+
+    <target_preparer class="com.android.tradefed.targetprep.PushFilePreparer">
+        <option name="cleanup" value="true" />
+        <option name="push"
+                value="VtsAidlSharedSecretTargetTest->/data/local/tmp/VtsAidlSharedSecretTargetTest" />
+    </target_preparer>
+
+    <test class="com.android.tradefed.testtype.GTest" >
+        <option name="native-test-device-path" value="/data/local/tmp" />
+        <option name="module-name" value="VtsAidlSharedSecretTargetTest" />
+        <option name="native-test-timeout" value="900000"/>
+    </test>
+</configuration>
diff --git a/security/sharedsecret/aidl/vts/functional/SharedSecretAidlTest.cpp b/security/sharedsecret/aidl/vts/functional/SharedSecretAidlTest.cpp
new file mode 100644
index 0000000..83f6ef3
--- /dev/null
+++ b/security/sharedsecret/aidl/vts/functional/SharedSecretAidlTest.cpp
@@ -0,0 +1,268 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "sharedsecret_test"
+#include <android-base/logging.h>
+
+#include <aidl/Vintf.h>
+#include <aidl/android/hardware/security/keymint/ErrorCode.h>
+#include <aidl/android/hardware/security/sharedsecret/ISharedSecret.h>
+#include <android/binder_manager.h>
+#include <gtest/gtest.h>
+#include <vector>
+
+namespace aidl::android::hardware::security::sharedsecret::test {
+using ::aidl::android::hardware::security::keymint::ErrorCode;
+using ::std::shared_ptr;
+using ::std::vector;
+using Status = ::ndk::ScopedAStatus;
+
+class SharedSecretAidlTest : public ::testing::Test {
+  public:
+    struct GetParamsResult {
+        ErrorCode error;
+        SharedSecretParameters params;
+        auto tie() { return std::tie(error, params); }
+    };
+
+    struct ComputeResult {
+        ErrorCode error;
+        vector<uint8_t> sharing_check;
+        auto tie() { return std::tie(error, sharing_check); }
+    };
+
+    GetParamsResult getSharedSecretParameters(shared_ptr<ISharedSecret>& sharedSecret) {
+        SharedSecretParameters params;
+        auto error = GetReturnErrorCode(sharedSecret->getSharedSecretParameters(&params));
+        EXPECT_EQ(ErrorCode::OK, error);
+        GetParamsResult result;
+        result.tie() = std::tie(error, params);
+        return result;
+    }
+
+    vector<SharedSecretParameters> getAllSharedSecretParameters() {
+        vector<SharedSecretParameters> paramsVec;
+        for (auto& sharedSecret : allSharedSecrets_) {
+            auto result = getSharedSecretParameters(sharedSecret);
+            EXPECT_EQ(ErrorCode::OK, result.error);
+            if (result.error == ErrorCode::OK) paramsVec.push_back(std::move(result.params));
+        }
+        return paramsVec;
+    }
+
+    ComputeResult computeSharedSecret(shared_ptr<ISharedSecret>& sharedSecret,
+                                      const vector<SharedSecretParameters>& params) {
+        std::vector<uint8_t> sharingCheck;
+        auto error = GetReturnErrorCode(sharedSecret->computeSharedSecret(params, &sharingCheck));
+        ComputeResult result;
+        result.tie() = std::tie(error, sharingCheck);
+        return result;
+    }
+
+    vector<ComputeResult> computeAllSharedSecrets(const vector<SharedSecretParameters>& params) {
+        vector<ComputeResult> result;
+        for (auto& sharedSecret : allSharedSecrets_) {
+            result.push_back(computeSharedSecret(sharedSecret, params));
+        }
+        return result;
+    }
+
+    vector<vector<uint8_t>> copyNonces(const vector<SharedSecretParameters>& paramsVec) {
+        vector<vector<uint8_t>> nonces;
+        for (auto& param : paramsVec) {
+            nonces.push_back(param.nonce);
+        }
+        return nonces;
+    }
+
+    void verifyResponses(const vector<uint8_t>& expected, const vector<ComputeResult>& responses) {
+        for (auto& response : responses) {
+            EXPECT_EQ(ErrorCode::OK, response.error);
+            EXPECT_EQ(expected, response.sharing_check) << "Sharing check values should match.";
+        }
+    }
+
+    ErrorCode GetReturnErrorCode(const Status& result) {
+        if (result.isOk()) return ErrorCode::OK;
+        if (result.getExceptionCode() == EX_SERVICE_SPECIFIC) {
+            return static_cast<ErrorCode>(result.getServiceSpecificError());
+        }
+        return ErrorCode::UNKNOWN_ERROR;
+    }
+
+    static shared_ptr<ISharedSecret> getSharedSecretService(const char* name) {
+        if (AServiceManager_isDeclared(name)) {
+            ::ndk::SpAIBinder binder(AServiceManager_waitForService(name));
+            return ISharedSecret::fromBinder(binder);
+        }
+        return nullptr;
+    }
+
+    const vector<shared_ptr<ISharedSecret>>& allSharedSecrets() { return allSharedSecrets_; }
+
+    static void SetUpTestCase() {
+        if (allSharedSecrets_.empty()) {
+            auto names = ::android::getAidlHalInstanceNames(ISharedSecret::descriptor);
+            for (const auto& name : names) {
+                auto servicePtr = getSharedSecretService(name.c_str());
+                if (servicePtr != nullptr) allSharedSecrets_.push_back(std::move(servicePtr));
+            }
+        }
+    }
+    static void TearDownTestCase() {}
+    void SetUp() override {}
+    void TearDown() override {}
+
+  private:
+    static vector<shared_ptr<ISharedSecret>> allSharedSecrets_;
+};
+
+vector<shared_ptr<ISharedSecret>> SharedSecretAidlTest::allSharedSecrets_;
+
+TEST_F(SharedSecretAidlTest, GetParameters) {
+    auto sharedSecrets = allSharedSecrets();
+    for (auto sharedSecret : sharedSecrets) {
+        auto result1 = getSharedSecretParameters(sharedSecret);
+        EXPECT_EQ(ErrorCode::OK, result1.error);
+        auto result2 = getSharedSecretParameters(sharedSecret);
+        EXPECT_EQ(ErrorCode::OK, result2.error);
+        ASSERT_EQ(result1.params.seed, result2.params.seed)
+                << "A given shared secret service should always return the same seed.";
+        ASSERT_EQ(result1.params.nonce, result2.params.nonce)
+                << "A given shared secret service should always return the same nonce until "
+                   "restart.";
+    }
+}
+
+TEST_F(SharedSecretAidlTest, ComputeSharedSecret) {
+    auto params = getAllSharedSecretParameters();
+    ASSERT_EQ(allSharedSecrets().size(), params.size())
+            << "One or more shared secret services failed to provide parameters.";
+    auto nonces = copyNonces(params);
+    EXPECT_EQ(allSharedSecrets().size(), nonces.size());
+    std::sort(nonces.begin(), nonces.end());
+    std::unique(nonces.begin(), nonces.end());
+    EXPECT_EQ(allSharedSecrets().size(), nonces.size());
+
+    auto responses = computeAllSharedSecrets(params);
+    ASSERT_GT(responses.size(), 0U);
+    verifyResponses(responses[0].sharing_check, responses);
+
+    // Do it a second time.  Should get the same answers.
+    params = getAllSharedSecretParameters();
+    ASSERT_EQ(allSharedSecrets().size(), params.size())
+            << "One or more shared secret services failed to provide parameters.";
+
+    responses = computeAllSharedSecrets(params);
+    ASSERT_GT(responses.size(), 0U);
+    ASSERT_EQ(32U, responses[0].sharing_check.size());
+    verifyResponses(responses[0].sharing_check, responses);
+}
+
+template <class F>
+class final_action {
+  public:
+    explicit final_action(F f) : f_(std::move(f)) {}
+    ~final_action() { f_(); }
+
+  private:
+    F f_;
+};
+
+template <class F>
+inline final_action<F> finally(const F& f) {
+    return final_action<F>(f);
+}
+
+TEST_F(SharedSecretAidlTest, ComputeSharedSecretCorruptNonce) {
+    auto fixup_hmac = finally([&]() { computeAllSharedSecrets(getAllSharedSecretParameters()); });
+
+    auto params = getAllSharedSecretParameters();
+    ASSERT_EQ(allSharedSecrets().size(), params.size())
+            << "One or more shared secret services failed to provide parameters.";
+
+    // All should be well in the normal case
+    auto responses = computeAllSharedSecrets(params);
+
+    ASSERT_GT(responses.size(), 0U);
+    vector<uint8_t> correct_response = responses[0].sharing_check;
+    verifyResponses(correct_response, responses);
+
+    // Pick a random param, a random byte within the param's nonce, and a random bit within
+    // the byte.  Flip that bit.
+    size_t param_to_tweak = rand() % params.size();
+    uint8_t byte_to_tweak = rand() % sizeof(params[param_to_tweak].nonce);
+    uint8_t bit_to_tweak = rand() % 8;
+    params[param_to_tweak].nonce[byte_to_tweak] ^= (1 << bit_to_tweak);
+
+    responses = computeAllSharedSecrets(params);
+    for (size_t i = 0; i < responses.size(); ++i) {
+        if (i == param_to_tweak) {
+            EXPECT_EQ(ErrorCode::INVALID_ARGUMENT, responses[i].error)
+                    << "Shared secret service that provided tweaked param should fail to compute "
+                       "shared secret";
+        } else {
+            EXPECT_EQ(ErrorCode::OK, responses[i].error) << "Others should succeed";
+            EXPECT_NE(correct_response, responses[i].sharing_check)
+                    << "Others should calculate a different shared secret, due to the tweaked "
+                       "nonce.";
+        }
+    }
+}
+
+TEST_F(SharedSecretAidlTest, ComputeSharedSecretCorruptSeed) {
+    auto fixup_hmac = finally([&]() { computeAllSharedSecrets(getAllSharedSecretParameters()); });
+    auto params = getAllSharedSecretParameters();
+    ASSERT_EQ(allSharedSecrets().size(), params.size())
+            << "One or more shared secret service failed to provide parameters.";
+
+    // All should be well in the normal case
+    auto responses = computeAllSharedSecrets(params);
+
+    ASSERT_GT(responses.size(), 0U);
+    vector<uint8_t> correct_response = responses[0].sharing_check;
+    verifyResponses(correct_response, responses);
+
+    // Pick a random param and modify the seed.  We just increase the seed length by 1.  It doesn't
+    // matter what value is in the additional byte; it changes the seed regardless.
+    auto param_to_tweak = rand() % params.size();
+    auto& to_tweak = params[param_to_tweak].seed;
+    ASSERT_TRUE(to_tweak.size() == 32 || to_tweak.size() == 0);
+    if (!to_tweak.size()) {
+        to_tweak.resize(32);  // Contents don't matter; a little randomization is nice.
+    }
+    to_tweak[0]++;
+
+    responses = computeAllSharedSecrets(params);
+    for (size_t i = 0; i < responses.size(); ++i) {
+        if (i == param_to_tweak) {
+            EXPECT_EQ(ErrorCode::INVALID_ARGUMENT, responses[i].error)
+                    << "Shared secret service that provided tweaked param should fail to compute "
+                       "shared secret";
+        } else {
+            EXPECT_EQ(ErrorCode::OK, responses[i].error) << "Others should succeed";
+            EXPECT_NE(correct_response, responses[i].sharing_check)
+                    << "Others should calculate a different shared secret, due to the tweaked "
+                       "nonce.";
+        }
+    }
+}
+}  // namespace aidl::android::hardware::security::sharedsecret::test
+
+int main(int argc, char** argv) {
+    ::testing::InitGoogleTest(&argc, argv);
+    return RUN_ALL_TESTS();
+}
diff --git a/tetheroffload/control/1.0/vts/functional/VtsHalTetheroffloadControlV1_0TargetTest.cpp b/tetheroffload/control/1.0/vts/functional/VtsHalTetheroffloadControlV1_0TargetTest.cpp
index ad4ef12..ea9bcb5 100644
--- a/tetheroffload/control/1.0/vts/functional/VtsHalTetheroffloadControlV1_0TargetTest.cpp
+++ b/tetheroffload/control/1.0/vts/functional/VtsHalTetheroffloadControlV1_0TargetTest.cpp
@@ -469,7 +469,7 @@
     }
 }
 
-GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(OffloadControlHidlTestBase);
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(OffloadControlTestV1_0_HalNotStarted);
 INSTANTIATE_TEST_CASE_P(
         PerInstance, OffloadControlTestV1_0_HalNotStarted,
         testing::Combine(testing::ValuesIn(android::hardware::getAllHalInstanceNames(
@@ -478,7 +478,7 @@
                                  IOffloadControl::descriptor))),
         android::hardware::PrintInstanceTupleNameToString<>);
 
-GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(OffloadControlHidlTest);
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(OffloadControlTestV1_0_HalStarted);
 INSTANTIATE_TEST_CASE_P(
         PerInstance, OffloadControlTestV1_0_HalStarted,
         testing::Combine(testing::ValuesIn(android::hardware::getAllHalInstanceNames(
diff --git a/tv/cec/1.1/Android.bp b/tv/cec/1.1/Android.bp
new file mode 100644
index 0000000..c2d4e54
--- /dev/null
+++ b/tv/cec/1.1/Android.bp
@@ -0,0 +1,16 @@
+// This file is autogenerated by hidl-gen -Landroidbp.
+
+hidl_interface {
+    name: "android.hardware.tv.cec@1.1",
+    root: "android.hardware",
+    srcs: [
+        "types.hal",
+        "IHdmiCec.hal",
+        "IHdmiCecCallback.hal",
+    ],
+    interfaces: [
+        "android.hardware.tv.cec@1.0",
+        "android.hidl.base@1.0",
+    ],
+    gen_java: true,
+}
diff --git a/tv/cec/1.1/IHdmiCec.hal b/tv/cec/1.1/IHdmiCec.hal
new file mode 100644
index 0000000..fe7bedf
--- /dev/null
+++ b/tv/cec/1.1/IHdmiCec.hal
@@ -0,0 +1,70 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.tv.cec@1.1;
+
+import @1.0::IHdmiCec;
+import @1.0::Result;
+import @1.0::SendMessageResult;
+
+import IHdmiCecCallback;
+
+/**
+ * HDMI-CEC HAL interface definition.
+ */
+interface IHdmiCec extends @1.0::IHdmiCec {
+    /**
+     * Passes the logical address that must be used in this system.
+     *
+     * HAL must use it to configure the hardware so that the CEC commands
+     * addressed the given logical address can be filtered in. This method must
+     * be able to be called as many times as necessary in order to support
+     * multiple logical devices.
+     *
+     * @param addr Logical address that must be used in this system. It must be
+     *        in the range of valid logical addresses for the call to succeed.
+     * @return result Result status of the operation. SUCCESS if successful,
+     *         FAILURE_INVALID_ARGS if the given logical address is invalid,
+     *         FAILURE_BUSY if device or resource is busy
+     */
+    addLogicalAddress_1_1(CecLogicalAddress addr) generates (Result result);
+
+    /**
+     * Transmits HDMI-CEC message to other HDMI device.
+     *
+     * The method must be designed to return in a certain amount of time and not
+     * hanging forever which may happen if CEC signal line is pulled low for
+     * some reason.
+     *
+     * It must try retransmission at least once as specified in the section '7.1
+     * Frame Re-transmissions' of the CEC Spec 1.4b.
+     *
+     * @param message CEC message to be sent to other HDMI device.
+     * @return result Result status of the operation. SUCCESS if successful,
+     *         NACK if the sent message is not acknowledged,
+     *         BUSY if the CEC bus is busy.
+     */
+    sendMessage_1_1(CecMessage message) generates (SendMessageResult result);
+
+    /**
+     * Sets a callback that HDMI-CEC HAL must later use for incoming CEC
+     * messages or internal HDMI events.
+     *
+     * @param callback Callback object to pass hdmi events to the system. The
+     *        previously registered callback must be replaced with this one.
+     */
+    setCallback_1_1(IHdmiCecCallback callback);
+};
diff --git a/tv/cec/1.1/IHdmiCecCallback.hal b/tv/cec/1.1/IHdmiCecCallback.hal
new file mode 100644
index 0000000..3928f18
--- /dev/null
+++ b/tv/cec/1.1/IHdmiCecCallback.hal
@@ -0,0 +1,30 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.tv.cec@1.1;
+
+import @1.0::IHdmiCecCallback;
+
+/**
+ * Callbacks from the HAL implementation to notify the system of new events.
+ */
+interface IHdmiCecCallback extends @1.0::IHdmiCecCallback {
+    /**
+     * The callback function that must be called by HAL implementation to notify
+     * the system of new CEC message arrival.
+     */
+    oneway onCecMessage_1_1(CecMessage message);
+};
diff --git a/tv/cec/1.1/default/Android.bp b/tv/cec/1.1/default/Android.bp
new file mode 100644
index 0000000..e0dff0d
--- /dev/null
+++ b/tv/cec/1.1/default/Android.bp
@@ -0,0 +1,23 @@
+cc_binary {
+    name: "android.hardware.tv.cec@1.1-service",
+    defaults: ["hidl_defaults"],
+    vintf_fragments: ["android.hardware.tv.cec@1.1-service.xml"],
+    relative_install_path: "hw",
+    vendor: true,
+    init_rc: ["android.hardware.tv.cec@1.1-service.rc"],
+    srcs: [
+        "serviceMock.cpp",
+        "HdmiCecMock.cpp",
+    ],
+
+    shared_libs: [
+        "liblog",
+        "libcutils",
+        "libbase",
+        "libutils",
+        "libhardware",
+        "libhidlbase",
+        "android.hardware.tv.cec@1.0",
+        "android.hardware.tv.cec@1.1",
+    ],
+}
diff --git a/tv/cec/1.1/default/HdmiCecMock.cpp b/tv/cec/1.1/default/HdmiCecMock.cpp
new file mode 100644
index 0000000..f65bab9
--- /dev/null
+++ b/tv/cec/1.1/default/HdmiCecMock.cpp
@@ -0,0 +1,371 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "android.hardware.tv.cec@1.1"
+#include <android-base/logging.h>
+#include <utils/Log.h>
+
+#include <hardware/hardware.h>
+#include <hardware/hdmi_cec.h>
+#include "HdmiCecMock.h"
+
+namespace android {
+namespace hardware {
+namespace tv {
+namespace cec {
+namespace V1_1 {
+namespace implementation {
+
+class WrappedCallback : public ::android::hardware::tv::cec::V1_1::IHdmiCecCallback {
+  public:
+    WrappedCallback(sp<::android::hardware::tv::cec::V1_0::IHdmiCecCallback> callback) {
+        mCallback = callback;
+    }
+
+    Return<void> onCecMessage(const ::android::hardware::tv::cec::V1_0::CecMessage& message) {
+        mCallback->onCecMessage(message);
+        return Void();
+    }
+    Return<void> onCecMessage_1_1(const ::android::hardware::tv::cec::V1_1::CecMessage& message) {
+        ::android::hardware::tv::cec::V1_0::CecMessage cecMessage;
+        cecMessage.initiator =
+                ::android::hardware::tv::cec::V1_0::CecLogicalAddress(message.initiator);
+        cecMessage.destination =
+                ::android::hardware::tv::cec::V1_0::CecLogicalAddress(message.destination);
+        cecMessage.body = message.body;
+        mCallback->onCecMessage(cecMessage);
+        return Void();
+    }
+    Return<void> onHotplugEvent(const ::android::hardware::tv::cec::V1_0::HotplugEvent& event) {
+        mCallback->onHotplugEvent(event);
+        return Void();
+    }
+
+  private:
+    sp<::android::hardware::tv::cec::V1_0::IHdmiCecCallback> mCallback;
+};
+
+/*
+ * (*set_option)() passes flags controlling the way HDMI-CEC service works down
+ * to HAL implementation. Those flags will be used in case the feature needs
+ * update in HAL itself, firmware or microcontroller.
+ */
+void HdmiCecMock::cec_set_option(int flag, int value) {
+    // maintain options and set them accordingly
+    switch (flag) {
+        case HDMI_OPTION_WAKEUP:
+            mOptionWakeUp = value;
+            break;
+        case HDMI_OPTION_ENABLE_CEC:
+            mOptionEnableCec = value;
+            break;
+        case HDMI_OPTION_SYSTEM_CEC_CONTROL:
+            mOptionSystemCecControl = value;
+            break;
+        case HDMI_OPTION_SET_LANG:
+            mOptionLanguage = value;
+            break;
+    }
+}
+
+// Methods from ::android::hardware::tv::cec::V1_0::IHdmiCec follow.
+Return<Result> HdmiCecMock::addLogicalAddress(CecLogicalAddress addr) {
+    return addLogicalAddress_1_1(::android::hardware::tv::cec::V1_1::CecLogicalAddress(addr));
+}
+
+Return<void> HdmiCecMock::clearLogicalAddress() {
+    // remove logical address from the list
+    mLogicalAddresses = {};
+    return Void();
+}
+
+Return<void> HdmiCecMock::getPhysicalAddress(getPhysicalAddress_cb _hidl_cb) {
+    // maintain a physical address and return it
+    // default 0xFFFF, update on hotplug event
+    _hidl_cb(Result::SUCCESS, mPhysicalAddress);
+    return Void();
+}
+
+Return<SendMessageResult> HdmiCecMock::sendMessage(const CecMessage& message) {
+    ::android::hardware::tv::cec::V1_1::CecMessage cecMessage;
+    cecMessage.initiator = ::android::hardware::tv::cec::V1_1::CecLogicalAddress(message.initiator);
+    cecMessage.destination =
+            ::android::hardware::tv::cec::V1_1::CecLogicalAddress(message.destination);
+    cecMessage.body = message.body;
+    return sendMessage_1_1(cecMessage);
+}
+
+Return<void> HdmiCecMock::setCallback(const sp<IHdmiCecCallback>& callback) {
+    return setCallback_1_1(new WrappedCallback(callback));
+}
+
+Return<int32_t> HdmiCecMock::getCecVersion() {
+    // maintain a cec version and return it
+    return mCecVersion;
+}
+
+Return<uint32_t> HdmiCecMock::getVendorId() {
+    return mCecVendorId;
+}
+
+Return<void> HdmiCecMock::getPortInfo(getPortInfo_cb _hidl_cb) {
+    // TODO ready port info from device specific config
+    _hidl_cb(mPortInfo);
+    return Void();
+}
+
+Return<void> HdmiCecMock::setOption(OptionKey key, bool value) {
+    cec_set_option(static_cast<int>(key), value ? 1 : 0);
+    return Void();
+}
+
+Return<void> HdmiCecMock::setLanguage(const hidl_string& language) {
+    if (language.size() != 3) {
+        LOG(ERROR) << "Wrong language code: expected 3 letters, but it was " << language.size()
+                   << ".";
+        return Void();
+    }
+    // TODO validate if language is a valid language code
+    const char* languageStr = language.c_str();
+    int convertedLanguage = ((languageStr[0] & 0xFF) << 16) | ((languageStr[1] & 0xFF) << 8) |
+                            (languageStr[2] & 0xFF);
+    cec_set_option(HDMI_OPTION_SET_LANG, convertedLanguage);
+    return Void();
+}
+
+Return<void> HdmiCecMock::enableAudioReturnChannel(int32_t portId __unused, bool enable __unused) {
+    // Maintain ARC status
+    return Void();
+}
+
+Return<bool> HdmiCecMock::isConnected(int32_t portId) {
+    // maintain port connection status and update on hotplug event
+    if (portId < mTotalPorts && portId >= 0) {
+        return mPortConnectionStatus[portId];
+    }
+    return false;
+}
+
+// Methods from ::android::hardware::tv::cec::V1_1::IHdmiCec follow.
+Return<Result> HdmiCecMock::addLogicalAddress_1_1(
+        ::android::hardware::tv::cec::V1_1::CecLogicalAddress addr) {
+    // have a list to maintain logical addresses
+    int size = mLogicalAddresses.size();
+    mLogicalAddresses.resize(size + 1);
+    mLogicalAddresses[size + 1] = addr;
+    return Result::SUCCESS;
+}
+
+Return<SendMessageResult> HdmiCecMock::sendMessage_1_1(
+        const ::android::hardware::tv::cec::V1_1::CecMessage& message) {
+    if (message.body.size() == 0) {
+        return SendMessageResult::NACK;
+    }
+    sendMessageToFifo(message);
+    return SendMessageResult::SUCCESS;
+}
+
+Return<void> HdmiCecMock::setCallback_1_1(
+        const sp<::android::hardware::tv::cec::V1_1::IHdmiCecCallback>& callback) {
+    if (mCallback != nullptr) {
+        mCallback = nullptr;
+    }
+
+    if (callback != nullptr) {
+        mCallback = callback;
+        mCallback->linkToDeath(this, 0 /*cookie*/);
+
+        mInputFile = open(CEC_MSG_IN_FIFO, O_RDWR);
+        mOutputFile = open(CEC_MSG_OUT_FIFO, O_RDWR);
+        pthread_create(&mThreadId, NULL, __threadLoop, this);
+        pthread_setname_np(mThreadId, "hdmi_cec_loop");
+    }
+    return Void();
+}
+
+void* HdmiCecMock::__threadLoop(void* user) {
+    HdmiCecMock* const self = static_cast<HdmiCecMock*>(user);
+    self->threadLoop();
+    return 0;
+}
+
+int HdmiCecMock::readMessageFromFifo(unsigned char* buf, int msgCount) {
+    if (msgCount <= 0 || !buf) {
+        return 0;
+    }
+
+    int ret = -1;
+    /* maybe blocked at driver */
+    ret = read(mInputFile, buf, msgCount);
+    if (ret < 0) {
+        ALOGE("[halimp] read :%s failed, ret:%d\n", CEC_MSG_IN_FIFO, ret);
+        return -1;
+    }
+
+    return ret;
+}
+
+int HdmiCecMock::sendMessageToFifo(const ::android::hardware::tv::cec::V1_1::CecMessage& message) {
+    unsigned char msgBuf[CEC_MESSAGE_BODY_MAX_LENGTH];
+    int ret = -1;
+
+    memset(msgBuf, 0, sizeof(msgBuf));
+    msgBuf[0] = ((static_cast<uint8_t>(message.initiator) & 0xf) << 4) |
+                (static_cast<uint8_t>(message.destination) & 0xf);
+
+    size_t length = std::min(static_cast<size_t>(message.body.size()),
+                             static_cast<size_t>(MaxLength::MESSAGE_BODY));
+    for (size_t i = 0; i < length; ++i) {
+        msgBuf[i + 1] = static_cast<unsigned char>(message.body[i]);
+    }
+
+    // open the output pipe for writing outgoing cec message
+    mOutputFile = open(CEC_MSG_OUT_FIFO, O_WRONLY);
+    if (mOutputFile < 0) {
+        ALOGD("[halimp] file open failed for writing");
+        return -1;
+    }
+
+    // write message into the output pipe
+    ret = write(mOutputFile, msgBuf, length + 1);
+    close(mOutputFile);
+    if (ret < 0) {
+        ALOGE("[halimp] write :%s failed, ret:%d\n", CEC_MSG_OUT_FIFO, ret);
+        return -1;
+    }
+    return ret;
+}
+
+void HdmiCecMock::printCecMsgBuf(const char* msg_buf, int len) {
+    char buf[64] = {};
+    int i, size = 0;
+    memset(buf, 0, sizeof(buf));
+    for (i = 0; i < len; i++) {
+        size += sprintf(buf + size, " %02x", msg_buf[i]);
+    }
+    ALOGD("[halimp] %s, msg:%s", __FUNCTION__, buf);
+}
+
+void HdmiCecMock::handleHotplugMessage(unsigned char* msgBuf) {
+    HotplugEvent hotplugEvent{.connected = ((msgBuf[3]) & 0xf) > 0,
+                              .portId = static_cast<uint32_t>(msgBuf[0] & 0xf)};
+
+    if (hotplugEvent.portId >= mPortInfo.size()) {
+        ALOGD("[halimp] ignore hot plug message, id %x does not exist", hotplugEvent.portId);
+        return;
+    }
+
+    ALOGD("[halimp] hot plug port id %x, is connected %x", (msgBuf[0] & 0xf), (msgBuf[3] & 0xf));
+    if (mPortInfo[hotplugEvent.portId].type == HdmiPortType::OUTPUT) {
+        mPhysicalAddress =
+                ((hotplugEvent.connected == 0) ? 0xffff : ((msgBuf[1] << 8) | (msgBuf[2])));
+        mPortInfo[hotplugEvent.portId].physicalAddress = mPhysicalAddress;
+        ALOGD("[halimp] hot plug physical address %x", mPhysicalAddress);
+    }
+
+    // todo update connection status
+
+    if (mCallback != nullptr) {
+        mCallback->onHotplugEvent(hotplugEvent);
+    }
+}
+
+void HdmiCecMock::handleCecMessage(unsigned char* msgBuf, int megSize) {
+    ::android::hardware::tv::cec::V1_1::CecMessage message;
+    size_t length = std::min(static_cast<size_t>(megSize - 1),
+                             static_cast<size_t>(MaxLength::MESSAGE_BODY));
+    message.body.resize(length);
+
+    for (size_t i = 0; i < length; ++i) {
+        message.body[i] = static_cast<uint8_t>(msgBuf[i + 1]);
+        ALOGD("[halimp] msg body %x", message.body[i]);
+    }
+
+    message.initiator = static_cast<::android::hardware::tv::cec::V1_1::CecLogicalAddress>(
+            (msgBuf[0] >> 4) & 0xf);
+    ALOGD("[halimp] msg init %x", message.initiator);
+    message.destination = static_cast<::android::hardware::tv::cec::V1_1::CecLogicalAddress>(
+            (msgBuf[0] >> 0) & 0xf);
+    ALOGD("[halimp] msg dest %x", message.destination);
+
+    // messageValidateAndHandle(&event);
+
+    if (mCallback != nullptr) {
+        mCallback->onCecMessage_1_1(message);
+    }
+}
+
+void HdmiCecMock::threadLoop() {
+    ALOGD("[halimp] threadLoop start.");
+    unsigned char msgBuf[CEC_MESSAGE_BODY_MAX_LENGTH];
+    int r = -1;
+
+    // open the input pipe
+    while (mInputFile < 0) {
+        usleep(1000 * 1000);
+        mInputFile = open(CEC_MSG_IN_FIFO, O_RDONLY);
+    }
+    ALOGD("[halimp] file open ok, fd = %d.", mInputFile);
+
+    while (mCecThreadRun) {
+        if (!mOptionSystemCecControl) {
+            usleep(1000 * 1000);
+            continue;
+        }
+
+        memset(msgBuf, 0, sizeof(msgBuf));
+        // try to get a message from dev.
+        // echo -n -e '\x04\x83' >> /dev/cec
+        r = readMessageFromFifo(msgBuf, CEC_MESSAGE_BODY_MAX_LENGTH);
+        if (r <= 1) {
+            // ignore received ping messages
+            continue;
+        }
+
+        printCecMsgBuf((const char*)msgBuf, r);
+
+        if (((msgBuf[0] >> 4) & 0xf) == 0xf) {
+            // the message is a hotplug event
+            handleHotplugMessage(msgBuf);
+            continue;
+        }
+
+        handleCecMessage(msgBuf, r);
+    }
+
+    ALOGD("[halimp] thread end.");
+    // mCecDevice.mExited = true;
+}
+
+HdmiCecMock::HdmiCecMock() {
+    ALOGE("[halimp] Opening a virtual HAL for testing and virtual machine.");
+    mCallback = nullptr;
+    mPortInfo.resize(mTotalPorts);
+    mPortConnectionStatus.resize(mTotalPorts);
+    mPortInfo[0] = {.type = HdmiPortType::OUTPUT,
+                    .portId = static_cast<uint32_t>(1),
+                    .cecSupported = true,
+                    .arcSupported = false,
+                    .physicalAddress = mPhysicalAddress};
+    mPortConnectionStatus[0] = false;
+}
+
+}  // namespace implementation
+}  // namespace V1_1
+}  // namespace cec
+}  // namespace tv
+}  // namespace hardware
+}  // namespace android
\ No newline at end of file
diff --git a/tv/cec/1.1/default/HdmiCecMock.h b/tv/cec/1.1/default/HdmiCecMock.h
new file mode 100644
index 0000000..0205f8d
--- /dev/null
+++ b/tv/cec/1.1/default/HdmiCecMock.h
@@ -0,0 +1,125 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <android/hardware/tv/cec/1.1/IHdmiCec.h>
+#include <hidl/Status.h>
+#include <algorithm>
+#include <vector>
+
+using namespace std;
+
+namespace android {
+namespace hardware {
+namespace tv {
+namespace cec {
+namespace V1_1 {
+namespace implementation {
+
+using ::android::sp;
+using ::android::hardware::hidl_string;
+using ::android::hardware::hidl_vec;
+using ::android::hardware::Return;
+using ::android::hardware::Void;
+using ::android::hardware::tv::cec::V1_0::CecLogicalAddress;
+using ::android::hardware::tv::cec::V1_0::CecMessage;
+using ::android::hardware::tv::cec::V1_0::HdmiPortInfo;
+using ::android::hardware::tv::cec::V1_0::HdmiPortType;
+using ::android::hardware::tv::cec::V1_0::HotplugEvent;
+using ::android::hardware::tv::cec::V1_0::IHdmiCecCallback;
+using ::android::hardware::tv::cec::V1_0::MaxLength;
+using ::android::hardware::tv::cec::V1_0::OptionKey;
+using ::android::hardware::tv::cec::V1_0::Result;
+using ::android::hardware::tv::cec::V1_0::SendMessageResult;
+using ::android::hardware::tv::cec::V1_1::IHdmiCec;
+
+#define CEC_MSG_IN_FIFO "/dev/cec_in_pipe"
+#define CEC_MSG_OUT_FIFO "/dev/cec_out_pipe"
+
+struct HdmiCecMock : public IHdmiCec, public hidl_death_recipient {
+    HdmiCecMock();
+    // Methods from ::android::hardware::tv::cec::V1_0::IHdmiCec follow.
+    Return<Result> addLogicalAddress(CecLogicalAddress addr) override;
+    Return<void> clearLogicalAddress() override;
+    Return<void> getPhysicalAddress(getPhysicalAddress_cb _hidl_cb) override;
+    Return<SendMessageResult> sendMessage(const CecMessage& message) override;
+    Return<void> setCallback(
+            const sp<::android::hardware::tv::cec::V1_0::IHdmiCecCallback>& callback) override;
+    Return<int32_t> getCecVersion() override;
+    Return<uint32_t> getVendorId() override;
+    Return<void> getPortInfo(getPortInfo_cb _hidl_cb) override;
+    Return<void> setOption(OptionKey key, bool value) override;
+    Return<void> setLanguage(const hidl_string& language) override;
+    Return<void> enableAudioReturnChannel(int32_t portId, bool enable) override;
+    Return<bool> isConnected(int32_t portId) override;
+
+    // Methods from ::android::hardware::tv::cec::V1_1::IHdmiCec follow.
+    Return<Result> addLogicalAddress_1_1(
+            ::android::hardware::tv::cec::V1_1::CecLogicalAddress addr) override;
+    Return<SendMessageResult> sendMessage_1_1(
+            const ::android::hardware::tv::cec::V1_1::CecMessage& message) override;
+    Return<void> setCallback_1_1(
+            const sp<::android::hardware::tv::cec::V1_1::IHdmiCecCallback>& callback) override;
+
+    virtual void serviceDied(uint64_t /*cookie*/,
+                             const wp<::android::hidl::base::V1_0::IBase>& /*who*/) {
+        setCallback(nullptr);
+    }
+
+    void cec_set_option(int flag, int value);
+    void printCecMsgBuf(const char* msg_buf, int len);
+
+  private:
+    static void* __threadLoop(void* data);
+    void threadLoop();
+    int readMessageFromFifo(unsigned char* buf, int msgCount);
+    int sendMessageToFifo(const ::android::hardware::tv::cec::V1_1::CecMessage& message);
+    void handleHotplugMessage(unsigned char* msgBuf);
+    void handleCecMessage(unsigned char* msgBuf, int length);
+
+  private:
+    sp<::android::hardware::tv::cec::V1_1::IHdmiCecCallback> mCallback;
+
+    // Variables for the virtual cec hal impl
+    uint16_t mPhysicalAddress = 0xFFFF;
+    vector<::android::hardware::tv::cec::V1_1::CecLogicalAddress> mLogicalAddresses;
+    int32_t mCecVersion = 0x06;
+    uint32_t mCecVendorId = 0x01;
+
+    // Port configuration
+    int mTotalPorts = 1;
+    hidl_vec<HdmiPortInfo> mPortInfo;
+    hidl_vec<bool> mPortConnectionStatus;
+
+    // CEC Option value
+    int mOptionWakeUp = 0;
+    int mOptionEnableCec = 0;
+    int mOptionSystemCecControl = 0;
+    int mOptionLanguage = 0;
+
+    // Testing variables
+    // Input file descriptor
+    int mInputFile;
+    // Output file descriptor
+    int mOutputFile;
+    bool mCecThreadRun = true;
+    pthread_t mThreadId = 0;
+};
+}  // namespace implementation
+}  // namespace V1_1
+}  // namespace cec
+}  // namespace tv
+}  // namespace hardware
+}  // namespace android
\ No newline at end of file
diff --git a/tv/cec/1.1/default/android.hardware.tv.cec@1.1-service.rc b/tv/cec/1.1/default/android.hardware.tv.cec@1.1-service.rc
new file mode 100644
index 0000000..e150c91
--- /dev/null
+++ b/tv/cec/1.1/default/android.hardware.tv.cec@1.1-service.rc
@@ -0,0 +1,6 @@
+service vendor.cec-hal-1-1 /vendor/bin/hw/android.hardware.tv.cec@1.1-service
+    interface android.hardware.tv.cec@1.0::IHdmiCec default
+    interface android.hardware.tv.cec@1.1::IHdmiCec default
+    class hal
+    user system
+    group system
\ No newline at end of file
diff --git a/tv/cec/1.1/default/android.hardware.tv.cec@1.1-service.xml b/tv/cec/1.1/default/android.hardware.tv.cec@1.1-service.xml
new file mode 100644
index 0000000..492369e
--- /dev/null
+++ b/tv/cec/1.1/default/android.hardware.tv.cec@1.1-service.xml
@@ -0,0 +1,11 @@
+<manifest version="1.0" type="device">
+    <hal format="hidl">
+        <name>android.hardware.tv.cec</name>
+        <transport>hwbinder</transport>
+        <version>1.1</version>
+        <interface>
+            <name>IHdmiCec</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+</manifest>
diff --git a/tv/cec/1.1/default/serviceMock.cpp b/tv/cec/1.1/default/serviceMock.cpp
new file mode 100644
index 0000000..72fc311
--- /dev/null
+++ b/tv/cec/1.1/default/serviceMock.cpp
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "android.hardware.tv.cec@1.1-service-shim"
+
+#include <android/hardware/tv/cec/1.1/IHdmiCec.h>
+#include <hidl/LegacySupport.h>
+#include "HdmiCecMock.h"
+
+using android::hardware::configureRpcThreadpool;
+using android::hardware::joinRpcThreadpool;
+using android::hardware::tv::cec::V1_1::IHdmiCec;
+using android::hardware::tv::cec::V1_1::implementation::HdmiCecMock;
+
+int main() {
+    configureRpcThreadpool(8, true /* callerWillJoin */);
+
+    // Setup hwbinder service
+    android::sp<IHdmiCec> service = new HdmiCecMock();
+    android::status_t status;
+    status = service->registerAsService();
+    LOG_ALWAYS_FATAL_IF(status != android::OK, "Error while registering mock cec service: %d",
+                        status);
+
+    joinRpcThreadpool();
+    return 0;
+}
diff --git a/tv/cec/1.1/types.hal b/tv/cec/1.1/types.hal
new file mode 100644
index 0000000..a117519
--- /dev/null
+++ b/tv/cec/1.1/types.hal
@@ -0,0 +1,45 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.tv.cec@1.1;
+
+import @1.0::CecLogicalAddress;
+import @1.0::CecMessageType;
+
+enum CecLogicalAddress : @1.0::CecLogicalAddress {
+    BACKUP_1 = 12,
+    BACKUP_2 = 13,
+};
+
+enum CecMessageType : @1.0::CecMessageType {
+    GIVE_FEATURES = 0xA5,
+    REPORT_FEATURES = 0xA6,
+    REQUEST_CURRENT_LATENCY = 0xA7,
+    REPORT_CURRENT_LATENCY = 0xA8,
+};
+
+struct CecMessage {
+    /** logical address of the initiator */
+    CecLogicalAddress initiator;
+
+    /** logical address of destination */
+    CecLogicalAddress destination;
+
+    /**
+     * The maximum size of body is 15 (MaxLength::MESSAGE_BODY) as specified in
+     * the section 6 of the CEC Spec 1.4b. Overflowed data must be ignored. */
+    vec<uint8_t> body;
+};
diff --git a/tv/cec/1.1/vts/functional/Android.bp b/tv/cec/1.1/vts/functional/Android.bp
new file mode 100644
index 0000000..5fc7093
--- /dev/null
+++ b/tv/cec/1.1/vts/functional/Android.bp
@@ -0,0 +1,14 @@
+cc_test {
+    name: "VtsHalTvCecV1_1TargetTest",
+    defaults: ["VtsHalTargetTestDefaults"],
+    srcs: ["VtsHalTvCecV1_1TargetTest.cpp"],
+    static_libs: [
+        "android.hardware.tv.cec@1.1",
+        "android.hardware.tv.cec@1.0",
+    ],
+    test_suites: [
+        "general-tests",
+        "vts",
+    ],
+    disable_framework: true,
+}
diff --git a/tv/cec/1.1/vts/functional/VtsHalTvCecV1_1TargetTest.cpp b/tv/cec/1.1/vts/functional/VtsHalTvCecV1_1TargetTest.cpp
new file mode 100644
index 0000000..1eb4643
--- /dev/null
+++ b/tv/cec/1.1/vts/functional/VtsHalTvCecV1_1TargetTest.cpp
@@ -0,0 +1,199 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "HdmiCec_hal_test"
+#include <android-base/logging.h>
+
+#include <android/hardware/tv/cec/1.1/IHdmiCec.h>
+#include <android/hardware/tv/cec/1.1/types.h>
+#include <utils/Log.h>
+#include <sstream>
+#include <vector>
+
+#include <gtest/gtest.h>
+#include <hidl/GtestPrinter.h>
+#include <hidl/ServiceManagement.h>
+
+using ::android::sp;
+using ::android::hardware::hidl_death_recipient;
+using ::android::hardware::hidl_vec;
+using ::android::hardware::Return;
+using ::android::hardware::Void;
+using ::android::hardware::tv::cec::V1_0::CecDeviceType;
+using ::android::hardware::tv::cec::V1_0::HdmiPortInfo;
+using ::android::hardware::tv::cec::V1_0::HdmiPortType;
+using ::android::hardware::tv::cec::V1_0::HotplugEvent;
+using ::android::hardware::tv::cec::V1_0::OptionKey;
+using ::android::hardware::tv::cec::V1_0::Result;
+using ::android::hardware::tv::cec::V1_0::SendMessageResult;
+using ::android::hardware::tv::cec::V1_1::CecLogicalAddress;
+using ::android::hardware::tv::cec::V1_1::CecMessage;
+using ::android::hardware::tv::cec::V1_1::IHdmiCec;
+using ::android::hardware::tv::cec::V1_1::IHdmiCecCallback;
+
+#define CEC_VERSION 0x05
+#define INCORRECT_VENDOR_ID 0x00
+
+// The main test class for TV CEC HAL.
+class HdmiCecTest : public ::testing::TestWithParam<std::string> {
+  public:
+    void SetUp() override {
+        hdmiCec = IHdmiCec::getService(GetParam());
+        ASSERT_NE(hdmiCec, nullptr);
+        ALOGI("%s: getService() for hdmiCec is %s", __func__,
+              hdmiCec->isRemote() ? "remote" : "local");
+
+        hdmiCec_death_recipient = new HdmiCecDeathRecipient();
+        hdmiCecCallback = new CecCallback();
+        ASSERT_NE(hdmiCec_death_recipient, nullptr);
+        ASSERT_TRUE(hdmiCec->linkToDeath(hdmiCec_death_recipient, 0).isOk());
+    }
+
+    std::vector<int> getDeviceTypes() {
+        std::vector<int> deviceTypes;
+        FILE* p = popen("getprop ro.hdmi.device_type", "re");
+        if (p) {
+            char* line = NULL;
+            size_t len = 0;
+            if (getline(&line, &len, p) > 0) {
+                std::istringstream stream(line);
+                std::string number{};
+                while (std::getline(stream, number, ',')) {
+                    deviceTypes.push_back(stoi(number));
+                }
+            }
+            pclose(p);
+        }
+        return deviceTypes;
+    }
+
+    bool hasDeviceType(CecDeviceType type) {
+        std::vector<int> deviceTypes = getDeviceTypes();
+        return std::find(deviceTypes.begin(), deviceTypes.end(), (int)type) != deviceTypes.end();
+    }
+
+    class CecCallback : public IHdmiCecCallback {
+      public:
+        Return<void> onCecMessage(
+                const ::android::hardware::tv::cec::V1_0::CecMessage& /* message */) {
+            return Void();
+        }
+        Return<void> onCecMessage_1_1(
+                const ::android::hardware::tv::cec::V1_1::CecMessage& /* message */) {
+            return Void();
+        }
+        Return<void> onHotplugEvent(
+                const ::android::hardware::tv::cec::V1_0::HotplugEvent& /* event */) {
+            return Void();
+        }
+    };
+
+    class HdmiCecDeathRecipient : public hidl_death_recipient {
+      public:
+        void serviceDied(uint64_t /*cookie*/,
+                         const android::wp<::android::hidl::base::V1_0::IBase>& /*who*/) override {
+            FAIL();
+        }
+    };
+
+    sp<IHdmiCec> hdmiCec;
+    sp<IHdmiCecCallback> hdmiCecCallback;
+    sp<HdmiCecDeathRecipient> hdmiCec_death_recipient;
+};
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(HdmiCecTest);
+INSTANTIATE_TEST_SUITE_P(
+        PerInstance, HdmiCecTest,
+        testing::ValuesIn(android::hardware::getAllHalInstanceNames(IHdmiCec::descriptor)),
+        android::hardware::PrintInstanceNameToString);
+
+TEST_P(HdmiCecTest, ClearAddLogicalAddress) {
+    hdmiCec->clearLogicalAddress();
+    Return<Result> ret = hdmiCec->addLogicalAddress_1_1(CecLogicalAddress::PLAYBACK_3);
+    EXPECT_EQ(ret, Result::SUCCESS);
+}
+
+TEST_P(HdmiCecTest, SendMessage) {
+    CecMessage message;
+    message.initiator = CecLogicalAddress::PLAYBACK_1;
+    message.destination = CecLogicalAddress::BROADCAST;
+    message.body.resize(1);
+    message.body[0] = 131;
+    SendMessageResult ret = hdmiCec->sendMessage_1_1(message);
+    EXPECT_EQ(ret, SendMessageResult::SUCCESS);
+}
+
+TEST_P(HdmiCecTest, CecVersion) {
+    Return<int32_t> ret = hdmiCec->getCecVersion();
+    EXPECT_GE(ret, CEC_VERSION);
+}
+
+TEST_P(HdmiCecTest, SetCallback) {
+    Return<void> ret = hdmiCec->setCallback_1_1(new CecCallback());
+    ASSERT_TRUE(ret.isOk());
+}
+
+TEST_P(HdmiCecTest, VendorId) {
+    Return<uint32_t> ret = hdmiCec->getVendorId();
+    EXPECT_NE(ret, INCORRECT_VENDOR_ID);
+}
+
+TEST_P(HdmiCecTest, GetPortInfo) {
+    hidl_vec<HdmiPortInfo> ports;
+    Return<void> ret =
+            hdmiCec->getPortInfo([&ports](hidl_vec<HdmiPortInfo> list) { ports = list; });
+    ASSERT_TRUE(ret.isOk());
+    bool cecSupportedOnDevice = false;
+    for (size_t i = 0; i < ports.size(); ++i) {
+        EXPECT_TRUE((ports[i].type == HdmiPortType::OUTPUT) ||
+                    (ports[i].type == HdmiPortType::INPUT));
+        if (ports[i].portId == 0) {
+            ALOGW("%s: Port id should start from 1", __func__);
+        }
+        cecSupportedOnDevice = cecSupportedOnDevice | ports[i].cecSupported;
+    }
+    EXPECT_NE(cecSupportedOnDevice, false) << "At least one port should support CEC";
+}
+
+TEST_P(HdmiCecTest, SetOption) {
+    Return<void> wakeup = hdmiCec->setOption(OptionKey::WAKEUP, false);
+    ASSERT_TRUE(wakeup.isOk());
+    Return<void> enableCec = hdmiCec->setOption(OptionKey::ENABLE_CEC, false);
+    ASSERT_TRUE(enableCec.isOk());
+    Return<void> systemCecControl = hdmiCec->setOption(OptionKey::SYSTEM_CEC_CONTROL, true);
+    ASSERT_TRUE(systemCecControl.isOk());
+    // Restore option keys to their default values
+    hdmiCec->setOption(OptionKey::WAKEUP, true);
+    hdmiCec->setOption(OptionKey::ENABLE_CEC, true);
+    hdmiCec->setOption(OptionKey::SYSTEM_CEC_CONTROL, false);
+}
+
+TEST_P(HdmiCecTest, SetLanguage) {
+    Return<void> ret = hdmiCec->setLanguage("eng");
+    ASSERT_TRUE(ret.isOk());
+}
+
+TEST_P(HdmiCecTest, EnableAudioReturnChannel) {
+    hidl_vec<HdmiPortInfo> ports;
+    Return<void> ret =
+            hdmiCec->getPortInfo([&ports](hidl_vec<HdmiPortInfo> list) { ports = list; });
+    for (size_t i = 0; i < ports.size(); ++i) {
+        if (ports[i].arcSupported) {
+            Return<void> ret = hdmiCec->enableAudioReturnChannel(ports[i].portId, true);
+            ASSERT_TRUE(ret.isOk());
+        }
+    }
+}
\ No newline at end of file
diff --git a/tv/tuner/1.1/default/Frontend.cpp b/tv/tuner/1.1/default/Frontend.cpp
index 6956f30..243891c 100644
--- a/tv/tuner/1.1/default/Frontend.cpp
+++ b/tv/tuner/1.1/default/Frontend.cpp
@@ -196,7 +196,7 @@
             }
             case FrontendStatusType::MODULATION: {
                 FrontendModulationStatus modulationStatus;
-                modulationStatus.isdbt(FrontendIsdbtModulation::MOD_16QAM);  // value = 1 << 3
+                modulationStatus.isdbs(FrontendIsdbsModulation::MOD_BPSK);  // value = 1 << 1
                 status.modulation(modulationStatus);
                 break;
             }
@@ -281,12 +281,14 @@
     for (int i = 0; i < statusTypes.size(); i++) {
         V1_1::FrontendStatusTypeExt1_1 type = statusTypes[i];
         V1_1::FrontendStatusExt1_1 status;
+
         // assign randomly selected values for testing.
+        // TODO: assign status values according to the frontend type
         switch (type) {
             case V1_1::FrontendStatusTypeExt1_1::MODULATIONS: {
                 vector<V1_1::FrontendModulation> modulations;
                 V1_1::FrontendModulation modulation;
-                modulation.isdbt(FrontendIsdbtModulation::MOD_16QAM);  // value = 1 << 3
+                modulation.isdbs(FrontendIsdbsModulation::MOD_BPSK);  // value = 1 << 1
                 modulations.push_back(modulation);
                 status.modulations(modulations);
                 break;
@@ -347,7 +349,7 @@
             }
             case V1_1::FrontendStatusTypeExt1_1::ROLL_OFF: {
                 V1_1::FrontendRollOff rollOff;
-                rollOff.dvbs(FrontendDvbsRolloff::ROLLOFF_0_35);
+                rollOff.isdbs(FrontendIsdbsRolloff::ROLLOFF_0_35);
                 status.rollOff(rollOff);
                 break;
             }
diff --git a/tv/tuner/1.1/default/Tuner.cpp b/tv/tuner/1.1/default/Tuner.cpp
index c3dcd1d..6cc9949 100644
--- a/tv/tuner/1.1/default/Tuner.cpp
+++ b/tv/tuner/1.1/default/Tuner.cpp
@@ -34,7 +34,7 @@
     // Static Frontends array to maintain local frontends information
     // Array index matches their FrontendId in the default impl
     mFrontendSize = 9;
-    mFrontends[0] = new Frontend(FrontendType::DVBT, 0, this);
+    mFrontends[0] = new Frontend(FrontendType::ISDBS, 0, this);
     mFrontends[1] = new Frontend(FrontendType::ATSC, 1, this);
     mFrontends[2] = new Frontend(FrontendType::DVBC, 2, this);
     mFrontends[3] = new Frontend(FrontendType::DVBS, 3, this);
@@ -47,7 +47,7 @@
 
     FrontendInfo::FrontendCapabilities caps;
     caps = FrontendInfo::FrontendCapabilities();
-    caps.dvbtCaps(FrontendDvbtCapabilities());
+    caps.isdbsCaps(FrontendIsdbsCapabilities());
     mFrontendCaps[0] = caps;
 
     caps = FrontendInfo::FrontendCapabilities();
@@ -168,6 +168,8 @@
             FrontendStatusType::PLP_ID,
             FrontendStatusType::LAYER_ERROR,
             FrontendStatusType::ATSC3_PLP_INFO,
+            static_cast<FrontendStatusType>(V1_1::FrontendStatusTypeExt1_1::MODULATIONS),
+            static_cast<FrontendStatusType>(V1_1::FrontendStatusTypeExt1_1::ROLL_OFF),
     };
     // assign randomly selected values for testing.
     info = {
diff --git a/usb/1.3/Android.bp b/usb/1.3/Android.bp
new file mode 100644
index 0000000..17367d3
--- /dev/null
+++ b/usb/1.3/Android.bp
@@ -0,0 +1,16 @@
+// This file is autogenerated by hidl-gen -Landroidbp.
+
+hidl_interface {
+    name: "android.hardware.usb@1.3",
+    root: "android.hardware",
+    srcs: [
+        "IUsb.hal",
+    ],
+    interfaces: [
+        "android.hardware.usb@1.0",
+        "android.hardware.usb@1.1",
+        "android.hardware.usb@1.2",
+        "android.hidl.base@1.0",
+    ],
+    gen_java: true,
+}
diff --git a/usb/1.3/IUsb.hal b/usb/1.3/IUsb.hal
new file mode 100644
index 0000000..3d1d380
--- /dev/null
+++ b/usb/1.3/IUsb.hal
@@ -0,0 +1,32 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.usb@1.3;
+
+import android.hardware.usb@1.2::IUsb;
+
+interface IUsb extends @1.2::IUsb {
+    /**
+     * This function is used to enable/disable USB controller when some
+     * scenarios need. This function can stop and restore USB data signaling.
+     *
+     * @param enable true Enable USB data signaling.
+     *               false Disable USB data signaling.
+     * @return true enable or disable USB data successfully
+     *         false if something wrong
+     */
+    enableUsbDataSignal(bool enable) generates(bool result);
+};
diff --git a/usb/1.3/vts/OWNERS b/usb/1.3/vts/OWNERS
new file mode 100644
index 0000000..a6a1e54
--- /dev/null
+++ b/usb/1.3/vts/OWNERS
@@ -0,0 +1,2 @@
+albertccwang@google.com
+badhri@google.com
diff --git a/usb/1.3/vts/functional/Android.bp b/usb/1.3/vts/functional/Android.bp
new file mode 100644
index 0000000..b62bb9d
--- /dev/null
+++ b/usb/1.3/vts/functional/Android.bp
@@ -0,0 +1,31 @@
+//
+// Copyright (C) 2021 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_test {
+    name: "VtsHalUsbV1_3TargetTest",
+    defaults: ["VtsHalTargetTestDefaults"],
+    srcs: ["VtsHalUsbV1_3TargetTest.cpp"],
+    static_libs: [
+        "android.hardware.usb@1.0",
+        "android.hardware.usb@1.1",
+        "android.hardware.usb@1.2",
+        "android.hardware.usb@1.3",
+    ],
+    test_suites: [
+        "general-tests",
+        "vts",
+    ],
+}
diff --git a/usb/1.3/vts/functional/VtsHalUsbV1_3TargetTest.cpp b/usb/1.3/vts/functional/VtsHalUsbV1_3TargetTest.cpp
new file mode 100644
index 0000000..ed35d42
--- /dev/null
+++ b/usb/1.3/vts/functional/VtsHalUsbV1_3TargetTest.cpp
@@ -0,0 +1,69 @@
+/*
+ * Copyright (C) 2021 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "VtsHalUsbV1_3TargetTest"
+#include <android-base/logging.h>
+
+#include <android/hardware/usb/1.3/IUsb.h>
+
+#include <gtest/gtest.h>
+#include <hidl/GtestPrinter.h>
+#include <hidl/ServiceManagement.h>
+
+#include <log/log.h>
+#include <stdlib.h>
+#include <condition_variable>
+
+using ::android::sp;
+using ::android::hardware::hidl_array;
+using ::android::hardware::hidl_memory;
+using ::android::hardware::hidl_string;
+using ::android::hardware::hidl_vec;
+using ::android::hardware::Return;
+using ::android::hardware::Void;
+using ::android::hardware::usb::V1_0::Status;
+using ::android::hardware::usb::V1_3::IUsb;
+using ::android::hidl::base::V1_0::IBase;
+
+// The main test class for the USB hidl HAL
+class UsbHidlTest : public ::testing::TestWithParam<std::string> {
+  public:
+    virtual void SetUp() override {
+        ALOGI(__FUNCTION__);
+        usb = IUsb::getService(GetParam());
+        ASSERT_NE(usb, nullptr);
+    }
+
+    virtual void TearDown() override { ALOGI("Teardown"); }
+
+    // USB hidl hal Proxy
+    sp<IUsb> usb;
+};
+
+/*
+ * Check to see if enable usb data signal succeeds.
+ * HAL service should call enableUsbDataSignal.
+ */
+TEST_P(UsbHidlTest, enableUsbDataSignal) {
+    Return<bool> ret = usb->enableUsbDataSignal(true);
+    ASSERT_TRUE(ret.isOk());
+}
+
+GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(UsbHidlTest);
+INSTANTIATE_TEST_SUITE_P(
+        PerInstance, UsbHidlTest,
+        testing::ValuesIn(android::hardware::getAllHalInstanceNames(IUsb::descriptor)),
+        android::hardware::PrintInstanceNameToString);
diff --git a/wifi/1.5/IWifiChip.hal b/wifi/1.5/IWifiChip.hal
index 209190a..5a3e288 100644
--- a/wifi/1.5/IWifiChip.hal
+++ b/wifi/1.5/IWifiChip.hal
@@ -236,19 +236,54 @@
     setCountryCode(int8_t[2] code) generates (WifiStatus status);
 
     /**
+     * Usable Wifi channels filter masks.
+     */
+    enum UsableChannelFilter : uint32_t {
+        /**
+         * Filter Wifi channels that should be avoided due to extreme
+         * cellular coexistence restrictions. Some Wifi channels can have
+         * extreme interference from/to cellular due to short frequency
+         * seperation with neighboring cellular channels or when there
+         * is harmonic and intermodulation interference. Channels which
+         * only have some performance degradation (e.g. power back off is
+         * sufficient to deal with coexistence issue) can be included and
+         * should not be filtered out.
+         */
+        CELLULAR_COEXISTENCE = 1 << 0,
+        /**
+         * Filter based on concurrency state.
+         * Examples:
+         * - 5GHz SAP operation may be supported in standalone mode, but if
+         *  there is STA connection on 5GHz DFS channel, none of the 5GHz
+         *  channels are usable for SAP if device does not support DFS SAP mode.
+         * - P2P GO may not be supported on indoor channels in EU during
+         *  standalone mode but if there is a STA connection on indoor channel,
+         *  P2P GO may be supported by some vendors on the same STA channel.
+         */
+        CONCURRENCY = 1 << 1,
+    };
+
+    /**
      * Retrieve list of usable Wifi channels for the specified band &
      * operational modes.
      *
      * The list of usable Wifi channels in a given band depends on factors
-     * like current country code, operational mode (e.g. STA, SAP, CLI, GO,
-     * TDLS, NAN) and any hard restrictons due to DFS, LTE Coex and
-     * MCC(multi channel-concurrency).
+     * like current country code, operational mode (e.g. STA, SAP, WFD-CLI,
+     * WFD-GO, TDLS, NAN) and other restrictons due to DFS, cellular coexistence
+     * and conncurency state of the device.
      *
      * @param band |WifiBand| for which list of usable channels is requested.
      * @param ifaceModeMask Bitmask of the modes represented by |WifiIfaceMode|
      *        Bitmask respresents all the modes that the caller is interested
-     *        in (e.g. STA, SAP, CLI, GO, TDLS, NAN).
-     *        Note: Bitmask does not represent concurrency matrix.
+     *        in (e.g. STA, SAP, CLI, GO, TDLS, NAN). E.g. If the caller is
+     *        interested in knowing usable channels for P2P CLI, P2P GO & NAN,
+     *        ifaceModeMask would be set to
+     *        IFACE_MODE_P2P_CLIENT|IFACE_MODE_P2P_GO|IFACE_MODE_NAN.
+     * @param filterMask Bitmask of filters represented by
+     *        |UsableChannelFilter|. Specifies whether driver should filter
+     *        channels based on additional criteria. If no filter is specified
+     *        driver should return usable channels purely based on regulatory
+     *        constraints.
      * @return status WifiStatus of the operation.
      *         Possible status codes:
      *         |WifiStatusCode.SUCCESS|,
@@ -257,10 +292,15 @@
      *         |WifiStatusCode.FAILURE_UNKNOWN|
      * @return channels List of channels represented by |WifiUsableChannel|
      *         Each entry represents a channel frequency, bandwidth and
-     *         bitmask of operational modes (e.g. STA, SAP, CLI, GO, TDLS, NAN)
-     *         allowed on that channel.
-     *         Note: Bitmask does not represent concurrency matrix.
+     *         bitmask of modes (e.g. STA, SAP, CLI, GO, TDLS, NAN) that are
+     *         allowed on that channel. E.g. If only STA mode can be supported
+     *         on an indoor channel, only the IFACE_MODE_STA bit would be set
+     *         for that channel. If 5GHz SAP cannot be supported, then none of
+     *         the 5GHz channels will have IFACE_MODE_SOFTAP bit set.
+     *         Note: Bits do not represent concurrency state. Each bit only
+     *         represents whether particular mode is allowed on that channel.
      */
-    getUsableChannels(WifiBand band, bitfield<WifiIfaceMode> ifaceModeMask)
+    getUsableChannels(WifiBand band, bitfield<WifiIfaceMode> ifaceModeMask,
+            bitfield<UsableChannelFilter> filterMask)
         generates (WifiStatus status, vec<WifiUsableChannel> channels);
 };
diff --git a/wifi/1.5/default/hidl_struct_util.cpp b/wifi/1.5/default/hidl_struct_util.cpp
index 7cee4cd..3c69da5 100644
--- a/wifi/1.5/default/hidl_struct_util.cpp
+++ b/wifi/1.5/default/hidl_struct_util.cpp
@@ -445,6 +445,20 @@
     return hidl_iface_mask;
 }
 
+uint32_t convertHidlUsableChannelFilterToLegacy(uint32_t hidl_filter_mask) {
+    uint32_t legacy_filter_mask = 0;
+    if (hidl_filter_mask &
+        IWifiChip::UsableChannelFilter::CELLULAR_COEXISTENCE) {
+        legacy_filter_mask |=
+            legacy_hal::WIFI_USABLE_CHANNEL_FILTER_CELLULAR_COEXISTENCE;
+    }
+    if (hidl_filter_mask & IWifiChip::UsableChannelFilter::CONCURRENCY) {
+        legacy_filter_mask |=
+            legacy_hal::WIFI_USABLE_CHANNEL_FILTER_CONCURRENCY;
+    }
+    return legacy_filter_mask;
+}
+
 bool convertLegacyWifiUsableChannelToHidl(
     const legacy_hal::wifi_usable_channel& legacy_usable_channel,
     V1_5::WifiUsableChannel* hidl_usable_channel) {
diff --git a/wifi/1.5/default/hidl_struct_util.h b/wifi/1.5/default/hidl_struct_util.h
index c0d7bf8..8b81033 100644
--- a/wifi/1.5/default/hidl_struct_util.h
+++ b/wifi/1.5/default/hidl_struct_util.h
@@ -208,6 +208,7 @@
     std::vector<V1_4::RttResult>* hidl_results);
 uint32_t convertHidlWifiBandToLegacyMacBand(V1_5::WifiBand band);
 uint32_t convertHidlWifiIfaceModeToLegacy(uint32_t hidl_iface_mask);
+uint32_t convertHidlUsableChannelFilterToLegacy(uint32_t hidl_filter_mask);
 bool convertLegacyWifiUsableChannelsToHidl(
     const std::vector<legacy_hal::wifi_usable_channel>& legacy_usable_channels,
     std::vector<V1_5::WifiUsableChannel>* hidl_usable_channels);
diff --git a/wifi/1.5/default/wifi_chip.cpp b/wifi/1.5/default/wifi_chip.cpp
index 2dc7314..0450a7b 100644
--- a/wifi/1.5/default/wifi_chip.cpp
+++ b/wifi/1.5/default/wifi_chip.cpp
@@ -740,10 +740,11 @@
 
 Return<void> WifiChip::getUsableChannels(
     WifiBand band, hidl_bitfield<WifiIfaceMode> ifaceModeMask,
+    hidl_bitfield<UsableChannelFilter> filterMask,
     getUsableChannels_cb _hidl_cb) {
     return validateAndCall(this, WifiStatusCode::ERROR_WIFI_CHIP_INVALID,
                            &WifiChip::getUsableChannelsInternal, _hidl_cb, band,
-                           ifaceModeMask);
+                           ifaceModeMask, filterMask);
 }
 
 void WifiChip::invalidateAndRemoveAllIfaces() {
@@ -1500,13 +1501,17 @@
 }
 
 std::pair<WifiStatus, std::vector<WifiUsableChannel>>
-WifiChip::getUsableChannelsInternal(WifiBand band, uint32_t ifaceModeMask) {
+WifiChip::getUsableChannelsInternal(WifiBand band, uint32_t ifaceModeMask,
+                                    uint32_t filterMask) {
     legacy_hal::wifi_error legacy_status;
     std::vector<legacy_hal::wifi_usable_channel> legacy_usable_channels;
     std::tie(legacy_status, legacy_usable_channels) =
         legacy_hal_.lock()->getUsableChannels(
             hidl_struct_util::convertHidlWifiBandToLegacyMacBand(band),
-            hidl_struct_util::convertHidlWifiIfaceModeToLegacy(ifaceModeMask));
+            hidl_struct_util::convertHidlWifiIfaceModeToLegacy(ifaceModeMask),
+            hidl_struct_util::convertHidlUsableChannelFilterToLegacy(
+                filterMask));
+
     if (legacy_status != legacy_hal::WIFI_SUCCESS) {
         return {createWifiStatusFromLegacyError(legacy_status), {}};
     }
diff --git a/wifi/1.5/default/wifi_chip.h b/wifi/1.5/default/wifi_chip.h
index d542792..b4ed30e 100644
--- a/wifi/1.5/default/wifi_chip.h
+++ b/wifi/1.5/default/wifi_chip.h
@@ -180,9 +180,10 @@
         setCoexUnsafeChannels_cb hidl_status_cb) override;
     Return<void> setCountryCode(const hidl_array<int8_t, 2>& code,
                                 setCountryCode_cb _hidl_cb) override;
-    Return<void> getUsableChannels(WifiBand band,
-                                   hidl_bitfield<WifiIfaceMode> ifaceModeMask,
-                                   getUsableChannels_cb _hidl_cb) override;
+    Return<void> getUsableChannels(
+        WifiBand band, hidl_bitfield<WifiIfaceMode> ifaceModeMask,
+        hidl_bitfield<UsableChannelFilter> filterMask,
+        getUsableChannels_cb _hidl_cb) override;
 
    private:
     void invalidateAndRemoveAllIfaces();
@@ -265,7 +266,8 @@
         std::vector<CoexUnsafeChannel> unsafe_channels, uint32_t restrictions);
     WifiStatus setCountryCodeInternal(const std::array<int8_t, 2>& code);
     std::pair<WifiStatus, std::vector<WifiUsableChannel>>
-    getUsableChannelsInternal(WifiBand band, uint32_t ifaceModeMask);
+    getUsableChannelsInternal(WifiBand band, uint32_t ifaceModeMask,
+                              uint32_t filterMask);
     WifiStatus handleChipConfiguration(
         std::unique_lock<std::recursive_mutex>* lock, ChipModeId mode_id);
     WifiStatus registerDebugRingBufferCallback();
diff --git a/wifi/1.5/default/wifi_legacy_hal.cpp b/wifi/1.5/default/wifi_legacy_hal.cpp
index 94603b3..f5ca753 100644
--- a/wifi/1.5/default/wifi_legacy_hal.cpp
+++ b/wifi/1.5/default/wifi_legacy_hal.cpp
@@ -1638,12 +1638,14 @@
 }
 
 std::pair<wifi_error, std::vector<wifi_usable_channel>>
-WifiLegacyHal::getUsableChannels(uint32_t band_mask, uint32_t iface_mode_mask) {
+WifiLegacyHal::getUsableChannels(uint32_t band_mask, uint32_t iface_mode_mask,
+                                 uint32_t filter_mask) {
     std::vector<wifi_usable_channel> channels;
     channels.resize(kMaxWifiUsableChannels);
     uint32_t size = 0;
     wifi_error status = global_func_table_.wifi_get_usable_channels(
-        global_handle_, band_mask, iface_mode_mask, channels.size(), &size,
+        global_handle_, band_mask, iface_mode_mask, filter_mask,
+        channels.size(), &size,
         reinterpret_cast<wifi_usable_channel*>(channels.data()));
     CHECK(size >= 0 && size <= kMaxWifiUsableChannels);
     channels.resize(size);
diff --git a/wifi/1.5/default/wifi_legacy_hal.h b/wifi/1.5/default/wifi_legacy_hal.h
index dc641ae..03ca841 100644
--- a/wifi/1.5/default/wifi_legacy_hal.h
+++ b/wifi/1.5/default/wifi_legacy_hal.h
@@ -313,6 +313,8 @@
 using ::wifi_tx_packet_fate;
 using ::wifi_tx_report;
 using ::wifi_usable_channel;
+using ::WIFI_USABLE_CHANNEL_FILTER_CELLULAR_COEXISTENCE;
+using ::WIFI_USABLE_CHANNEL_FILTER_CONCURRENCY;
 using ::WLAN_MAC_2_4_BAND;
 using ::WLAN_MAC_5_0_BAND;
 using ::WLAN_MAC_60_0_BAND;
@@ -705,7 +707,7 @@
     // Retrieve the list of usable channels in the requested bands
     // for the requested modes
     std::pair<wifi_error, std::vector<wifi_usable_channel>> getUsableChannels(
-        uint32_t band_mask, uint32_t iface_mode_mask);
+        uint32_t band_mask, uint32_t iface_mode_mask, uint32_t filter_mask);
 
    private:
     // Retrieve interface handles for all the available interfaces.
diff --git a/wifi/1.5/vts/functional/wifi_chip_hidl_test.cpp b/wifi/1.5/vts/functional/wifi_chip_hidl_test.cpp
index 509f1bd..5ac747d 100644
--- a/wifi/1.5/vts/functional/wifi_chip_hidl_test.cpp
+++ b/wifi/1.5/vts/functional/wifi_chip_hidl_test.cpp
@@ -195,10 +195,12 @@
 TEST_P(WifiChipHidlTest, getUsableChannels) {
     uint32_t ifaceModeMask =
         WifiIfaceMode::IFACE_MODE_P2P_CLIENT | WifiIfaceMode::IFACE_MODE_P2P_GO;
+    uint32_t filterMask = IWifiChip::UsableChannelFilter::CELLULAR_COEXISTENCE |
+                          IWifiChip::UsableChannelFilter::CONCURRENCY;
     configureChipForIfaceType(IfaceType::STA, true);
     WifiBand band = WifiBand::BAND_24GHZ_5GHZ_6GHZ;
-    const auto& statusNonEmpty =
-        HIDL_INVOKE(wifi_chip_, getUsableChannels, band, ifaceModeMask);
+    const auto& statusNonEmpty = HIDL_INVOKE(wifi_chip_, getUsableChannels,
+                                             band, ifaceModeMask, filterMask);
     if (statusNonEmpty.first.code != WifiStatusCode::SUCCESS) {
         EXPECT_EQ(WifiStatusCode::ERROR_NOT_SUPPORTED,
                   statusNonEmpty.first.code);