Merge "WiFi: Get contention time stats from wifi_wmm_ac_stat in link_layer_stats" into sc-dev
diff --git a/audio/7.0/config/Android.bp b/audio/7.0/config/Android.bp
index f67cc7c..4a46795 100644
--- a/audio/7.0/config/Android.bp
+++ b/audio/7.0/config/Android.bp
@@ -4,3 +4,19 @@
package_name: "android.audio.policy.configuration.V7_0",
nullability: true,
}
+
+xsd_config {
+ name: "audio_policy_configuration_V7_0_enums",
+ srcs: ["audio_policy_configuration.xsd"],
+ package_name: "android.audio.policy.configuration.V7_0",
+ nullability: true,
+ enums_only: true,
+}
+
+xsd_config {
+ name: "audio_policy_configuration_V7_0_parser",
+ srcs: ["audio_policy_configuration.xsd"],
+ package_name: "android.audio.policy.configuration.V7_0",
+ nullability: true,
+ parser_only: true,
+}
diff --git a/audio/7.0/config/audio_policy_configuration.xsd b/audio/7.0/config/audio_policy_configuration.xsd
index 31ec64b..ee51aa8 100644
--- a/audio/7.0/config/audio_policy_configuration.xsd
+++ b/audio/7.0/config/audio_policy_configuration.xsd
@@ -311,13 +311,17 @@
</xs:restriction>
</xs:simpleType>
<xs:simpleType name="vendorExtension">
- <!-- Vendor extension names must be prefixed by "VX_" to distinguish them from AOSP values.
- Vendor are encouraged to namespace their module names to avoid conflicts.
- Example for an hypothetical Google virtual reality device:
- <devicePort tagName="VR" type="VX_GOOGLE_VR" role="sink">
+ <!-- Vendor extension names must be prefixed by "VX_" to distinguish them from
+ AOSP values. Vendors must namespace their names to avoid conflicts. The
+ namespace part must only use capital latin characters and decimal digits and
+ consist of at least 3 characters. The part of the extension name after the
+ namespace may in addition include underscores. Example for a hypothetical
+ Google virtual reality device:
+
+ <devicePort tagName="VR" type="VX_GOOGLE_VR" role="sink" />
-->
<xs:restriction base="xs:string">
- <xs:pattern value="VX_[_a-zA-Z0-9]+"/>
+ <xs:pattern value="VX_[A-Z0-9]{3,}_[_A-Z0-9]+"/>
</xs:restriction>
</xs:simpleType>
<xs:simpleType name="extendableAudioDevice">
diff --git a/audio/common/7.0/Android.bp b/audio/common/7.0/Android.bp
index 1c016b4..47f031f 100644
--- a/audio/common/7.0/Android.bp
+++ b/audio/common/7.0/Android.bp
@@ -16,15 +16,14 @@
cc_library {
name: "android.hardware.audio.common@7.0-enums",
vendor_available: true,
- generated_headers: ["audio_policy_configuration_V7_0"],
- generated_sources: ["audio_policy_configuration_V7_0"],
+ generated_headers: ["audio_policy_configuration_V7_0_enums"],
+ generated_sources: ["audio_policy_configuration_V7_0_enums"],
header_libs: ["libxsdc-utils"],
- export_generated_headers: ["audio_policy_configuration_V7_0"],
+ export_generated_headers: ["audio_policy_configuration_V7_0_enums"],
export_header_lib_headers: ["libxsdc-utils"],
export_include_dirs: ["enums/include"],
shared_libs: [
"libbase",
"liblog",
- "libxml2",
],
}
diff --git a/audio/common/7.0/enums/include/android_audio_policy_configuration_V7_0-enums.h b/audio/common/7.0/enums/include/android_audio_policy_configuration_V7_0-enums.h
index b427f3a..fe8eee1 100644
--- a/audio/common/7.0/enums/include/android_audio_policy_configuration_V7_0-enums.h
+++ b/audio/common/7.0/enums/include/android_audio_policy_configuration_V7_0-enums.h
@@ -14,14 +14,14 @@
* limitations under the License.
*/
-#ifndef ANDROID_AUDIO_POLICY_CONFIGURATION_V7_0_ENUMS_H
-#define ANDROID_AUDIO_POLICY_CONFIGURATION_V7_0_ENUMS_H
+#ifndef ANDROID_AUDIO_POLICY_CONFIGURATION_V7_0__ENUMS_H
+#define ANDROID_AUDIO_POLICY_CONFIGURATION_V7_0__ENUMS_H
#include <sys/types.h>
-#include <algorithm>
-#include <cctype>
+#include <regex>
+#include <string>
-#include <android_audio_policy_configuration_V7_0.h>
+#include <android_audio_policy_configuration_V7_0_enums.h>
namespace android::audio::policy::configuration::V7_0 {
@@ -219,11 +219,9 @@
}
static inline bool isVendorExtension(const std::string& s) {
- // Must match the "vendorExtension" rule from the XSD file.
- static const std::string vendorPrefix = "VX_";
- return maybeVendorExtension(s) &&
- std::all_of(s.begin() + vendorPrefix.size(), s.end(),
- [](unsigned char c) { return c == '_' || std::isalnum(c); });
+ // Must be the same as the "vendorExtension" rule from the XSD file.
+ static const std::regex vendorExtension("VX_[A-Z0-9]{3,}_[_A-Z0-9]+");
+ return std::regex_match(s.begin(), s.end(), vendorExtension);
}
static inline bool isUnknownAudioChannelMask(const std::string& mask) {
@@ -264,4 +262,4 @@
} // namespace android::audio::policy::configuration::V7_0
-#endif // ANDROID_AUDIO_POLICY_CONFIGURATION_V7_0_ENUMS_H
+#endif // ANDROID_AUDIO_POLICY_CONFIGURATION_V7_0__ENUMS_H
diff --git a/audio/common/7.0/example/Android.bp b/audio/common/7.0/example/Android.bp
index 03c1cd8..a6ae560 100644
--- a/audio/common/7.0/example/Android.bp
+++ b/audio/common/7.0/example/Android.bp
@@ -35,7 +35,6 @@
"libcutils",
"libhidlbase",
"liblog",
- "libxml2",
"libutils",
"android.hardware.audio@7.0",
"android.hardware.audio.common@7.0",
diff --git a/audio/common/7.0/example/Effect.cpp b/audio/common/7.0/example/Effect.cpp
index 5788811..0621669 100644
--- a/audio/common/7.0/example/Effect.cpp
+++ b/audio/common/7.0/example/Effect.cpp
@@ -17,7 +17,7 @@
#define LOG_TAG "EffectsFactory7.0"
#include <log/log.h>
-#include <android_audio_policy_configuration_V7_0.h>
+#include <android_audio_policy_configuration_V7_0-enums.h>
#include "Effect.h"
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..9afc95a 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"],
@@ -140,7 +140,6 @@
"android.hardware.audio.common@7.0",
"android.hardware.audio.common@7.0-enums",
"libbase",
- "libxml2",
],
cflags: [
"-DMAJOR_VERSION=7",
@@ -152,6 +151,32 @@
// 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..e154453 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) {
@@ -432,10 +432,16 @@
// The enums module is too small to have unit tests on its own.
TEST(HidlUtils, VendorExtension) {
EXPECT_TRUE(xsd::isVendorExtension("VX_GOOGLE_VR_42"));
+ EXPECT_TRUE(xsd::isVendorExtension("VX_QCM_SPK"));
EXPECT_FALSE(xsd::isVendorExtension(""));
EXPECT_FALSE(xsd::isVendorExtension("random string"));
EXPECT_FALSE(xsd::isVendorExtension("VX_"));
+ EXPECT_FALSE(xsd::isVendorExtension("VX_X"));
+ EXPECT_FALSE(xsd::isVendorExtension("VX_X_"));
+ EXPECT_FALSE(xsd::isVendorExtension("VX_X_X"));
+ EXPECT_FALSE(xsd::isVendorExtension("VX_XX_X"));
EXPECT_FALSE(xsd::isVendorExtension("VX_GOOGLE_$$"));
+ EXPECT_FALSE(xsd::isVendorExtension("VX_$CM_SPK"));
}
TEST(HidlUtils, ConvertInvalidDeviceAddress) {
@@ -476,6 +482,11 @@
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 +671,18 @@
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/default/Android.bp b/audio/core/all-versions/default/Android.bp
index e0f0894..0222bee 100644
--- a/audio/core/all-versions/default/Android.bp
+++ b/audio/core/all-versions/default/Android.bp
@@ -138,7 +138,6 @@
"android.hardware.audio.common@7.0-enums",
"android.hardware.audio.common@7.0-util",
"libbase",
- "libxml2",
],
cflags: [
"-DMAJOR_VERSION=7",
diff --git a/audio/core/all-versions/default/util/Android.bp b/audio/core/all-versions/default/util/Android.bp
index 447184b..ee80bbb 100644
--- a/audio/core/all-versions/default/util/Android.bp
+++ b/audio/core/all-versions/default/util/Android.bp
@@ -95,7 +95,6 @@
"android.hardware.audio.common@7.0-util",
"android.hardware.audio@7.0",
"libbase",
- "libxml2",
],
cflags: [
"-DMAJOR_VERSION=7",
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/audio/core/all-versions/vts/functional/Android.bp b/audio/core/all-versions/vts/functional/Android.bp
index e8b704c..8cea3cb 100644
--- a/audio/core/all-versions/vts/functional/Android.bp
+++ b/audio/core/all-versions/vts/functional/Android.bp
@@ -146,6 +146,8 @@
srcs: [
"7.0/AudioPrimaryHidlHalTest.cpp",
],
+ generated_headers: ["audio_policy_configuration_V7_0_parser"],
+ generated_sources: ["audio_policy_configuration_V7_0_parser"],
static_libs: [
"android.hardware.audio@7.0",
"android.hardware.audio.common@7.0",
diff --git a/audio/effect/all-versions/vts/functional/VtsHalAudioEffectTargetTest.cpp b/audio/effect/all-versions/vts/functional/VtsHalAudioEffectTargetTest.cpp
index 15a2fd9..23e7786 100644
--- a/audio/effect/all-versions/vts/functional/VtsHalAudioEffectTargetTest.cpp
+++ b/audio/effect/all-versions/vts/functional/VtsHalAudioEffectTargetTest.cpp
@@ -31,7 +31,6 @@
#include <android/hidl/memory/1.0/IMemory.h>
#if MAJOR_VERSION >= 7
#include <android_audio_policy_configuration_V7_0-enums.h>
-#include <android_audio_policy_configuration_V7_0.h>
#endif
#include <common/all-versions/VersionUtils.h>
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/vehicle/2.0/types.hal b/automotive/vehicle/2.0/types.hal
index ed75e1d..e3fd16d 100644
--- a/automotive/vehicle/2.0/types.hal
+++ b/automotive/vehicle/2.0/types.hal
@@ -354,6 +354,12 @@
/**
* Speed of the vehicle
*
+ * The value must be positive when the vehicle is moving forward and negative when
+ * the vehicle is moving backward. This value is independent of gear value
+ * (CURRENT_GEAR or GEAR_SELECTION), for example, if GEAR_SELECTION is GEAR_NEUTRAL,
+ * PERF_VEHICLE_SPEED is positive when the vehicle is moving forward, negative when moving
+ * backward, and zero when not moving.
+ *
* @change_mode VehiclePropertyChangeMode:CONTINUOUS
* @access VehiclePropertyAccess:READ
* @unit VehicleUnit:METER_PER_SEC
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/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/IFace.aidl b/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/IFace.aidl
index 37345ec..bfaf90d 100644
--- a/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/IFace.aidl
+++ b/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/IFace.aidl
@@ -35,4 +35,5 @@
interface IFace {
android.hardware.biometrics.face.SensorProps[] getSensorProps();
android.hardware.biometrics.face.ISession createSession(in int sensorId, in int userId, in android.hardware.biometrics.face.ISessionCallback cb);
+ void reset();
}
diff --git a/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/ISession.aidl b/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/ISession.aidl
index b855a9e..c9165e1 100644
--- a/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/ISession.aidl
+++ b/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/ISession.aidl
@@ -45,4 +45,5 @@
void getAuthenticatorId(in int cookie);
void invalidateAuthenticatorId(in int cookie);
void resetLockout(in int cookie, in android.hardware.keymaster.HardwareAuthToken hat);
+ void close(in int cookie);
}
diff --git a/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/SessionState.aidl b/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/SessionState.aidl
index 46751d0..3792eae 100644
--- a/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/SessionState.aidl
+++ b/biometrics/face/aidl/aidl_api/android.hardware.biometrics.face/current/android/hardware/biometrics/face/SessionState.aidl
@@ -34,7 +34,7 @@
@Backing(type="byte") @VintfStability
enum SessionState {
IDLING = 0,
- TERMINATED = 1,
+ CLOSED = 1,
GENERATING_CHALLENGE = 2,
REVOKING_CHALLENGE = 3,
ENROLLING = 4,
diff --git a/biometrics/face/aidl/android/hardware/biometrics/face/IFace.aidl b/biometrics/face/aidl/android/hardware/biometrics/face/IFace.aidl
index f9ed4b1..afb7c8d 100644
--- a/biometrics/face/aidl/android/hardware/biometrics/face/IFace.aidl
+++ b/biometrics/face/aidl/android/hardware/biometrics/face/IFace.aidl
@@ -35,6 +35,10 @@
* Creates a session that can be used by the framework to perform operations such as
* enroll, authenticate, etc. for the given sensorId and userId.
*
+ * Calling this method while there is an active session is considered an error. If the
+ * framework is in a bad state and for some reason cannot close its session, it should use
+ * the reset method below.
+ *
* Implementations must store user-specific state or metadata in /data/vendor_de/<user>/facedata
* as specified by the SELinux policy. The directory /data/vendor_de is managed by vold (see
* vold_prepare_subdirs.cpp). Implementations may store additional user-specific data, such as
@@ -47,4 +51,13 @@
*/
ISession createSession(in int sensorId, in int userId, in ISessionCallback cb);
+ /**
+ * Resets the HAL into a clean state, forcing it to cancel all of the pending operations, close
+ * its current session, and release all of the acquired resources.
+ *
+ * This should be used as a last resort to recover the HAL if the current session becomes
+ * unresponsive. The implementation might choose to restart the HAL process to get back into a
+ * good state.
+ */
+ void reset();
}
diff --git a/biometrics/face/aidl/android/hardware/biometrics/face/ISession.aidl b/biometrics/face/aidl/android/hardware/biometrics/face/ISession.aidl
index f540502..6f2014a 100644
--- a/biometrics/face/aidl/android/hardware/biometrics/face/ISession.aidl
+++ b/biometrics/face/aidl/android/hardware/biometrics/face/ISession.aidl
@@ -17,19 +17,20 @@
package android.hardware.biometrics.face;
import android.hardware.biometrics.common.ICancellationSignal;
-import android.hardware.biometrics.face.Feature;
import android.hardware.biometrics.face.EnrollmentType;
-import android.hardware.keymaster.HardwareAuthToken;
+import android.hardware.biometrics.face.Feature;
import android.hardware.common.NativeHandle;
+import android.hardware.keymaster.HardwareAuthToken;
-/** * A session is a collection of immutable state (sensorId, userId), mutable state (SessionState),
+/**
+ * A session is a collection of immutable state (sensorId, userId), mutable state (SessionState),
* methods available for the framework to call, and a callback (ISessionCallback) to notify the
* framework about the events and results. A session is used to establish communication between
* the framework and the HAL.
*/
@VintfStability
interface ISession {
- /**
+ /**
* generateChallenge:
*
* Begins a secure transaction request. Note that the challenge by itself is not useful. It only
@@ -134,9 +135,9 @@
* @param hat See above documentation.
* @param enrollmentType See the EnrollmentType enum.
* @param features See the Feature enum.
- * @param previewSurface A surface provided by the framework if SensorProps#halControlsPreview is
- * set to true. The HAL must send the preview frames to previewSurface if
- * it's not null.
+ * @param previewSurface A surface provided by the framework if SensorProps#halControlsPreview
+ * is set to true. The HAL must send the preview frames to previewSurface
+ * if it's not null.
* @return ICancellationSignal An object that can be used by the framework to cancel this
* operation.
*/
@@ -420,5 +421,22 @@
* @param hat HardwareAuthToken See above documentation.
*/
void resetLockout(in int cookie, in HardwareAuthToken hat);
-}
+ /*
+ * Close this session and allow the HAL to release the resources associated with this session.
+ *
+ * A session can only be closed when it's in SessionState::IDLING. Closing a session will
+ * result in a ISessionCallback#onStateChanged call with SessionState::CLOSED.
+ *
+ * If a session is unresponsive or stuck in a state other than SessionState::CLOSED,
+ * IFace#reset could be used as a last resort to terminate the session and recover the HAL
+ * from a bad state.
+ *
+ * All sessions must be explicitly closed. Calling IFace#createSession while there is an active
+ * session is considered an error.
+ *
+ * @param cookie An identifier used to track subsystem operations related to this call path. The
+ * client must guarantee that it is unique per ISession.
+ */
+ void close(in int cookie);
+}
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/android/hardware/biometrics/face/SessionState.aidl b/biometrics/face/aidl/android/hardware/biometrics/face/SessionState.aidl
index 7675564..afde4eb 100644
--- a/biometrics/face/aidl/android/hardware/biometrics/face/SessionState.aidl
+++ b/biometrics/face/aidl/android/hardware/biometrics/face/SessionState.aidl
@@ -25,9 +25,9 @@
IDLING,
/**
- * The session has been terminated by the HAL.
+ * The session has been closed by the client.
*/
- TERMINATED,
+ CLOSED,
/**
* The HAL is processing the ISession#generateChallenge request.
@@ -89,4 +89,3 @@
*/
RESETTING_LOCKOUT
}
-
diff --git a/biometrics/face/aidl/default/Face.cpp b/biometrics/face/aidl/default/Face.cpp
index 773359e..2b40850 100644
--- a/biometrics/face/aidl/default/Face.cpp
+++ b/biometrics/face/aidl/default/Face.cpp
@@ -63,4 +63,8 @@
return ndk::ScopedAStatus::ok();
}
+ndk::ScopedAStatus Face::reset() {
+ return ndk::ScopedAStatus::ok();
+}
+
} // namespace aidl::android::hardware::biometrics::face
diff --git a/biometrics/face/aidl/default/Face.h b/biometrics/face/aidl/default/Face.h
index 786b4f8..809b856 100644
--- a/biometrics/face/aidl/default/Face.h
+++ b/biometrics/face/aidl/default/Face.h
@@ -27,6 +27,8 @@
ndk::ScopedAStatus createSession(int32_t sensorId, int32_t userId,
const std::shared_ptr<ISessionCallback>& cb,
std::shared_ptr<ISession>* _aidl_return) override;
+
+ ndk::ScopedAStatus reset() override;
};
} // namespace aidl::android::hardware::biometrics::face
diff --git a/biometrics/face/aidl/default/Session.cpp b/biometrics/face/aidl/default/Session.cpp
index 63d1721..a7130e6 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();
@@ -129,4 +142,8 @@
return ndk::ScopedAStatus::ok();
}
+ndk::ScopedAStatus Session::close(int32_t /*cookie*/) {
+ return ndk::ScopedAStatus::ok();
+}
+
} // namespace aidl::android::hardware::biometrics::face
diff --git a/biometrics/face/aidl/default/Session.h b/biometrics/face/aidl/default/Session.h
index 83cb064..0651726 100644
--- a/biometrics/face/aidl/default/Session.h
+++ b/biometrics/face/aidl/default/Session.h
@@ -63,6 +63,8 @@
ndk::ScopedAStatus resetLockout(int32_t cookie,
const keymaster::HardwareAuthToken& hat) override;
+ ndk::ScopedAStatus close(int32_t cookie) override;
+
private:
std::shared_ptr<ISessionCallback> cb_;
};
diff --git a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/IFingerprint.aidl b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/IFingerprint.aidl
index c5a5422..2d44528 100644
--- a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/IFingerprint.aidl
+++ b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/IFingerprint.aidl
@@ -35,4 +35,5 @@
interface IFingerprint {
android.hardware.biometrics.fingerprint.SensorProps[] getSensorProps();
android.hardware.biometrics.fingerprint.ISession createSession(in int sensorId, in int userId, in android.hardware.biometrics.fingerprint.ISessionCallback cb);
+ void reset();
}
diff --git a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/ISession.aidl b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/ISession.aidl
index be0029c..b583006 100644
--- a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/ISession.aidl
+++ b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/ISession.aidl
@@ -43,6 +43,7 @@
void getAuthenticatorId(in int cookie);
void invalidateAuthenticatorId(in int cookie);
void resetLockout(in int cookie, in android.hardware.keymaster.HardwareAuthToken hat);
+ void close(in int cookie);
void onPointerDown(in int pointerId, in int x, in int y, in float minor, in float major);
void onPointerUp(in int pointerId);
void onUiReady();
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/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SessionState.aidl b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SessionState.aidl
index 44323ff..05dd85b 100644
--- a/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SessionState.aidl
+++ b/biometrics/fingerprint/aidl/aidl_api/android.hardware.biometrics.fingerprint/current/android/hardware/biometrics/fingerprint/SessionState.aidl
@@ -34,14 +34,15 @@
@Backing(type="byte") @VintfStability
enum SessionState {
IDLING = 0,
- GENERATING_CHALLENGE = 1,
- REVOKING_CHALLENGE = 2,
- ENROLLING = 3,
- AUTHENTICATING = 4,
- DETECTING_INTERACTION = 5,
- ENUMERATING_ENROLLMENTS = 6,
- REMOVING_ENROLLMENTS = 7,
- GETTING_AUTHENTICATOR_ID = 8,
- INVALIDATING_AUTHENTICATOR_ID = 9,
- RESETTING_LOCKOUT = 10,
+ CLOSED = 1,
+ GENERATING_CHALLENGE = 2,
+ REVOKING_CHALLENGE = 3,
+ ENROLLING = 4,
+ AUTHENTICATING = 5,
+ DETECTING_INTERACTION = 6,
+ ENUMERATING_ENROLLMENTS = 7,
+ REMOVING_ENROLLMENTS = 8,
+ GETTING_AUTHENTICATOR_ID = 9,
+ INVALIDATING_AUTHENTICATOR_ID = 10,
+ RESETTING_LOCKOUT = 11,
}
diff --git a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/IFingerprint.aidl b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/IFingerprint.aidl
index 3675aa4..37062ba 100644
--- a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/IFingerprint.aidl
+++ b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/IFingerprint.aidl
@@ -35,6 +35,10 @@
* Creates a session which can then be used by the framework to perform operations such as
* enroll, authenticate, etc for the given sensorId and userId.
*
+ * Calling this method while there is an active session is considered an error. If the
+ * framework is in a bad state and for some reason cannot close its session, it should use
+ * the reset method below.
+ *
* A physical sensor identified by sensorId typically supports only a single in-flight session
* at a time. As such, if a session is currently in a state other than SessionState::IDLING, the
* HAL MUST finish or cancel the current operation and return to SessionState::IDLING before the
@@ -61,4 +65,14 @@
* @return A new session
*/
ISession createSession(in int sensorId, in int userId, in ISessionCallback cb);
+
+ /**
+ * Resets the HAL into a clean state, forcing it to cancel all of the pending operations, close
+ * its current session, and release all of the acquired resources.
+ *
+ * This should be used as a last resort to recover the HAL if the current session becomes
+ * unresponsive. The implementation might choose to restart the HAL process to get back into a
+ * good state.
+ */
+ void reset();
}
diff --git a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/ISession.aidl b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/ISession.aidl
index f9c3732..ab7930d 100644
--- a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/ISession.aidl
+++ b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/ISession.aidl
@@ -366,6 +366,24 @@
*/
void resetLockout(in int cookie, in HardwareAuthToken hat);
+ /*
+ * Close this session and allow the HAL to release the resources associated with this session.
+ *
+ * A session can only be closed when it's in SessionState::IDLING. Closing a session will
+ * result in a ISessionCallback#onStateChanged call with SessionState::CLOSED.
+ *
+ * If a session is unresponsive or stuck in a state other than SessionState::CLOSED,
+ * IFingerprint#reset could be used as a last resort to terminate the session and recover the
+ * HAL from a bad state.
+ *
+ * All sessions must be explicitly closed. Calling IFingerprint#createSession while there is an
+ * active session is considered an error.
+ *
+ * @param cookie An identifier used to track subsystem operations related to this call path. The
+ * client must guarantee that it is unique per ISession.
+ */
+ void close(in int cookie);
+
/**
* Methods for notifying the under-display fingerprint sensor about external events.
*/
@@ -420,4 +438,3 @@
*/
void onUiReady();
}
-
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/android/hardware/biometrics/fingerprint/SessionState.aidl b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SessionState.aidl
index 1de01ad..19a6ce3 100644
--- a/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SessionState.aidl
+++ b/biometrics/fingerprint/aidl/android/hardware/biometrics/fingerprint/SessionState.aidl
@@ -25,6 +25,11 @@
IDLING,
/**
+ * The session has been closed by the client.
+ */
+ CLOSED,
+
+ /**
* The HAL is processing the ISession#generateChallenge request.
*/
GENERATING_CHALLENGE,
@@ -74,4 +79,3 @@
*/
RESETTING_LOCKOUT
}
-
diff --git a/biometrics/fingerprint/aidl/default/Android.bp b/biometrics/fingerprint/aidl/default/Android.bp
index c8cb663..6b43bff 100644
--- a/biometrics/fingerprint/aidl/default/Android.bp
+++ b/biometrics/fingerprint/aidl/default/Android.bp
@@ -1,18 +1,34 @@
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: [
+ "CancellationSignal.cpp",
+ "Fingerprint.cpp",
+ "Session.cpp",
+ "WorkerThread.cpp",
+ "main.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/CancellationSignal.cpp b/biometrics/fingerprint/aidl/default/CancellationSignal.cpp
new file mode 100644
index 0000000..6598316
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/CancellationSignal.cpp
@@ -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.
+ */
+
+#include "CancellationSignal.h"
+
+#include <android-base/logging.h>
+#include <chrono>
+
+namespace aidl::android::hardware::biometrics::fingerprint {
+
+CancellationSignal::CancellationSignal(std::promise<void>&& cancellationPromise)
+ : mCancellationPromise(std::move(cancellationPromise)) {}
+
+ndk::ScopedAStatus CancellationSignal::cancel() {
+ mCancellationPromise.set_value();
+ return ndk::ScopedAStatus::ok();
+}
+
+bool shouldCancel(const std::future<void>& f) {
+ CHECK(f.valid());
+ return f.wait_for(std::chrono::seconds(0)) == std::future_status::ready;
+}
+
+} // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/Fingerprint.cpp b/biometrics/fingerprint/aidl/default/Fingerprint.cpp
index 6eb35d9..67dc34f 100644
--- a/biometrics/fingerprint/aidl/default/Fingerprint.cpp
+++ b/biometrics/fingerprint/aidl/default/Fingerprint.cpp
@@ -15,49 +15,61 @@
*/
#include "Fingerprint.h"
+
#include "Session.h"
namespace aidl::android::hardware::biometrics::fingerprint {
+namespace {
+constexpr size_t MAX_WORKER_QUEUE_SIZE = 5;
+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";
-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";
+} // namespace
-ndk::ScopedAStatus Fingerprint::getSensorProps(std::vector<SensorProps>* return_val) {
- *return_val = std::vector<SensorProps>();
+Fingerprint::Fingerprint()
+ : mEngine(std::make_unique<FakeFingerprintEngine>()), mWorker(MAX_WORKER_QUEUE_SIZE) {}
- 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);
+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*/,
+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) {
+ auto sessionSp = mSession.lock();
+ CHECK(sessionSp == nullptr || sessionSp->isClosed()) << "Open session already exists!";
+
+ auto session = SharedRefBase::make<Session>(sensorId, userId, cb, mEngine.get(), &mWorker);
+ mSession = session;
+ *out = session;
return ndk::ScopedAStatus::ok();
}
+
+ndk::ScopedAStatus Fingerprint::reset() {
+ // Crash. The system will start a fresh instance of the HAL.
+ CHECK(false) << "Unable to reset. Crashing.";
+ 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..f6a0314 100644
--- a/biometrics/fingerprint/aidl/default/Session.cpp
+++ b/biometrics/fingerprint/aidl/default/Session.cpp
@@ -14,90 +14,233 @@
* limitations under the License.
*/
-#include <aidl/android/hardware/biometrics/common/BnCancellationSignal.h>
-
#include "Session.h"
+#include <android-base/logging.h>
+
+#include "CancellationSignal.h"
+
namespace aidl::android::hardware::biometrics::fingerprint {
-class CancellationSignal : public common::BnCancellationSignal {
- public:
- ndk::ScopedAStatus cancel() override { return ndk::ScopedAStatus::ok(); }
-};
+Session::Session(int sensorId, int userId, std::shared_ptr<ISessionCallback> cb,
+ FakeFingerprintEngine* engine, WorkerThread* worker)
+ : mSensorId(sensorId),
+ mUserId(userId),
+ mCb(std::move(cb)),
+ mEngine(engine),
+ mWorker(worker),
+ mScheduledState(SessionState::IDLING),
+ mCurrentState(SessionState::IDLING) {
+ CHECK_GE(mSensorId, 0);
+ CHECK_GE(mUserId, 0);
+ CHECK(mEngine);
+ CHECK(mWorker);
+ CHECK(mCb);
+}
-Session::Session(std::shared_ptr<ISessionCallback> cb) : cb_(std::move(cb)) {}
+void Session::scheduleStateOrCrash(SessionState state) {
+ CHECK(mScheduledState == SessionState::IDLING);
+ CHECK(mCurrentState == SessionState::IDLING);
+ mScheduledState = state;
+}
-ndk::ScopedAStatus Session::generateChallenge(int32_t /*cookie*/, int32_t /*timeoutSec*/) {
+void Session::enterStateOrCrash(int cookie, SessionState state) {
+ CHECK(mScheduledState == state);
+ mCurrentState = mScheduledState;
+ mScheduledState = SessionState::IDLING;
+ mCb->onStateChanged(cookie, mCurrentState);
+}
+
+void Session::enterIdling(int cookie) {
+ mCurrentState = SessionState::IDLING;
+ mCb->onStateChanged(cookie, mCurrentState);
+}
+
+bool Session::isClosed() {
+ return mCurrentState == SessionState::CLOSED;
+}
+
+ndk::ScopedAStatus Session::generateChallenge(int32_t cookie, int32_t timeoutSec) {
+ LOG(INFO) << "generateChallenge";
+ scheduleStateOrCrash(SessionState::GENERATING_CHALLENGE);
+
+ mWorker->schedule(Callable::from([this, cookie, timeoutSec] {
+ enterStateOrCrash(cookie, SessionState::GENERATING_CHALLENGE);
+ mEngine->generateChallengeImpl(mCb.get(), timeoutSec);
+ enterIdling(cookie);
+ }));
+
return ndk::ScopedAStatus::ok();
}
-ndk::ScopedAStatus Session::revokeChallenge(int32_t /*cookie*/, int64_t /*challenge*/) {
+ndk::ScopedAStatus Session::revokeChallenge(int32_t cookie, int64_t challenge) {
+ LOG(INFO) << "revokeChallenge";
+ scheduleStateOrCrash(SessionState::REVOKING_CHALLENGE);
+
+ mWorker->schedule(Callable::from([this, cookie, challenge] {
+ enterStateOrCrash(cookie, SessionState::REVOKING_CHALLENGE);
+ mEngine->revokeChallengeImpl(mCb.get(), challenge);
+ enterIdling(cookie);
+ }));
+
return ndk::ScopedAStatus::ok();
}
-ndk::ScopedAStatus Session::enroll(int32_t /*cookie*/, const keymaster::HardwareAuthToken& /*hat*/,
- std::shared_ptr<common::ICancellationSignal>* /*return_val*/) {
+ndk::ScopedAStatus Session::enroll(int32_t cookie, const keymaster::HardwareAuthToken& hat,
+ std::shared_ptr<common::ICancellationSignal>* out) {
+ LOG(INFO) << "enroll";
+ scheduleStateOrCrash(SessionState::ENROLLING);
+
+ std::promise<void> cancellationPromise;
+ auto cancFuture = cancellationPromise.get_future();
+
+ mWorker->schedule(Callable::from([this, cookie, hat, cancFuture = std::move(cancFuture)] {
+ enterStateOrCrash(cookie, SessionState::ENROLLING);
+ if (shouldCancel(cancFuture)) {
+ mCb->onError(Error::CANCELED, 0 /* vendorCode */);
+ } else {
+ mEngine->enrollImpl(mCb.get(), hat);
+ }
+ enterIdling(cookie);
+ }));
+
+ *out = SharedRefBase::make<CancellationSignal>(std::move(cancellationPromise));
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);
- }
- *return_val = SharedRefBase::make<CancellationSignal>();
+ndk::ScopedAStatus Session::authenticate(int32_t cookie, int64_t operationId,
+ std::shared_ptr<common::ICancellationSignal>* out) {
+ LOG(INFO) << "authenticate";
+ scheduleStateOrCrash(SessionState::AUTHENTICATING);
+
+ std::promise<void> cancPromise;
+ auto cancFuture = cancPromise.get_future();
+
+ mWorker->schedule(
+ Callable::from([this, cookie, operationId, cancFuture = std::move(cancFuture)] {
+ enterStateOrCrash(cookie, SessionState::AUTHENTICATING);
+ if (shouldCancel(cancFuture)) {
+ mCb->onError(Error::CANCELED, 0 /* vendorCode */);
+ } else {
+ mEngine->authenticateImpl(mCb.get(), operationId);
+ }
+ enterIdling(cookie);
+ }));
+
+ *out = SharedRefBase::make<CancellationSignal>(std::move(cancPromise));
return ndk::ScopedAStatus::ok();
}
-ndk::ScopedAStatus Session::detectInteraction(
- int32_t /*cookie*/, std::shared_ptr<common::ICancellationSignal>* /*return_val*/) {
+ndk::ScopedAStatus Session::detectInteraction(int32_t cookie,
+ std::shared_ptr<common::ICancellationSignal>* out) {
+ LOG(INFO) << "detectInteraction";
+ scheduleStateOrCrash(SessionState::DETECTING_INTERACTION);
+
+ std::promise<void> cancellationPromise;
+ auto cancFuture = cancellationPromise.get_future();
+
+ mWorker->schedule(Callable::from([this, cookie, cancFuture = std::move(cancFuture)] {
+ enterStateOrCrash(cookie, SessionState::DETECTING_INTERACTION);
+ if (shouldCancel(cancFuture)) {
+ mCb->onError(Error::CANCELED, 0 /* vendorCode */);
+ } else {
+ mEngine->detectInteractionImpl(mCb.get());
+ }
+ enterIdling(cookie);
+ }));
+
+ *out = SharedRefBase::make<CancellationSignal>(std::move(cancellationPromise));
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>());
- }
+ndk::ScopedAStatus Session::enumerateEnrollments(int32_t cookie) {
+ LOG(INFO) << "enumerateEnrollments";
+ scheduleStateOrCrash(SessionState::ENUMERATING_ENROLLMENTS);
+
+ mWorker->schedule(Callable::from([this, cookie] {
+ enterStateOrCrash(cookie, SessionState::ENUMERATING_ENROLLMENTS);
+ mEngine->enumerateEnrollmentsImpl(mCb.get());
+ enterIdling(cookie);
+ }));
+
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>());
- }
+ndk::ScopedAStatus Session::removeEnrollments(int32_t cookie,
+ const std::vector<int32_t>& enrollmentIds) {
+ LOG(INFO) << "removeEnrollments";
+ scheduleStateOrCrash(SessionState::REMOVING_ENROLLMENTS);
+
+ mWorker->schedule(Callable::from([this, cookie, enrollmentIds] {
+ enterStateOrCrash(cookie, SessionState::REMOVING_ENROLLMENTS);
+ mEngine->removeEnrollmentsImpl(mCb.get(), enrollmentIds);
+ enterIdling(cookie);
+ }));
+
return ndk::ScopedAStatus::ok();
}
-ndk::ScopedAStatus Session::getAuthenticatorId(int32_t /*cookie*/) {
- if (cb_) {
- cb_->onStateChanged(0, SessionState::GETTING_AUTHENTICATOR_ID);
- cb_->onAuthenticatorIdRetrieved(0 /* authenticatorId */);
- }
+ndk::ScopedAStatus Session::getAuthenticatorId(int32_t cookie) {
+ LOG(INFO) << "getAuthenticatorId";
+ scheduleStateOrCrash(SessionState::GETTING_AUTHENTICATOR_ID);
+
+ mWorker->schedule(Callable::from([this, cookie] {
+ enterStateOrCrash(cookie, SessionState::GETTING_AUTHENTICATOR_ID);
+ mEngine->getAuthenticatorIdImpl(mCb.get());
+ enterIdling(cookie);
+ }));
+
return ndk::ScopedAStatus::ok();
}
-ndk::ScopedAStatus Session::invalidateAuthenticatorId(int32_t /*cookie*/) {
+ndk::ScopedAStatus Session::invalidateAuthenticatorId(int32_t cookie) {
+ LOG(INFO) << "invalidateAuthenticatorId";
+ scheduleStateOrCrash(SessionState::INVALIDATING_AUTHENTICATOR_ID);
+
+ mWorker->schedule(Callable::from([this, cookie] {
+ enterStateOrCrash(cookie, SessionState::INVALIDATING_AUTHENTICATOR_ID);
+ mEngine->invalidateAuthenticatorIdImpl(mCb.get());
+ enterIdling(cookie);
+ }));
+
return ndk::ScopedAStatus::ok();
}
-ndk::ScopedAStatus Session::resetLockout(int32_t /*cookie*/,
- const keymaster::HardwareAuthToken& /*hat*/) {
+ndk::ScopedAStatus Session::resetLockout(int32_t cookie, const keymaster::HardwareAuthToken& hat) {
+ LOG(INFO) << "resetLockout";
+ scheduleStateOrCrash(SessionState::RESETTING_LOCKOUT);
+
+ mWorker->schedule(Callable::from([this, cookie, hat] {
+ enterStateOrCrash(cookie, SessionState::RESETTING_LOCKOUT);
+ mEngine->resetLockoutImpl(mCb.get(), hat);
+ enterIdling(cookie);
+ }));
+
+ return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Session::close(int32_t cookie) {
+ LOG(INFO) << "close";
+ CHECK(mCurrentState == SessionState::IDLING) << "Can't close a non-idling session. Crashing.";
+ mCurrentState = SessionState::CLOSED;
+ mCb->onStateChanged(cookie, mCurrentState);
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..d1a63d0
--- /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(std::unique_ptr<Callable> 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;
+ }
+ std::unique_ptr<Callable> task = std::move(mQueue.front());
+ mQueue.pop_front();
+ lock.unlock();
+ (*task)();
+ }
+}
+
+} // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/include/Callable.h b/biometrics/fingerprint/aidl/default/include/Callable.h
new file mode 100644
index 0000000..c629511
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/include/Callable.h
@@ -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.
+ */
+
+#pragma once
+
+namespace aidl::android::hardware::biometrics::fingerprint {
+
+// Interface for representing parameterless functions. Unlike std::function<void()>, this can also
+// represent move-only lambdas.
+class Callable {
+ public:
+ virtual void operator()() = 0;
+ virtual ~Callable() = default;
+
+ // Creates a heap-allocated Callable instance from any function object.
+ template <typename T>
+ static std::unique_ptr<Callable> from(T func);
+
+ private:
+ template <typename T>
+ class AnyFuncWrapper;
+};
+
+// Private helper class for wrapping any function object into a Callable.
+template <typename T>
+class Callable::AnyFuncWrapper : public Callable {
+ public:
+ explicit AnyFuncWrapper(T func) : mFunc(std::move(func)) {}
+
+ void operator()() override { mFunc(); }
+
+ private:
+ T mFunc;
+};
+
+template <typename T>
+std::unique_ptr<Callable> Callable::from(T func) {
+ return std::make_unique<AnyFuncWrapper<T>>(std::move(func));
+}
+
+} // namespace aidl::android::hardware::biometrics::fingerprint
\ No newline at end of file
diff --git a/biometrics/fingerprint/aidl/default/include/CancellationSignal.h b/biometrics/fingerprint/aidl/default/include/CancellationSignal.h
new file mode 100644
index 0000000..99f2fba
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/include/CancellationSignal.h
@@ -0,0 +1,42 @@
+/*
+ * 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 <aidl/android/hardware/biometrics/common/BnCancellationSignal.h>
+#include <aidl/android/hardware/biometrics/fingerprint/ISessionCallback.h>
+#include <functional>
+#include <future>
+
+#include "WorkerThread.h"
+
+namespace aidl::android::hardware::biometrics::fingerprint {
+
+class CancellationSignal : public common::BnCancellationSignal {
+ public:
+ explicit CancellationSignal(std::promise<void>&& cancellationPromise);
+
+ ndk::ScopedAStatus cancel() override;
+
+ private:
+ std::promise<void> mCancellationPromise;
+};
+
+// Returns whether the given cancellation future is ready, i.e. whether the operation corresponding
+// to this future should be cancelled.
+bool shouldCancel(const std::future<void>& cancellationFuture);
+
+} // namespace aidl::android::hardware::biometrics::fingerprint
diff --git a/biometrics/fingerprint/aidl/default/include/FakeFingerprintEngine.h b/biometrics/fingerprint/aidl/default/include/FakeFingerprintEngine.h
new file mode 100644
index 0000000..9343316
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/include/FakeFingerprintEngine.h
@@ -0,0 +1,76 @@
+/*
+ * 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 <android-base/logging.h>
+
+namespace aidl::android::hardware::biometrics::fingerprint {
+
+class FakeFingerprintEngine {
+ public:
+ void generateChallengeImpl(ISessionCallback* cb, int32_t /*timeoutSec*/) {
+ LOG(INFO) << "generateChallengeImpl";
+ cb->onChallengeGenerated(0 /* challenge */);
+ }
+
+ void revokeChallengeImpl(ISessionCallback* cb, int64_t challenge) {
+ LOG(INFO) << "revokeChallengeImpl";
+ cb->onChallengeRevoked(challenge);
+ }
+
+ void enrollImpl(ISessionCallback* cb, const keymaster::HardwareAuthToken& /*hat*/) {
+ LOG(INFO) << "enrollImpl";
+ cb->onEnrollmentProgress(0 /* enrollmentId */, 0 /* remaining */);
+ }
+
+ void authenticateImpl(ISessionCallback* cb, int64_t /*operationId*/) {
+ LOG(INFO) << "authenticateImpl";
+ cb->onAuthenticationSucceeded(0 /* enrollmentId */, {} /* hat */);
+ }
+
+ void detectInteractionImpl(ISessionCallback* cb) {
+ LOG(INFO) << "detectInteractionImpl";
+ cb->onInteractionDetected();
+ }
+
+ void enumerateEnrollmentsImpl(ISessionCallback* cb) {
+ LOG(INFO) << "enumerateEnrollmentsImpl";
+ cb->onEnrollmentsEnumerated({} /* enrollmentIds */);
+ }
+
+ void removeEnrollmentsImpl(ISessionCallback* cb, const std::vector<int32_t>& enrollmentIds) {
+ LOG(INFO) << "removeEnrollmentsImpl";
+ cb->onEnrollmentsRemoved(enrollmentIds);
+ }
+
+ void getAuthenticatorIdImpl(ISessionCallback* cb) {
+ LOG(INFO) << "getAuthenticatorIdImpl";
+ cb->onAuthenticatorIdRetrieved(0 /* authenticatorId */);
+ }
+
+ void invalidateAuthenticatorIdImpl(ISessionCallback* cb) {
+ LOG(INFO) << "invalidateAuthenticatorIdImpl";
+ cb->onAuthenticatorIdInvalidated(0 /* newAuthenticatorId */);
+ }
+
+ void resetLockoutImpl(ISessionCallback* cb, const keymaster::HardwareAuthToken& /*hat*/) {
+ LOG(INFO) << "resetLockoutImpl";
+ cb->onLockoutCleared();
+ }
+};
+
+} // namespace aidl::android::hardware::biometrics::fingerprint
\ No newline at end of file
diff --git a/biometrics/fingerprint/aidl/default/Fingerprint.h b/biometrics/fingerprint/aidl/default/include/Fingerprint.h
similarity index 79%
rename from biometrics/fingerprint/aidl/default/Fingerprint.h
rename to biometrics/fingerprint/aidl/default/include/Fingerprint.h
index 4e952ba..9b8eef8 100644
--- a/biometrics/fingerprint/aidl/default/Fingerprint.h
+++ b/biometrics/fingerprint/aidl/default/include/Fingerprint.h
@@ -18,15 +18,28 @@
#include <aidl/android/hardware/biometrics/fingerprint/BnFingerprint.h>
+#include "FakeFingerprintEngine.h"
+#include "Session.h"
+#include "WorkerThread.h"
+
namespace aidl::android::hardware::biometrics::fingerprint {
class Fingerprint : 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;
+
+ ndk::ScopedAStatus reset() override;
+
+ private:
+ std::unique_ptr<FakeFingerprintEngine> mEngine;
+ WorkerThread mWorker;
+ std::weak_ptr<Session> mSession;
};
} // 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 61%
rename from biometrics/fingerprint/aidl/default/Session.h
rename to biometrics/fingerprint/aidl/default/include/Session.h
index ed3ae3f..adda831 100644
--- a/biometrics/fingerprint/aidl/default/Session.h
+++ b/biometrics/fingerprint/aidl/default/include/Session.h
@@ -19,6 +19,9 @@
#include <aidl/android/hardware/biometrics/fingerprint/BnSession.h>
#include <aidl/android/hardware/biometrics/fingerprint/ISessionCallback.h>
+#include "FakeFingerprintEngine.h"
+#include "WorkerThread.h"
+
namespace aidl::android::hardware::biometrics::fingerprint {
namespace common = aidl::android::hardware::biometrics::common;
@@ -26,21 +29,21 @@
class Session : public BnSession {
public:
- explicit Session(std::shared_ptr<ISessionCallback> cb);
+ Session(int sensorId, int userId, std::shared_ptr<ISessionCallback> cb,
+ FakeFingerprintEngine* engine, WorkerThread* worker);
ndk::ScopedAStatus generateChallenge(int32_t cookie, int32_t timeoutSec) override;
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 operationId,
+ 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;
@@ -54,6 +57,8 @@
ndk::ScopedAStatus resetLockout(int32_t cookie,
const keymaster::HardwareAuthToken& hat) override;
+ ndk::ScopedAStatus close(int32_t cookie) override;
+
ndk::ScopedAStatus onPointerDown(int32_t pointerId, int32_t x, int32_t y, float minor,
float major) override;
@@ -61,8 +66,29 @@
ndk::ScopedAStatus onUiReady() override;
+ bool isClosed();
+
private:
- std::shared_ptr<ISessionCallback> cb_;
+ // Crashes the HAL if it's not currently idling because that would be an invalid state machine
+ // transition. Otherwise, sets the scheduled state to the given state.
+ void scheduleStateOrCrash(SessionState state);
+
+ // Crashes the HAL if the provided state doesn't match the previously scheduled state.
+ // Otherwise, transitions into the provided state, clears the scheduled state, and notifies
+ // the client about the transition by calling ISessionCallback#onStateChanged.
+ void enterStateOrCrash(int cookie, SessionState state);
+
+ // Sets the current state to SessionState::IDLING and notifies the client about the transition
+ // by calling ISessionCallback#onStateChanged.
+ void enterIdling(int cookie);
+
+ int32_t mSensorId;
+ int32_t mUserId;
+ std::shared_ptr<ISessionCallback> mCb;
+ FakeFingerprintEngine* mEngine;
+ WorkerThread* mWorker;
+ SessionState mScheduledState;
+ SessionState mCurrentState;
};
} // 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..6fff4f2
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/include/WorkerThread.h
@@ -0,0 +1,79 @@
+/*
+ * 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>
+
+#include "Callable.h"
+
+namespace aidl::android::hardware::biometrics::fingerprint {
+
+// 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.
+ // This method expects heap-allocated tasks because it's the simplest way to represent function
+ // objects of any type. Stack-allocated std::function could be used instead, but it cannot
+ // represent functions with move-only captures because std::function is inherently copyable.
+ // Not being able to pass move-only lambdas is a major limitation for the HAL implementation,
+ // so heap-allocated tasks that share a common interface (Callable) were chosen instead.
+ bool schedule(std::unique_ptr<Callable> 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<std::unique_ptr<Callable>> 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..0d5014bb
--- /dev/null
+++ b/biometrics/fingerprint/aidl/default/tests/WorkerThreadTest.cpp
@@ -0,0 +1,106 @@
+/*
+ * 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::Callable;
+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(Callable::from([] {})));
+ // 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(Callable::from([] { 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(Callable::from([] {}));
+ worker.schedule(Callable::from([] {}));
+
+ EXPECT_FALSE(worker.schedule(Callable::from([] {})));
+}
+
+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(Callable::from([&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(Callable::from([&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(Callable::from([&promise1] {
+ promise1.set_value();
+ std::this_thread::sleep_for(200ms);
+ }));
+ worker.schedule(Callable::from([&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/2.1/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/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.5.xml b/compatibility_matrices/compatibility_matrix.5.xml
index e772b6f..96a3692 100644
--- a/compatibility_matrices/compatibility_matrix.5.xml
+++ b/compatibility_matrices/compatibility_matrix.5.xml
@@ -86,7 +86,7 @@
</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>
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..f9fa0bd
--- /dev/null
+++ b/drm/1.4/vts/functional/drm_hal_test.cpp
@@ -0,0 +1,197 @@
+/*
+ * 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);
+}
+
+TEST_P(DrmHalTest, GetLogMessages) {
+ auto drm = DrmPluginV1_4();
+ auto sid = OpenSession();
+ auto crypto_1_0 = CryptoPlugin(sid);
+ sp<V1_4::ICryptoPlugin> crypto(V1_4::ICryptoPlugin::castFrom(crypto_1_0));
+
+ hidl_vec<uint8_t> initData;
+ hidl_string mime{"text/plain"};
+ V1_0::KeyedVector optionalParameters;
+ auto res = drmPlugin->getKeyRequest_1_2(
+ sid, initData, mime, V1_0::KeyType::STREAMING,
+ optionalParameters, [&](V1_2::Status status, const hidl_vec<uint8_t>&,
+ V1_1::KeyRequestType, const hidl_string&) {
+ EXPECT_NE(V1_2::Status::OK, status);
+ });
+ EXPECT_OK(res);
+
+ V1_4::IDrmPlugin::getLogMessages_cb cb = [&](
+ V1_4::Status status,
+ hidl_vec<V1_4::LogMessage> logs) {
+ EXPECT_EQ(V1_4::Status::OK, status);
+ EXPECT_NE(0, logs.size());
+ for (auto log: logs) {
+ ALOGI("priority=[%u] message='%s'", log.priority, log.message.c_str());
+ }
+ };
+
+ auto res2 = drm->getLogMessages(cb);
+ EXPECT_OK(res2);
+
+ auto res3 = crypto->getLogMessages(cb);
+ EXPECT_OK(res3);
+
+ closeSession(sid);
+}
+
+} // 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/graphics/composer/2.4/vts/functional/AndroidTest.xml b/graphics/composer/2.4/vts/functional/AndroidTest.xml
new file mode 100644
index 0000000..583aa68
--- /dev/null
+++ b/graphics/composer/2.4/vts/functional/AndroidTest.xml
@@ -0,0 +1,36 @@
+<?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 VtsHalGraphicsComposerV2_4TargetTest.">
+ <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.StopServicesSetup">
+ </target_preparer>
+
+ <target_preparer class="com.android.tradefed.targetprep.PushFilePreparer">
+ <option name="cleanup" value="true" />
+ <option name="push" value="VtsHalGraphicsComposerV2_4TargetTest->/data/local/tmp/VtsHalGraphicsComposerV2_4TargetTest" />
+ </target_preparer>
+
+ <test class="com.android.tradefed.testtype.GTest" >
+ <option name="native-test-device-path" value="/data/local/tmp" />
+ <option name="module-name" value="VtsHalGraphicsComposerV2_4TargetTest" />
+ <option name="native-test-timeout" value="300000"/>
+ </test>
+</configuration>
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/Burst.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Burst.h
index f2cbe93..8329303 100644
--- a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Burst.h
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Burst.h
@@ -41,7 +41,7 @@
Burst(PrivateConstructorTag tag, nn::SharedPreparedModel preparedModel);
- OptionalCacheHold cacheMemory(const nn::Memory& memory) const override;
+ OptionalCacheHold cacheMemory(const nn::SharedMemory& memory) const override;
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
const nn::Request& request, nn::MeasureTiming measure) const override;
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h
index d3d933b..5d4bdbc 100644
--- a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h
@@ -36,7 +36,7 @@
GeneralResult<Operation> unvalidatedConvert(const hal::V1_0::Operation& operation);
GeneralResult<Model::OperandValues> unvalidatedConvert(
const hardware::hidl_vec<uint8_t>& operandValues);
-GeneralResult<Memory> unvalidatedConvert(const hardware::hidl_memory& memory);
+GeneralResult<SharedMemory> unvalidatedConvert(const hardware::hidl_memory& memory);
GeneralResult<Model> unvalidatedConvert(const hal::V1_0::Model& model);
GeneralResult<Request::Argument> unvalidatedConvert(
const hal::V1_0::RequestArgument& requestArgument);
@@ -65,7 +65,7 @@
nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation);
nn::GeneralResult<hidl_vec<uint8_t>> unvalidatedConvert(
const nn::Model::OperandValues& operandValues);
-nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Memory& memory);
+nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory);
nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model);
nn::GeneralResult<RequestArgument> unvalidatedConvert(const nn::Request::Argument& requestArgument);
nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Request::MemoryPool& memoryPool);
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/1.0/utils/src/Burst.cpp b/neuralnetworks/1.0/utils/src/Burst.cpp
index 384bd9b..971ad08 100644
--- a/neuralnetworks/1.0/utils/src/Burst.cpp
+++ b/neuralnetworks/1.0/utils/src/Burst.cpp
@@ -43,7 +43,7 @@
CHECK(kPreparedModel != nullptr);
}
-Burst::OptionalCacheHold Burst::cacheMemory(const nn::Memory& /*memory*/) const {
+Burst::OptionalCacheHold Burst::cacheMemory(const nn::SharedMemory& /*memory*/) const {
return nullptr;
}
diff --git a/neuralnetworks/1.0/utils/src/Conversions.cpp b/neuralnetworks/1.0/utils/src/Conversions.cpp
index fde7346..7a099cf 100644
--- a/neuralnetworks/1.0/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.0/utils/src/Conversions.cpp
@@ -153,8 +153,8 @@
return Model::OperandValues(operandValues.data(), operandValues.size());
}
-GeneralResult<Memory> unvalidatedConvert(const hidl_memory& memory) {
- return createSharedMemoryFromHidlMemory(memory);
+GeneralResult<SharedMemory> unvalidatedConvert(const hidl_memory& memory) {
+ return hal::utils::createSharedMemoryFromHidlMemory(memory);
}
GeneralResult<Model> unvalidatedConvert(const hal::V1_0::Model& model) {
@@ -346,9 +346,8 @@
return hidl_vec<uint8_t>(operandValues.data(), operandValues.data() + operandValues.size());
}
-nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Memory& memory) {
- return hidl_memory(memory.name, NN_TRY(hal::utils::hidlHandleFromSharedHandle(memory.handle)),
- memory.size);
+nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
+ return hal::utils::createHidlMemoryFromSharedMemory(memory);
}
nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
@@ -392,7 +391,7 @@
}
nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Request::MemoryPool& memoryPool) {
- return unvalidatedConvert(std::get<nn::Memory>(memoryPool));
+ return unvalidatedConvert(std::get<nn::SharedMemory>(memoryPool));
}
nn::GeneralResult<Request> unvalidatedConvert(const nn::Request& request) {
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/1.1/utils/src/Conversions.cpp b/neuralnetworks/1.1/utils/src/Conversions.cpp
index b47f25a..07bf7bc 100644
--- a/neuralnetworks/1.1/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.1/utils/src/Conversions.cpp
@@ -175,7 +175,7 @@
return V1_0::utils::unvalidatedConvert(operandValues);
}
-nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
return V1_0::utils::unvalidatedConvert(memory);
}
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/1.2/utils/src/Conversions.cpp b/neuralnetworks/1.2/utils/src/Conversions.cpp
index 062f6f7..7ae483e 100644
--- a/neuralnetworks/1.2/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.2/utils/src/Conversions.cpp
@@ -304,7 +304,11 @@
}
GeneralResult<SharedHandle> unvalidatedConvert(const hidl_handle& hidlHandle) {
- return hal::utils::sharedHandleFromNativeHandle(hidlHandle.getNativeHandle());
+ if (hidlHandle.getNativeHandle() == nullptr) {
+ return nullptr;
+ }
+ auto handle = NN_TRY(hal::utils::sharedHandleFromNativeHandle(hidlHandle.getNativeHandle()));
+ return std::make_shared<const Handle>(std::move(handle));
}
GeneralResult<DeviceType> convert(const hal::V1_2::DeviceType& deviceType) {
@@ -365,7 +369,7 @@
return V1_0::utils::unvalidatedConvert(operandValues);
}
-nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
return V1_0::utils::unvalidatedConvert(memory);
}
@@ -588,7 +592,10 @@
}
nn::GeneralResult<hidl_handle> unvalidatedConvert(const nn::SharedHandle& handle) {
- return hal::utils::hidlHandleFromSharedHandle(handle);
+ if (handle == nullptr) {
+ return {};
+ }
+ return hal::utils::hidlHandleFromSharedHandle(*handle);
}
nn::GeneralResult<DeviceType> convert(const nn::DeviceType& deviceType) {
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/Buffer.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
index fda79c8..69e87f7 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
@@ -42,8 +42,8 @@
nn::Request::MemoryDomainToken getToken() const override;
- nn::GeneralResult<void> copyTo(const nn::Memory& dst) const override;
- nn::GeneralResult<void> copyFrom(const nn::Memory& src,
+ nn::GeneralResult<void> copyTo(const nn::SharedMemory& dst) const override;
+ nn::GeneralResult<void> copyFrom(const nn::SharedMemory& src,
const nn::Dimensions& dimensions) const override;
private:
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
index 74a6534..8e1cdb8 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
@@ -59,7 +59,7 @@
GeneralResult<ErrorStatus> convert(const hal::V1_3::ErrorStatus& errorStatus);
GeneralResult<SharedHandle> convert(const hardware::hidl_handle& handle);
-GeneralResult<Memory> convert(const hardware::hidl_memory& memory);
+GeneralResult<SharedMemory> convert(const hardware::hidl_memory& memory);
GeneralResult<std::vector<BufferRole>> convert(
const hardware::hidl_vec<hal::V1_3::BufferRole>& bufferRoles);
@@ -100,7 +100,7 @@
nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
nn::GeneralResult<hidl_handle> convert(const nn::SharedHandle& handle);
-nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory);
+nn::GeneralResult<hidl_memory> convert(const nn::SharedMemory& memory);
nn::GeneralResult<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
nn::GeneralResult<V1_0::DeviceStatus> convert(const nn::DeviceStatus& deviceStatus);
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/Buffer.cpp b/neuralnetworks/1.3/utils/src/Buffer.cpp
index 614033e..ada5265 100644
--- a/neuralnetworks/1.3/utils/src/Buffer.cpp
+++ b/neuralnetworks/1.3/utils/src/Buffer.cpp
@@ -61,7 +61,7 @@
return kToken;
}
-nn::GeneralResult<void> Buffer::copyTo(const nn::Memory& dst) const {
+nn::GeneralResult<void> Buffer::copyTo(const nn::SharedMemory& dst) const {
const auto hidlDst = NN_TRY(convert(dst));
const auto ret = kBuffer->copyTo(hidlDst);
@@ -71,7 +71,7 @@
return {};
}
-nn::GeneralResult<void> Buffer::copyFrom(const nn::Memory& src,
+nn::GeneralResult<void> Buffer::copyFrom(const nn::SharedMemory& src,
const nn::Dimensions& dimensions) const {
const auto hidlSrc = NN_TRY(convert(src));
const auto hidlDimensions = hidl_vec<uint32_t>(dimensions);
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/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index 8b7db2b..6e74a62 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -261,7 +261,7 @@
using Discriminator = hal::V1_3::Request::MemoryPool::hidl_discriminator;
switch (memoryPool.getDiscriminator()) {
case Discriminator::hidlMemory:
- return createSharedMemoryFromHidlMemory(memoryPool.hidlMemory());
+ return hal::utils::createSharedMemoryFromHidlMemory(memoryPool.hidlMemory());
case Discriminator::token:
return static_cast<Request::MemoryDomainToken>(memoryPool.token());
}
@@ -352,7 +352,7 @@
return validatedConvert(handle);
}
-GeneralResult<Memory> convert(const hardware::hidl_memory& memory) {
+GeneralResult<SharedMemory> convert(const hardware::hidl_memory& memory) {
return validatedConvert(memory);
}
@@ -386,7 +386,7 @@
return V1_2::utils::unvalidatedConvert(handle);
}
-nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
return V1_0::utils::unvalidatedConvert(memory);
}
@@ -424,7 +424,7 @@
return unvalidatedConvertVec(arguments);
}
-nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::Memory& memory) {
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::SharedMemory& memory) {
Request::MemoryPool ret;
ret.hidlMemory(NN_TRY(unvalidatedConvert(memory)));
return ret;
@@ -677,7 +677,7 @@
return validatedConvert(handle);
}
-nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> convert(const nn::SharedMemory& memory) {
return validatedConvert(memory);
}
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..147d401
--- /dev/null
+++ b/neuralnetworks/aidl/utils/Android.bp
@@ -0,0 +1,34 @@
+//
+// 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: [
+ "libarect",
+ "neuralnetworks_types",
+ "neuralnetworks_utils_hal_common",
+ ],
+ shared_libs: [
+ "android.hardware.neuralnetworks-V1-ndk_platform",
+ "libbinder_ndk",
+ "libhidlbase",
+ "libnativewindow",
+ ],
+}
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..1b2f69c
--- /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<SharedMemory> 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<SharedMemory> 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<SharedMemory>> 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::SharedMemory& memory);
+nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape);
+nn::GeneralResult<ErrorStatus> unvalidatedConvert(const nn::ErrorStatus& errorStatus);
+
+nn::GeneralResult<Memory> convert(const nn::SharedMemory& 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..db3504b
--- /dev/null
+++ b/neuralnetworks/aidl/utils/src/Conversions.cpp
@@ -0,0 +1,731 @@
+/*
+ * 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 <android/hardware_buffer.h>
+#include <cutils/native_handle.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 <vndk/hardware_buffer.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 {
+
+using ::aidl::android::hardware::common::NativeHandle;
+
+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;
+}
+
+GeneralResult<Handle> unvalidatedConvertHelper(const NativeHandle& aidlNativeHandle) {
+ std::vector<base::unique_fd> fds;
+ fds.reserve(aidlNativeHandle.fds.size());
+ for (const auto& fd : aidlNativeHandle.fds) {
+ const 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 Handle{.fds = std::move(fds), .ints = aidlNativeHandle.ints};
+}
+
+struct NativeHandleDeleter {
+ void operator()(native_handle_t* handle) const {
+ if (handle) {
+ native_handle_close(handle);
+ native_handle_delete(handle);
+ }
+ }
+};
+
+using UniqueNativeHandle = std::unique_ptr<native_handle_t, NativeHandleDeleter>;
+
+static nn::GeneralResult<UniqueNativeHandle> nativeHandleFromAidlHandle(
+ const NativeHandle& handle) {
+ std::vector<base::unique_fd> fds;
+ fds.reserve(handle.fds.size());
+ for (const auto& fd : handle.fds) {
+ const int dupFd = dup(fd.get());
+ if (dupFd == -1) {
+ return NN_ERROR() << "Failed to dup the fd";
+ }
+ fds.emplace_back(dupFd);
+ }
+
+ constexpr size_t kIntMax = std::numeric_limits<int>::max();
+ CHECK_LE(handle.fds.size(), kIntMax);
+ CHECK_LE(handle.ints.size(), kIntMax);
+ native_handle_t* nativeHandle = native_handle_create(static_cast<int>(handle.fds.size()),
+ static_cast<int>(handle.ints.size()));
+ if (nativeHandle == nullptr) {
+ return NN_ERROR() << "Failed to create native_handle";
+ }
+ for (size_t i = 0; i < fds.size(); ++i) {
+ nativeHandle->data[i] = fds[i].release();
+ }
+ std::copy(handle.ints.begin(), handle.ints.end(), &nativeHandle->data[nativeHandle->numFds]);
+
+ return UniqueNativeHandle(nativeHandle);
+}
+
+} // 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;
+}
+
+static uint32_t roundUpToMultiple(uint32_t value, uint32_t multiple) {
+ return (value + multiple - 1) / multiple * multiple;
+}
+
+GeneralResult<SharedMemory> unvalidatedConvert(const aidl_hal::Memory& memory) {
+ VERIFY_NON_NEGATIVE(memory.size) << "Memory size must not be negative";
+ if (memory.size > std::numeric_limits<uint32_t>::max()) {
+ return NN_ERROR() << "Memory: size must be <= std::numeric_limits<size_t>::max()";
+ }
+
+ if (memory.name != "hardware_buffer_blob") {
+ return std::make_shared<const Memory>(Memory{
+ .handle = NN_TRY(unvalidatedConvertHelper(memory.handle)),
+ .size = static_cast<uint32_t>(memory.size),
+ .name = memory.name,
+ });
+ }
+
+ const auto size = static_cast<uint32_t>(memory.size);
+ const auto format = AHARDWAREBUFFER_FORMAT_BLOB;
+ const auto usage = AHARDWAREBUFFER_USAGE_CPU_READ_OFTEN | AHARDWAREBUFFER_USAGE_CPU_WRITE_OFTEN;
+ const uint32_t width = size;
+ const uint32_t height = 1; // height is always 1 for BLOB mode AHardwareBuffer.
+ const uint32_t layers = 1; // layers is always 1 for BLOB mode AHardwareBuffer.
+
+ const UniqueNativeHandle handle = NN_TRY(nativeHandleFromAidlHandle(memory.handle));
+ const native_handle_t* nativeHandle = handle.get();
+
+ // AHardwareBuffer_createFromHandle() might fail because an allocator
+ // expects a specific stride value. In that case, we try to guess it by
+ // aligning the width to small powers of 2.
+ // TODO(b/174120849): Avoid stride assumptions.
+ AHardwareBuffer* hardwareBuffer = nullptr;
+ status_t status = UNKNOWN_ERROR;
+ for (uint32_t alignment : {1, 4, 32, 64, 128, 2, 8, 16}) {
+ const uint32_t stride = roundUpToMultiple(width, alignment);
+ AHardwareBuffer_Desc desc{
+ .width = width,
+ .height = height,
+ .layers = layers,
+ .format = format,
+ .usage = usage,
+ .stride = stride,
+ };
+ status = AHardwareBuffer_createFromHandle(&desc, nativeHandle,
+ AHARDWAREBUFFER_CREATE_FROM_HANDLE_METHOD_CLONE,
+ &hardwareBuffer);
+ if (status == NO_ERROR) {
+ break;
+ }
+ }
+ if (status != NO_ERROR) {
+ return NN_ERROR(ErrorStatus::GENERAL_FAILURE)
+ << "Can't create AHardwareBuffer from handle. Error: " << status;
+ }
+
+ return std::make_shared<const Memory>(Memory{
+ .handle = HardwareBufferHandle(hardwareBuffer, /*takeOwnership=*/true),
+ .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 NativeHandle& aidlNativeHandle) {
+ return std::make_shared<const Handle>(NN_TRY(unvalidatedConvertHelper(aidlNativeHandle)));
+}
+
+GeneralResult<ExecutionPreference> convert(
+ const aidl_hal::ExecutionPreference& executionPreference) {
+ return validatedConvert(executionPreference);
+}
+
+GeneralResult<SharedMemory> 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<SharedMemory>> 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;
+}
+
+nn::GeneralResult<common::NativeHandle> unvalidatedConvert(const nn::Handle& handle) {
+ common::NativeHandle aidlNativeHandle;
+ aidlNativeHandle.fds.reserve(handle.fds.size());
+ for (const auto& fd : handle.fds) {
+ const 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 = handle.ints;
+ return aidlNativeHandle;
+}
+
+static nn::GeneralResult<common::NativeHandle> aidlHandleFromNativeHandle(
+ const native_handle_t& handle) {
+ common::NativeHandle aidlNativeHandle;
+
+ aidlNativeHandle.fds.reserve(handle.numFds);
+ for (int i = 0; i < handle.numFds; ++i) {
+ const int dupFd = dup(handle.data[i]);
+ if (dupFd == -1) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Failed to dup the fd";
+ }
+ aidlNativeHandle.fds.emplace_back(dupFd);
+ }
+
+ aidlNativeHandle.ints = std::vector<int>(&handle.data[handle.numFds],
+ &handle.data[handle.numFds + handle.numInts]);
+
+ return aidlNativeHandle;
+}
+
+} // namespace
+
+nn::GeneralResult<common::NativeHandle> unvalidatedConvert(const nn::SharedHandle& sharedHandle) {
+ CHECK(sharedHandle != nullptr);
+ return unvalidatedConvert(*sharedHandle);
+}
+
+nn::GeneralResult<Memory> unvalidatedConvert(const nn::SharedMemory& memory) {
+ CHECK(memory != nullptr);
+ if (memory->size > std::numeric_limits<int64_t>::max()) {
+ return NN_ERROR() << "Memory size doesn't fit into int64_t.";
+ }
+ if (const auto* handle = std::get_if<nn::Handle>(&memory->handle)) {
+ return Memory{
+ .handle = NN_TRY(unvalidatedConvert(*handle)),
+ .size = static_cast<int64_t>(memory->size),
+ .name = memory->name,
+ };
+ }
+
+ const auto* ahwb = std::get<nn::HardwareBufferHandle>(memory->handle).get();
+ AHardwareBuffer_Desc bufferDesc;
+ AHardwareBuffer_describe(ahwb, &bufferDesc);
+
+ if (bufferDesc.format == AHARDWAREBUFFER_FORMAT_BLOB) {
+ CHECK_EQ(memory->size, bufferDesc.width);
+ CHECK_EQ(memory->name, "hardware_buffer_blob");
+ } else {
+ CHECK_EQ(memory->size, 0u);
+ CHECK_EQ(memory->name, "hardware_buffer");
+ }
+
+ const native_handle_t* nativeHandle = AHardwareBuffer_getNativeHandle(ahwb);
+ if (nativeHandle == nullptr) {
+ return NN_ERROR() << "unvalidatedConvert failed because AHardwareBuffer_getNativeHandle "
+ "returned nullptr";
+ }
+
+ return Memory{
+ .handle = NN_TRY(aidlHandleFromNativeHandle(*nativeHandle)),
+ .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::SharedMemory& 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..4beb828
--- /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::SharedMemory> 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..3c7f5f7
--- /dev/null
+++ b/neuralnetworks/aidl/vts/functional/Utils.cpp
@@ -0,0 +1,253 @@
+/*
+ * 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, /*takeOwnership=*/false).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/Android.bp b/neuralnetworks/utils/common/Android.bp
index 6c491ae..50295f1 100644
--- a/neuralnetworks/utils/common/Android.bp
+++ b/neuralnetworks/utils/common/Android.bp
@@ -22,10 +22,12 @@
export_include_dirs: ["include"],
cflags: ["-Wthread-safety"],
static_libs: [
+ "libarect",
"neuralnetworks_types",
],
shared_libs: [
"libhidlbase",
+ "libnativewindow",
],
}
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
index b3989e5..547f203 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 {
@@ -68,10 +74,12 @@
std::vector<uint32_t> countNumberOfConsumers(size_t numberOfOperands,
const std::vector<nn::Operation>& operations);
-nn::GeneralResult<nn::Memory> createSharedMemoryFromHidlMemory(const hidl_memory& memory);
+nn::GeneralResult<hidl_memory> createHidlMemoryFromSharedMemory(const nn::SharedMemory& memory);
+nn::GeneralResult<nn::SharedMemory> createSharedMemoryFromHidlMemory(const hidl_memory& memory);
-nn::GeneralResult<hidl_handle> hidlHandleFromSharedHandle(const nn::SharedHandle& handle);
-nn::GeneralResult<nn::SharedHandle> sharedHandleFromNativeHandle(const native_handle_t* handle);
+nn::GeneralResult<hidl_handle> hidlHandleFromSharedHandle(const nn::Handle& handle);
+nn::GeneralResult<nn::Handle> sharedHandleFromNativeHandle(const native_handle_t* handle);
+
nn::GeneralResult<hidl_vec<hidl_handle>> convertSyncFences(
const std::vector<nn::SyncFence>& fences);
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/HandleError.h b/neuralnetworks/utils/common/include/nnapi/hal/HandleError.h
index 95a20a8..209b663 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/HandleError.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/HandleError.h
@@ -14,6 +14,9 @@
* limitations under the License.
*/
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_HANDLE_ERROR_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_HANDLE_ERROR_H
+
#include <android/hidl/base/1.0/IBase.h>
#include <hidl/HidlSupport.h>
#include <nnapi/Result.h>
@@ -50,7 +53,8 @@
})
template <typename Type>
-nn::GeneralResult<Type> makeGeneralFailure(nn::Result<Type> result, nn::ErrorStatus status) {
+nn::GeneralResult<Type> makeGeneralFailure(
+ nn::Result<Type> result, nn::ErrorStatus status = nn::ErrorStatus::GENERAL_FAILURE) {
if (!result.has_value()) {
return nn::error(status) << std::move(result).error();
}
@@ -75,7 +79,8 @@
}
template <typename Type>
-nn::ExecutionResult<Type> makeExecutionFailure(nn::Result<Type> result, nn::ErrorStatus status) {
+nn::ExecutionResult<Type> makeExecutionFailure(
+ nn::Result<Type> result, nn::ErrorStatus status = nn::ErrorStatus::GENERAL_FAILURE) {
return makeExecutionFailure(makeGeneralFailure(result, status));
}
@@ -86,4 +91,6 @@
} else \
return NN_ERROR(canonical)
-} // namespace android::hardware::neuralnetworks::utils
\ No newline at end of file
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_HANDLE_ERROR_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/InvalidBuffer.h b/neuralnetworks/utils/common/include/nnapi/hal/InvalidBuffer.h
index 8c04b88..0e98c2e 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/InvalidBuffer.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/InvalidBuffer.h
@@ -31,9 +31,9 @@
public:
nn::Request::MemoryDomainToken getToken() const override;
- nn::GeneralResult<void> copyTo(const nn::Memory& dst) const override;
+ nn::GeneralResult<void> copyTo(const nn::SharedMemory& dst) const override;
- nn::GeneralResult<void> copyFrom(const nn::Memory& src,
+ nn::GeneralResult<void> copyFrom(const nn::SharedMemory& src,
const nn::Dimensions& dimensions) const override;
};
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/InvalidBurst.h b/neuralnetworks/utils/common/include/nnapi/hal/InvalidBurst.h
index 83e60b6..996858c 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/InvalidBurst.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/InvalidBurst.h
@@ -29,7 +29,7 @@
class InvalidBurst final : public nn::IBurst {
public:
- OptionalCacheHold cacheMemory(const nn::Memory& memory) const override;
+ OptionalCacheHold cacheMemory(const nn::SharedMemory& memory) const override;
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
const nn::Request& request, nn::MeasureTiming measure) const override;
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ResilientBuffer.h b/neuralnetworks/utils/common/include/nnapi/hal/ResilientBuffer.h
index d2c2469..c8ca6f2 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/ResilientBuffer.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ResilientBuffer.h
@@ -46,9 +46,9 @@
nn::Request::MemoryDomainToken getToken() const override;
- nn::GeneralResult<void> copyTo(const nn::Memory& dst) const override;
+ nn::GeneralResult<void> copyTo(const nn::SharedMemory& dst) const override;
- nn::GeneralResult<void> copyFrom(const nn::Memory& src,
+ nn::GeneralResult<void> copyFrom(const nn::SharedMemory& src,
const nn::Dimensions& dimensions) const override;
private:
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ResilientBurst.h b/neuralnetworks/utils/common/include/nnapi/hal/ResilientBurst.h
index 0df287f..3b87330 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/ResilientBurst.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ResilientBurst.h
@@ -44,7 +44,7 @@
nn::SharedBurst getBurst() const;
nn::GeneralResult<nn::SharedBurst> recover(const nn::IBurst* failingBurst) const;
- OptionalCacheHold cacheMemory(const nn::Memory& memory) const override;
+ OptionalCacheHold cacheMemory(const nn::SharedMemory& memory) const override;
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
const nn::Request& request, nn::MeasureTiming measure) const override;
diff --git a/neuralnetworks/utils/common/src/CommonUtils.cpp b/neuralnetworks/utils/common/src/CommonUtils.cpp
index c04c8df..7a5035f 100644
--- a/neuralnetworks/utils/common/src/CommonUtils.cpp
+++ b/neuralnetworks/utils/common/src/CommonUtils.cpp
@@ -20,11 +20,14 @@
#include <android-base/logging.h>
#include <android-base/unique_fd.h>
+#include <android/hardware_buffer.h>
+#include <hidl/HidlSupport.h>
#include <nnapi/Result.h>
#include <nnapi/SharedMemory.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/Validation.h>
+#include <vndk/hardware_buffer.h>
#include <algorithm>
#include <any>
@@ -203,13 +206,13 @@
nn::GeneralResult<void> unflushDataFromSharedToPointer(
const nn::Request& request, const std::optional<nn::Request>& maybeRequestInShared) {
if (!maybeRequestInShared.has_value() || maybeRequestInShared->pools.empty() ||
- !std::holds_alternative<nn::Memory>(maybeRequestInShared->pools.back())) {
+ !std::holds_alternative<nn::SharedMemory>(maybeRequestInShared->pools.back())) {
return {};
}
const auto& requestInShared = *maybeRequestInShared;
// Map the memory.
- const auto& outputMemory = std::get<nn::Memory>(requestInShared.pools.back());
+ const auto& outputMemory = std::get<nn::SharedMemory>(requestInShared.pools.back());
const auto [pointer, size, context] = NN_TRY(map(outputMemory));
const uint8_t* constantPointer =
std::visit([](const auto& o) { return static_cast<const uint8_t*>(o); }, pointer);
@@ -248,44 +251,128 @@
return nn::countNumberOfConsumers(numberOfOperands, operations);
}
-nn::GeneralResult<hidl_handle> hidlHandleFromSharedHandle(const nn::SharedHandle& handle) {
- if (handle == nullptr) {
- return {};
+nn::GeneralResult<hidl_memory> createHidlMemoryFromSharedMemory(const nn::SharedMemory& memory) {
+ if (memory == nullptr) {
+ return NN_ERROR() << "Memory must be non-empty";
+ }
+ if (const auto* handle = std::get_if<nn::Handle>(&memory->handle)) {
+ return hidl_memory(memory->name, NN_TRY(hidlHandleFromSharedHandle(*handle)), memory->size);
}
+ const auto* ahwb = std::get<nn::HardwareBufferHandle>(memory->handle).get();
+ AHardwareBuffer_Desc bufferDesc;
+ AHardwareBuffer_describe(ahwb, &bufferDesc);
+
+ if (bufferDesc.format == AHARDWAREBUFFER_FORMAT_BLOB) {
+ CHECK_EQ(memory->size, bufferDesc.width);
+ CHECK_EQ(memory->name, "hardware_buffer_blob");
+ } else {
+ CHECK_EQ(memory->size, 0u);
+ CHECK_EQ(memory->name, "hardware_buffer");
+ }
+
+ const native_handle_t* nativeHandle = AHardwareBuffer_getNativeHandle(ahwb);
+ const hidl_handle hidlHandle(nativeHandle);
+ hidl_handle handle(hidlHandle);
+
+ return hidl_memory(memory->name, std::move(handle), memory->size);
+}
+
+static uint32_t roundUpToMultiple(uint32_t value, uint32_t multiple) {
+ return (value + multiple - 1) / multiple * multiple;
+}
+
+nn::GeneralResult<nn::SharedMemory> createSharedMemoryFromHidlMemory(const hidl_memory& memory) {
+ CHECK_LE(memory.size(), std::numeric_limits<uint32_t>::max());
+
+ if (memory.name() != "hardware_buffer_blob") {
+ return std::make_shared<const nn::Memory>(nn::Memory{
+ .handle = NN_TRY(sharedHandleFromNativeHandle(memory.handle())),
+ .size = static_cast<uint32_t>(memory.size()),
+ .name = memory.name(),
+ });
+ }
+
+ const auto size = memory.size();
+ const auto format = AHARDWAREBUFFER_FORMAT_BLOB;
+ const auto usage = AHARDWAREBUFFER_USAGE_CPU_READ_OFTEN | AHARDWAREBUFFER_USAGE_CPU_WRITE_OFTEN;
+ const uint32_t width = size;
+ const uint32_t height = 1; // height is always 1 for BLOB mode AHardwareBuffer.
+ const uint32_t layers = 1; // layers is always 1 for BLOB mode AHardwareBuffer.
+
+ // AHardwareBuffer_createFromHandle() might fail because an allocator
+ // expects a specific stride value. In that case, we try to guess it by
+ // aligning the width to small powers of 2.
+ // TODO(b/174120849): Avoid stride assumptions.
+ AHardwareBuffer* hardwareBuffer = nullptr;
+ status_t status = UNKNOWN_ERROR;
+ for (uint32_t alignment : {1, 4, 32, 64, 128, 2, 8, 16}) {
+ const uint32_t stride = roundUpToMultiple(width, alignment);
+ AHardwareBuffer_Desc desc{
+ .width = width,
+ .height = height,
+ .layers = layers,
+ .format = format,
+ .usage = usage,
+ .stride = stride,
+ };
+ status = AHardwareBuffer_createFromHandle(&desc, memory.handle(),
+ AHARDWAREBUFFER_CREATE_FROM_HANDLE_METHOD_CLONE,
+ &hardwareBuffer);
+ if (status == NO_ERROR) {
+ break;
+ }
+ }
+ if (status != NO_ERROR) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Can't create AHardwareBuffer from handle. Error: " << status;
+ }
+
+ return std::make_shared<const nn::Memory>(nn::Memory{
+ .handle = nn::HardwareBufferHandle(hardwareBuffer, /*takeOwnership=*/true),
+ .size = static_cast<uint32_t>(memory.size()),
+ .name = memory.name(),
+ });
+}
+
+nn::GeneralResult<hidl_handle> hidlHandleFromSharedHandle(const nn::Handle& handle) {
std::vector<base::unique_fd> fds;
- fds.reserve(handle->fds.size());
- for (const auto& fd : handle->fds) {
- int dupFd = dup(fd);
+ fds.reserve(handle.fds.size());
+ for (const auto& fd : handle.fds) {
+ const int dupFd = dup(fd);
if (dupFd == -1) {
return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Failed to dup the fd";
}
fds.emplace_back(dupFd);
}
- native_handle_t* nativeHandle = native_handle_create(handle->fds.size(), handle->ints.size());
+ constexpr size_t kIntMax = std::numeric_limits<int>::max();
+ CHECK_LE(handle.fds.size(), kIntMax);
+ CHECK_LE(handle.ints.size(), kIntMax);
+ native_handle_t* nativeHandle = native_handle_create(static_cast<int>(handle.fds.size()),
+ static_cast<int>(handle.ints.size()));
if (nativeHandle == nullptr) {
return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Failed to create native_handle";
}
for (size_t i = 0; i < fds.size(); ++i) {
nativeHandle->data[i] = fds[i].release();
}
- std::copy(handle->ints.begin(), handle->ints.end(), &nativeHandle->data[nativeHandle->numFds]);
+ std::copy(handle.ints.begin(), handle.ints.end(), &nativeHandle->data[nativeHandle->numFds]);
hidl_handle hidlHandle;
hidlHandle.setTo(nativeHandle, /*shouldOwn=*/true);
return hidlHandle;
}
-nn::GeneralResult<nn::SharedHandle> sharedHandleFromNativeHandle(const native_handle_t* handle) {
+nn::GeneralResult<nn::Handle> sharedHandleFromNativeHandle(const native_handle_t* handle) {
if (handle == nullptr) {
- return nullptr;
+ return NN_ERROR() << "sharedHandleFromNativeHandle failed because handle is nullptr";
}
std::vector<base::unique_fd> fds;
fds.reserve(handle->numFds);
for (int i = 0; i < handle->numFds; ++i) {
- int dupFd = dup(handle->data[i]);
+ const int dupFd = dup(handle->data[i]);
if (dupFd == -1) {
return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Failed to dup the fd";
}
@@ -295,18 +382,18 @@
std::vector<int> ints(&handle->data[handle->numFds],
&handle->data[handle->numFds + handle->numInts]);
- return std::make_shared<const nn::Handle>(nn::Handle{
- .fds = std::move(fds),
- .ints = std::move(ints),
- });
+ return nn::Handle{.fds = std::move(fds), .ints = std::move(ints)};
}
nn::GeneralResult<hidl_vec<hidl_handle>> convertSyncFences(
const std::vector<nn::SyncFence>& syncFences) {
hidl_vec<hidl_handle> handles(syncFences.size());
for (size_t i = 0; i < syncFences.size(); ++i) {
- handles[i] =
- NN_TRY(hal::utils::hidlHandleFromSharedHandle(syncFences[i].getSharedHandle()));
+ const auto& handle = syncFences[i].getSharedHandle();
+ if (handle == nullptr) {
+ return NN_ERROR() << "convertSyncFences failed because sync fence is empty";
+ }
+ handles[i] = NN_TRY(hidlHandleFromSharedHandle(*handle));
}
return handles;
}
diff --git a/neuralnetworks/utils/common/src/InvalidBuffer.cpp b/neuralnetworks/utils/common/src/InvalidBuffer.cpp
index c6f75d7..e73001d 100644
--- a/neuralnetworks/utils/common/src/InvalidBuffer.cpp
+++ b/neuralnetworks/utils/common/src/InvalidBuffer.cpp
@@ -30,11 +30,11 @@
return nn::Request::MemoryDomainToken{};
}
-nn::GeneralResult<void> InvalidBuffer::copyTo(const nn::Memory& /*dst*/) const {
+nn::GeneralResult<void> InvalidBuffer::copyTo(const nn::SharedMemory& /*dst*/) const {
return NN_ERROR() << "InvalidBuffer";
}
-nn::GeneralResult<void> InvalidBuffer::copyFrom(const nn::Memory& /*src*/,
+nn::GeneralResult<void> InvalidBuffer::copyFrom(const nn::SharedMemory& /*src*/,
const nn::Dimensions& /*dimensions*/) const {
return NN_ERROR() << "InvalidBuffer";
}
diff --git a/neuralnetworks/utils/common/src/InvalidBurst.cpp b/neuralnetworks/utils/common/src/InvalidBurst.cpp
index 4ca6603..81ca18d 100644
--- a/neuralnetworks/utils/common/src/InvalidBurst.cpp
+++ b/neuralnetworks/utils/common/src/InvalidBurst.cpp
@@ -26,7 +26,8 @@
namespace android::hardware::neuralnetworks::utils {
-InvalidBurst::OptionalCacheHold InvalidBurst::cacheMemory(const nn::Memory& /*memory*/) const {
+InvalidBurst::OptionalCacheHold InvalidBurst::cacheMemory(
+ const nn::SharedMemory& /*memory*/) const {
return nullptr;
}
diff --git a/neuralnetworks/utils/common/src/ResilientBuffer.cpp b/neuralnetworks/utils/common/src/ResilientBuffer.cpp
index 47abbe2..1904375 100644
--- a/neuralnetworks/utils/common/src/ResilientBuffer.cpp
+++ b/neuralnetworks/utils/common/src/ResilientBuffer.cpp
@@ -99,12 +99,12 @@
return getBuffer()->getToken();
}
-nn::GeneralResult<void> ResilientBuffer::copyTo(const nn::Memory& dst) const {
+nn::GeneralResult<void> ResilientBuffer::copyTo(const nn::SharedMemory& dst) const {
const auto fn = [&dst](const nn::IBuffer& buffer) { return buffer.copyTo(dst); };
return protect(*this, fn);
}
-nn::GeneralResult<void> ResilientBuffer::copyFrom(const nn::Memory& src,
+nn::GeneralResult<void> ResilientBuffer::copyFrom(const nn::SharedMemory& src,
const nn::Dimensions& dimensions) const {
const auto fn = [&src, &dimensions](const nn::IBuffer& buffer) {
return buffer.copyFrom(src, dimensions);
diff --git a/neuralnetworks/utils/common/src/ResilientBurst.cpp b/neuralnetworks/utils/common/src/ResilientBurst.cpp
index 0d3cb33..5ca868b 100644
--- a/neuralnetworks/utils/common/src/ResilientBurst.cpp
+++ b/neuralnetworks/utils/common/src/ResilientBurst.cpp
@@ -94,7 +94,8 @@
return mBurst;
}
-ResilientBurst::OptionalCacheHold ResilientBurst::cacheMemory(const nn::Memory& memory) const {
+ResilientBurst::OptionalCacheHold ResilientBurst::cacheMemory(
+ const nn::SharedMemory& memory) const {
return getBurst()->cacheMemory(memory);
}
diff --git a/neuralnetworks/utils/common/test/MockBuffer.h b/neuralnetworks/utils/common/test/MockBuffer.h
index c5405fb..59d5700 100644
--- a/neuralnetworks/utils/common/test/MockBuffer.h
+++ b/neuralnetworks/utils/common/test/MockBuffer.h
@@ -27,9 +27,9 @@
class MockBuffer final : public IBuffer {
public:
MOCK_METHOD(Request::MemoryDomainToken, getToken, (), (const, override));
- MOCK_METHOD(GeneralResult<void>, copyTo, (const Memory& dst), (const, override));
- MOCK_METHOD(GeneralResult<void>, copyFrom, (const Memory& src, const Dimensions& dimensions),
- (const, override));
+ MOCK_METHOD(GeneralResult<void>, copyTo, (const SharedMemory& dst), (const, override));
+ MOCK_METHOD(GeneralResult<void>, copyFrom,
+ (const SharedMemory& src, const Dimensions& dimensions), (const, override));
};
} // namespace android::nn
diff --git a/neuralnetworks/utils/common/test/ResilientBufferTest.cpp b/neuralnetworks/utils/common/test/ResilientBufferTest.cpp
index deb9b7c..7afd020 100644
--- a/neuralnetworks/utils/common/test/ResilientBufferTest.cpp
+++ b/neuralnetworks/utils/common/test/ResilientBufferTest.cpp
@@ -15,9 +15,11 @@
*/
#include <gmock/gmock.h>
+#include <nnapi/SharedMemory.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/hal/ResilientBuffer.h>
+#include <memory>
#include <tuple>
#include <utility>
#include "MockBuffer.h"
@@ -113,7 +115,8 @@
EXPECT_CALL(*mockBuffer, copyTo(_)).Times(1).WillOnce(Return(kNoError));
// run test
- const auto result = buffer->copyTo({});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyTo(memory);
// verify result
ASSERT_TRUE(result.has_value())
@@ -126,7 +129,8 @@
EXPECT_CALL(*mockBuffer, copyTo(_)).Times(1).WillOnce(kReturnGeneralFailure);
// run test
- const auto result = buffer->copyTo({});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyTo(memory);
// verify result
ASSERT_FALSE(result.has_value());
@@ -140,7 +144,8 @@
EXPECT_CALL(*mockBufferFactory, Call()).Times(1).WillOnce(kReturnGeneralFailure);
// run test
- const auto result = buffer->copyTo({});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyTo(memory);
// verify result
ASSERT_FALSE(result.has_value());
@@ -156,7 +161,8 @@
EXPECT_CALL(*mockBufferFactory, Call()).Times(1).WillOnce(Return(recoveredMockBuffer));
// run test
- const auto result = buffer->copyTo({});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyTo(memory);
// verify result
ASSERT_TRUE(result.has_value())
@@ -169,7 +175,8 @@
EXPECT_CALL(*mockBuffer, copyFrom(_, _)).Times(1).WillOnce(Return(kNoError));
// run test
- const auto result = buffer->copyFrom({}, {});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyFrom(memory, {});
// verify result
ASSERT_TRUE(result.has_value())
@@ -182,7 +189,8 @@
EXPECT_CALL(*mockBuffer, copyFrom(_, _)).Times(1).WillOnce(kReturnGeneralFailure);
// run test
- const auto result = buffer->copyFrom({}, {});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyFrom(memory, {});
// verify result
ASSERT_FALSE(result.has_value());
@@ -196,7 +204,8 @@
EXPECT_CALL(*mockBufferFactory, Call()).Times(1).WillOnce(kReturnGeneralFailure);
// run test
- const auto result = buffer->copyFrom({}, {});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyFrom(memory, {});
// verify result
ASSERT_FALSE(result.has_value());
@@ -212,7 +221,8 @@
EXPECT_CALL(*mockBufferFactory, Call()).Times(1).WillOnce(Return(recoveredMockBuffer));
// run test
- const auto result = buffer->copyFrom({}, {});
+ const nn::SharedMemory memory = std::make_shared<const nn::Memory>();
+ const auto result = buffer->copyFrom(memory, {});
// verify result
ASSERT_TRUE(result.has_value())
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 b756ce1..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
*
@@ -462,7 +465,7 @@
* cell information isn't known then the appropriate unknown value will be returned.
* This does not cause or change the rate of unsolicited cellInfoList().
*
- * This is identitcal to getCellInfoList in V1.0, but it requests updated version of CellInfo.
+ * This is identical to getCellInfoList in V1.0, but it requests updated version of CellInfo.
*
* @param serial Serial number of request.
*
@@ -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/IRadioResponse.hal b/radio/1.6/IRadioResponse.hal
index 6ad5cf2..56ce809 100644
--- a/radio/1.6/IRadioResponse.hal
+++ b/radio/1.6/IRadioResponse.hal
@@ -19,6 +19,7 @@
import @1.0::SendSmsResult;
import @1.4::RadioAccessFamily;
import @1.5::IRadioResponse;
+import @1.5::RadioAccessSpecifier;
import @1.6::Call;
import @1.6::CellInfo;
import @1.6::RegStateResult;
@@ -344,6 +345,7 @@
/**
* @param info Response info struct containing response type, serial no. and error
+ * @param specifiers List of RadioAccessSpecifiers that are scanned.
*
* Valid errors returned:
* RadioError:NONE
@@ -351,7 +353,8 @@
* RadioError:INTERNAL_ERR
* RadioError:INVALID_ARGUMENTS
*/
- oneway getSystemSelectionChannelsResponse(RadioResponseInfo info);
+ oneway getSystemSelectionChannelsResponse(
+ RadioResponseInfo info, vec<RadioAccessSpecifier> specifiers);
/**
* This is identical to getCellInfoListResponse_1_5 but uses an updated version of CellInfo.
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/radio/1.6/vts/functional/radio_hidl_hal_utils_v1_6.h b/radio/1.6/vts/functional/radio_hidl_hal_utils_v1_6.h
index f32e312..f610f2a 100644
--- a/radio/1.6/vts/functional/radio_hidl_hal_utils_v1_6.h
+++ b/radio/1.6/vts/functional/radio_hidl_hal_utils_v1_6.h
@@ -805,7 +805,8 @@
const ::android::hardware::radio::V1_6::RadioResponseInfo& info);
Return<void> getSystemSelectionChannelsResponse(
- const ::android::hardware::radio::V1_6::RadioResponseInfo& info);
+ const ::android::hardware::radio::V1_6::RadioResponseInfo& info,
+ const hidl_vec<::android::hardware::radio::V1_5::RadioAccessSpecifier>& specifier);
Return<void> getSignalStrengthResponse_1_6(
const ::android::hardware::radio::V1_6::RadioResponseInfo& info,
diff --git a/radio/1.6/vts/functional/radio_response.cpp b/radio/1.6/vts/functional/radio_response.cpp
index fad3f12..027e9ac 100644
--- a/radio/1.6/vts/functional/radio_response.cpp
+++ b/radio/1.6/vts/functional/radio_response.cpp
@@ -1190,7 +1190,8 @@
}
Return<void> RadioResponse_v1_6::getSystemSelectionChannelsResponse(
- const ::android::hardware::radio::V1_6::RadioResponseInfo& info) {
+ const ::android::hardware::radio::V1_6::RadioResponseInfo& info,
+ const hidl_vec<::android::hardware::radio::V1_5::RadioAccessSpecifier>& /*specifier*/) {
rspInfo = info;
parent_v1_6.notify(info.serial);
return Void();
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/aidl/vts/performance/Android.bp b/security/keymint/aidl/vts/performance/Android.bp
new file mode 100644
index 0000000..03240c3
--- /dev/null
+++ b/security/keymint/aidl/vts/performance/Android.bp
@@ -0,0 +1,38 @@
+//
+// 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_benchmark {
+ name: "VtsAidlKeyMintBenchmarkTest",
+ defaults: [
+ "VtsHalTargetTestDefaults",
+ "use_libaidlvintf_gtest_helper_static",
+ ],
+ srcs: [
+ "KeyMintBenchmark.cpp",
+ ],
+ shared_libs: [
+ "libbinder_ndk",
+ "libcrypto",
+ "libkeymint",
+ "libkeymint_support",
+ ],
+ static_libs: [
+ "android.hardware.security.keymint-V1-ndk_platform",
+ "android.hardware.security.secureclock-V1-ndk_platform",
+ "libcppbor_external",
+ "libchrome",
+ ],
+}
diff --git a/security/keymint/aidl/vts/performance/KeyMintBenchmark.cpp b/security/keymint/aidl/vts/performance/KeyMintBenchmark.cpp
new file mode 100644
index 0000000..f87ca78
--- /dev/null
+++ b/security/keymint/aidl/vts/performance/KeyMintBenchmark.cpp
@@ -0,0 +1,714 @@
+/*
+ * 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_benchmark"
+
+#include <base/command_line.h>
+#include <benchmark/benchmark.h>
+#include <iostream>
+
+#include <aidl/Vintf.h>
+#include <aidl/android/hardware/security/keymint/ErrorCode.h>
+#include <aidl/android/hardware/security/keymint/IKeyMintDevice.h>
+#include <android/binder_manager.h>
+#include <binder/IServiceManager.h>
+#include <keymint_support/authorization_set.h>
+
+#define SMALL_MESSAGE_SIZE 64
+#define MEDIUM_MESSAGE_SIZE 1024
+#define LARGE_MESSAGE_SIZE 131072
+
+namespace aidl::android::hardware::security::keymint::test {
+
+::std::ostream& operator<<(::std::ostream& os, const keymint::AuthorizationSet& set);
+
+using ::android::sp;
+using Status = ::ndk::ScopedAStatus;
+using ::std::optional;
+using ::std::shared_ptr;
+using ::std::string;
+using ::std::vector;
+
+class KeyMintBenchmarkTest {
+ public:
+ KeyMintBenchmarkTest() {
+ message_cache_.push_back(string(SMALL_MESSAGE_SIZE, 'x'));
+ message_cache_.push_back(string(MEDIUM_MESSAGE_SIZE, 'x'));
+ message_cache_.push_back(string(LARGE_MESSAGE_SIZE, 'x'));
+ }
+
+ static KeyMintBenchmarkTest* newInstance(const char* instanceName) {
+ if (AServiceManager_isDeclared(instanceName)) {
+ ::ndk::SpAIBinder binder(AServiceManager_waitForService(instanceName));
+ KeyMintBenchmarkTest* test = new KeyMintBenchmarkTest();
+ test->InitializeKeyMint(IKeyMintDevice::fromBinder(binder));
+ return test;
+ } else {
+ return nullptr;
+ }
+ }
+
+ int getError() { return static_cast<int>(error_); }
+
+ const string& GenerateMessage(int size) {
+ for (const string& message : message_cache_) {
+ if (message.size() == size) {
+ return message;
+ }
+ }
+ string message = string(size, 'x');
+ message_cache_.push_back(message);
+ return std::move(message);
+ }
+
+ optional<BlockMode> getBlockMode(string transform) {
+ if (transform.find("/ECB") != string::npos) {
+ return BlockMode::ECB;
+ } else if (transform.find("/CBC") != string::npos) {
+ return BlockMode::CBC;
+ } else if (transform.find("/CTR") != string::npos) {
+ return BlockMode::CTR;
+ } else if (transform.find("/GCM") != string::npos) {
+ return BlockMode::GCM;
+ }
+ return {};
+ }
+
+ PaddingMode getPadding(string transform, bool sign) {
+ if (transform.find("/PKCS7") != string::npos) {
+ return PaddingMode::PKCS7;
+ } else if (transform.find("/PSS") != string::npos) {
+ return PaddingMode::RSA_PSS;
+ } else if (transform.find("/OAEP") != string::npos) {
+ return PaddingMode::RSA_OAEP;
+ } else if (transform.find("/PKCS1") != string::npos) {
+ return sign ? PaddingMode::RSA_PKCS1_1_5_SIGN : PaddingMode::RSA_PKCS1_1_5_ENCRYPT;
+ } else if (sign && transform.find("RSA") != string::npos) {
+ // RSA defaults to PKCS1 for sign
+ return PaddingMode::RSA_PKCS1_1_5_SIGN;
+ }
+ return PaddingMode::NONE;
+ }
+
+ optional<Algorithm> getAlgorithm(string transform) {
+ if (transform.find("AES") != string::npos) {
+ return Algorithm::AES;
+ } else if (transform.find("Hmac") != string::npos) {
+ return Algorithm::HMAC;
+ } else if (transform.find("DESede") != string::npos) {
+ return Algorithm::TRIPLE_DES;
+ } else if (transform.find("RSA") != string::npos) {
+ return Algorithm::RSA;
+ } else if (transform.find("EC") != string::npos) {
+ return Algorithm::EC;
+ }
+ std::cerr << "Can't find algorithm for " << transform << std::endl;
+ return {};
+ }
+
+ Digest getDigest(string transform) {
+ if (transform.find("MD5") != string::npos) {
+ return Digest::MD5;
+ } else if (transform.find("SHA1") != string::npos ||
+ transform.find("SHA-1") != string::npos) {
+ return Digest::SHA1;
+ } else if (transform.find("SHA224") != string::npos) {
+ return Digest::SHA_2_224;
+ } else if (transform.find("SHA256") != string::npos) {
+ return Digest::SHA_2_256;
+ } else if (transform.find("SHA384") != string::npos) {
+ return Digest::SHA_2_384;
+ } else if (transform.find("SHA512") != string::npos) {
+ return Digest::SHA_2_512;
+ } else if (transform.find("RSA") != string::npos &&
+ transform.find("OAEP") != string::npos) {
+ return Digest::SHA1;
+ } else if (transform.find("Hmac") != string::npos) {
+ return Digest::SHA_2_256;
+ }
+ return Digest::NONE;
+ }
+
+ bool GenerateKey(string transform, int keySize, bool sign = false) {
+ if (transform == key_transform_) {
+ return true;
+ } else if (key_transform_ != "") {
+ // Deleting old key first
+ key_transform_ = "";
+ if (DeleteKey() != ErrorCode::OK) {
+ return false;
+ }
+ }
+ std::optional<Algorithm> algorithm = getAlgorithm(transform);
+ if (!algorithm) {
+ std::cerr << "Error: invalid algorithm " << transform << std::endl;
+ return false;
+ }
+ key_transform_ = transform;
+ AuthorizationSetBuilder authSet = AuthorizationSetBuilder()
+ .Authorization(TAG_NO_AUTH_REQUIRED)
+ .Authorization(TAG_PURPOSE, KeyPurpose::ENCRYPT)
+ .Authorization(TAG_PURPOSE, KeyPurpose::DECRYPT)
+ .Authorization(TAG_PURPOSE, KeyPurpose::SIGN)
+ .Authorization(TAG_PURPOSE, KeyPurpose::VERIFY)
+ .Authorization(TAG_KEY_SIZE, keySize)
+ .Authorization(TAG_ALGORITHM, algorithm.value())
+ .Digest(getDigest(transform))
+ .Padding(getPadding(transform, sign));
+ std::optional<BlockMode> blockMode = getBlockMode(transform);
+ if (blockMode) {
+ authSet.BlockMode(blockMode.value());
+ if (blockMode == BlockMode::GCM) {
+ authSet.Authorization(TAG_MIN_MAC_LENGTH, 128);
+ }
+ }
+ if (algorithm == Algorithm::HMAC) {
+ authSet.Authorization(TAG_MIN_MAC_LENGTH, 128);
+ }
+ if (algorithm == Algorithm::RSA) {
+ authSet.Authorization(TAG_RSA_PUBLIC_EXPONENT, 65537U);
+ authSet.SetDefaultValidity();
+ }
+ if (algorithm == Algorithm::EC) {
+ authSet.SetDefaultValidity();
+ }
+ error_ = GenerateKey(authSet);
+ return error_ == ErrorCode::OK;
+ }
+
+ AuthorizationSet getOperationParams(string transform, bool sign = false) {
+ AuthorizationSetBuilder builder = AuthorizationSetBuilder()
+ .Padding(getPadding(transform, sign))
+ .Digest(getDigest(transform));
+ std::optional<BlockMode> blockMode = getBlockMode(transform);
+ if (sign && (transform.find("Hmac") != string::npos)) {
+ builder.Authorization(TAG_MAC_LENGTH, 128);
+ }
+ if (blockMode) {
+ builder.BlockMode(*blockMode);
+ if (blockMode == BlockMode::GCM) {
+ builder.Authorization(TAG_MAC_LENGTH, 128);
+ }
+ }
+ return std::move(builder);
+ }
+
+ optional<string> Process(const string& message, const AuthorizationSet& /*in_params*/,
+ AuthorizationSet* out_params, const string& signature = "") {
+ static const int HIDL_BUFFER_LIMIT = 1 << 14; // 16KB
+ ErrorCode result;
+
+ // Update
+ AuthorizationSet update_params;
+ AuthorizationSet update_out_params;
+ string output;
+ string aidl_output;
+ int32_t input_consumed = 0;
+ int32_t aidl_input_consumed = 0;
+ while (message.length() - input_consumed > 0) {
+ result = Update(update_params, message.substr(input_consumed, HIDL_BUFFER_LIMIT),
+ &update_out_params, &aidl_output, &aidl_input_consumed);
+ if (result != ErrorCode::OK) {
+ error_ = result;
+ return {};
+ }
+ output.append(aidl_output);
+ input_consumed += aidl_input_consumed;
+ aidl_output.clear();
+ }
+
+ // Finish
+ AuthorizationSet finish_params;
+ AuthorizationSet finish_out_params;
+ result = Finish(finish_params, message.substr(input_consumed), signature,
+ &finish_out_params, &aidl_output);
+ if (result != ErrorCode::OK) {
+ error_ = result;
+ return {};
+ }
+ output.append(aidl_output);
+ out_params->push_back(finish_out_params);
+ return output;
+ }
+
+ ErrorCode DeleteKey() {
+ Status result = keymint_->deleteKey(key_blob_);
+ key_blob_ = vector<uint8_t>();
+ return GetReturnErrorCode(result);
+ }
+
+ ErrorCode Begin(KeyPurpose purpose, const AuthorizationSet& in_params,
+ AuthorizationSet* out_params) {
+ Status result;
+ BeginResult out;
+ result = keymint_->begin(purpose, key_blob_, in_params.vector_data(), HardwareAuthToken(),
+ &out);
+ if (result.isOk()) {
+ *out_params = out.params;
+ op_ = out.operation;
+ }
+ return GetReturnErrorCode(result);
+ }
+
+ SecurityLevel securityLevel_;
+ string name_;
+
+ private:
+ ErrorCode GenerateKey(const AuthorizationSet& key_desc,
+ const optional<AttestationKey>& attest_key = std::nullopt) {
+ key_blob_.clear();
+ KeyCreationResult creationResult;
+ Status result = keymint_->generateKey(key_desc.vector_data(), attest_key, &creationResult);
+ if (result.isOk()) {
+ key_blob_ = std::move(creationResult.keyBlob);
+ creationResult.keyCharacteristics.clear();
+ creationResult.certificateChain.clear();
+ }
+ return GetReturnErrorCode(result);
+ }
+
+ void InitializeKeyMint(std::shared_ptr<IKeyMintDevice> keyMint) {
+ if (!keyMint) {
+ std::cerr << "Trying initialize nullptr in InitializeKeyMint" << std::endl;
+ return;
+ }
+ keymint_ = std::move(keyMint);
+ KeyMintHardwareInfo info;
+ Status result = keymint_->getHardwareInfo(&info);
+ if (!result.isOk()) {
+ std::cerr << "InitializeKeyMint: getHardwareInfo failed with "
+ << result.getServiceSpecificError() << std::endl;
+ }
+ securityLevel_ = info.securityLevel;
+ name_.assign(info.keyMintName.begin(), info.keyMintName.end());
+ }
+
+ ErrorCode Finish(const AuthorizationSet& in_params, const string& input,
+ const string& signature, AuthorizationSet* out_params, string* output) {
+ Status result;
+ if (!op_) {
+ std::cerr << "Finish: Operation is nullptr" << std::endl;
+ return ErrorCode::UNEXPECTED_NULL_POINTER;
+ }
+ KeyParameterArray key_params;
+ key_params.params = in_params.vector_data();
+
+ KeyParameterArray in_keyParams;
+ in_keyParams.params = in_params.vector_data();
+
+ std::optional<KeyParameterArray> out_keyParams;
+ std::optional<vector<uint8_t>> o_put;
+
+ vector<uint8_t> oPut;
+ result = op_->finish(in_keyParams, vector<uint8_t>(input.begin(), input.end()),
+ vector<uint8_t>(signature.begin(), signature.end()), {}, {},
+ &out_keyParams, &oPut);
+
+ if (result.isOk()) {
+ if (out_keyParams) {
+ out_params->push_back(AuthorizationSet(out_keyParams->params));
+ }
+ output->append(oPut.begin(), oPut.end());
+ }
+ op_.reset();
+ return GetReturnErrorCode(result);
+ }
+
+ ErrorCode Update(const AuthorizationSet& in_params, const string& input,
+ AuthorizationSet* out_params, string* output, int32_t* input_consumed) {
+ Status result;
+ if (!op_) {
+ std::cerr << "Update: Operation is nullptr" << std::endl;
+ return ErrorCode::UNEXPECTED_NULL_POINTER;
+ }
+
+ KeyParameterArray key_params;
+ key_params.params = in_params.vector_data();
+
+ KeyParameterArray in_keyParams;
+ in_keyParams.params = in_params.vector_data();
+
+ std::optional<KeyParameterArray> out_keyParams;
+ std::optional<ByteArray> o_put;
+ result = op_->update(in_keyParams, vector<uint8_t>(input.begin(), input.end()), {}, {},
+ &out_keyParams, &o_put, input_consumed);
+
+ if (result.isOk()) {
+ if (o_put) {
+ output->append(o_put->data.begin(), o_put->data.end());
+ }
+
+ if (out_keyParams) {
+ out_params->push_back(AuthorizationSet(out_keyParams->params));
+ }
+ }
+
+ return GetReturnErrorCode(result);
+ }
+
+ ErrorCode GetReturnErrorCode(const Status& result) {
+ error_ = static_cast<ErrorCode>(result.getServiceSpecificError());
+ if (result.isOk()) return ErrorCode::OK;
+
+ if (result.getExceptionCode() == EX_SERVICE_SPECIFIC) {
+ return static_cast<ErrorCode>(result.getServiceSpecificError());
+ }
+
+ return ErrorCode::UNKNOWN_ERROR;
+ }
+
+ std::shared_ptr<IKeyMintOperation> op_;
+ vector<Certificate> cert_chain_;
+ vector<uint8_t> key_blob_;
+ vector<KeyCharacteristics> key_characteristics_;
+ std::shared_ptr<IKeyMintDevice> keymint_;
+ std::vector<string> message_cache_;
+ std::string key_transform_;
+ ErrorCode error_;
+};
+
+KeyMintBenchmarkTest* keymintTest;
+
+static void settings(benchmark::internal::Benchmark* benchmark) {
+ benchmark->Unit(benchmark::kMillisecond);
+}
+
+static void addDefaultLabel(benchmark::State& state) {
+ std::string secLevel;
+ switch (keymintTest->securityLevel_) {
+ case SecurityLevel::STRONGBOX:
+ secLevel = "STRONGBOX";
+ break;
+ case SecurityLevel::SOFTWARE:
+ secLevel = "SOFTWARE";
+ break;
+ case SecurityLevel::TRUSTED_ENVIRONMENT:
+ secLevel = "TEE";
+ break;
+ case SecurityLevel::KEYSTORE:
+ secLevel = "KEYSTORE";
+ break;
+ }
+ state.SetLabel("hardware_name:" + keymintTest->name_ + " sec_level:" + secLevel);
+}
+
+// clang-format off
+#define BENCHMARK_KM(func, transform, keySize) \
+ BENCHMARK_CAPTURE(func, transform/keySize, #transform "/" #keySize, keySize)->Apply(settings);
+#define BENCHMARK_KM_MSG(func, transform, keySize, msgSize) \
+ BENCHMARK_CAPTURE(func, transform/keySize/msgSize, #transform "/" #keySize "/" #msgSize, \
+ keySize, msgSize) \
+ ->Apply(settings);
+
+#define BENCHMARK_KM_ALL_MSGS(func, transform, keySize) \
+ BENCHMARK_KM_MSG(func, transform, keySize, SMALL_MESSAGE_SIZE) \
+ BENCHMARK_KM_MSG(func, transform, keySize, MEDIUM_MESSAGE_SIZE) \
+ BENCHMARK_KM_MSG(func, transform, keySize, LARGE_MESSAGE_SIZE)
+
+#define BENCHMARK_KM_CIPHER(transform, keySize, msgSize) \
+ BENCHMARK_KM_MSG(encrypt, transform, keySize, msgSize) \
+ BENCHMARK_KM_MSG(decrypt, transform, keySize, msgSize)
+
+#define BENCHMARK_KM_CIPHER_ALL_MSGS(transform, keySize) \
+ BENCHMARK_KM_ALL_MSGS(encrypt, transform, keySize) \
+ BENCHMARK_KM_ALL_MSGS(decrypt, transform, keySize)
+
+#define BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, keySize) \
+ BENCHMARK_KM_ALL_MSGS(sign, transform, keySize) \
+ BENCHMARK_KM_ALL_MSGS(verify, transform, keySize)
+// clang-format on
+
+/*
+ * ============= KeyGen TESTS ==================
+ */
+static void keygen(benchmark::State& state, string transform, int keySize) {
+ addDefaultLabel(state);
+ for (auto _ : state) {
+ if (!keymintTest->GenerateKey(transform, keySize)) {
+ state.SkipWithError(
+ ("Key generation error, " + std::to_string(keymintTest->getError())).c_str());
+ }
+ state.PauseTiming();
+
+ keymintTest->DeleteKey();
+ state.ResumeTiming();
+ }
+}
+
+BENCHMARK_KM(keygen, AES, 128);
+BENCHMARK_KM(keygen, AES, 256);
+
+BENCHMARK_KM(keygen, RSA, 2048);
+BENCHMARK_KM(keygen, RSA, 3072);
+BENCHMARK_KM(keygen, RSA, 4096);
+
+BENCHMARK_KM(keygen, EC, 224);
+BENCHMARK_KM(keygen, EC, 256);
+BENCHMARK_KM(keygen, EC, 384);
+BENCHMARK_KM(keygen, EC, 521);
+
+BENCHMARK_KM(keygen, DESede, 168);
+
+BENCHMARK_KM(keygen, Hmac, 64);
+BENCHMARK_KM(keygen, Hmac, 128);
+BENCHMARK_KM(keygen, Hmac, 256);
+BENCHMARK_KM(keygen, Hmac, 512);
+
+/*
+ * ============= SIGNATURE TESTS ==================
+ */
+
+static void sign(benchmark::State& state, string transform, int keySize, int msgSize) {
+ addDefaultLabel(state);
+ if (!keymintTest->GenerateKey(transform, keySize, true)) {
+ state.SkipWithError(
+ ("Key generation error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+
+ auto in_params = keymintTest->getOperationParams(transform, true);
+ AuthorizationSet out_params;
+ string message = keymintTest->GenerateMessage(msgSize);
+
+ for (auto _ : state) {
+ state.PauseTiming();
+ ErrorCode error = keymintTest->Begin(KeyPurpose::SIGN, in_params, &out_params);
+ if (error != ErrorCode::OK) {
+ state.SkipWithError(
+ ("Error beginning sign, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ state.ResumeTiming();
+ out_params.Clear();
+ if (!keymintTest->Process(message, in_params, &out_params)) {
+ state.SkipWithError(("Sign error, " + std::to_string(keymintTest->getError())).c_str());
+ break;
+ }
+ }
+}
+
+static void verify(benchmark::State& state, string transform, int keySize, int msgSize) {
+ addDefaultLabel(state);
+ if (!keymintTest->GenerateKey(transform, keySize, true)) {
+ state.SkipWithError(
+ ("Key generation error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ AuthorizationSet out_params;
+ auto in_params = keymintTest->getOperationParams(transform, true);
+ string message = keymintTest->GenerateMessage(msgSize);
+ ErrorCode error = keymintTest->Begin(KeyPurpose::SIGN, in_params, &out_params);
+ if (error != ErrorCode::OK) {
+ state.SkipWithError(
+ ("Error beginning sign, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ std::optional<string> signature = keymintTest->Process(message, in_params, &out_params);
+ if (!signature) {
+ state.SkipWithError(("Sign error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ out_params.Clear();
+ if (transform.find("Hmac") != string::npos) {
+ in_params = keymintTest->getOperationParams(transform, false);
+ }
+ for (auto _ : state) {
+ state.PauseTiming();
+ error = keymintTest->Begin(KeyPurpose::VERIFY, in_params, &out_params);
+ if (error != ErrorCode::OK) {
+ state.SkipWithError(
+ ("Verify begin error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ state.ResumeTiming();
+ if (!keymintTest->Process(message, in_params, &out_params, *signature)) {
+ state.SkipWithError(
+ ("Verify error, " + std::to_string(keymintTest->getError())).c_str());
+ break;
+ }
+ }
+}
+
+// clang-format off
+#define BENCHMARK_KM_SIGNATURE_ALL_HMAC_KEYS(transform) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 64) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 128) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 256) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 512)
+
+BENCHMARK_KM_SIGNATURE_ALL_HMAC_KEYS(HmacSHA1)
+BENCHMARK_KM_SIGNATURE_ALL_HMAC_KEYS(HmacSHA256)
+BENCHMARK_KM_SIGNATURE_ALL_HMAC_KEYS(HmacSHA224)
+BENCHMARK_KM_SIGNATURE_ALL_HMAC_KEYS(HmacSHA256)
+BENCHMARK_KM_SIGNATURE_ALL_HMAC_KEYS(HmacSHA384)
+BENCHMARK_KM_SIGNATURE_ALL_HMAC_KEYS(HmacSHA512)
+
+#define BENCHMARK_KM_SIGNATURE_ALL_ECDSA_KEYS(transform) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 224) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 256) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 384) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 521)
+
+BENCHMARK_KM_SIGNATURE_ALL_ECDSA_KEYS(NONEwithECDSA);
+BENCHMARK_KM_SIGNATURE_ALL_ECDSA_KEYS(SHA1withECDSA);
+BENCHMARK_KM_SIGNATURE_ALL_ECDSA_KEYS(SHA224withECDSA);
+BENCHMARK_KM_SIGNATURE_ALL_ECDSA_KEYS(SHA256withECDSA);
+BENCHMARK_KM_SIGNATURE_ALL_ECDSA_KEYS(SHA384withECDSA);
+BENCHMARK_KM_SIGNATURE_ALL_ECDSA_KEYS(SHA512withECDSA);
+
+#define BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(transform) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 2048) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 3072) \
+ BENCHMARK_KM_SIGNATURE_ALL_MSGS(transform, 4096)
+
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(MD5withRSA);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA1withRSA);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA224withRSA);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA384withRSA);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA512withRSA);
+
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(MD5withRSA/PSS);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA1withRSA/PSS);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA224withRSA/PSS);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA384withRSA/PSS);
+BENCHMARK_KM_SIGNATURE_ALL_RSA_KEYS(SHA512withRSA/PSS);
+// clang-format on
+
+/*
+ * ============= CIPHER TESTS ==================
+ */
+
+static void encrypt(benchmark::State& state, string transform, int keySize, int msgSize) {
+ addDefaultLabel(state);
+ if (!keymintTest->GenerateKey(transform, keySize)) {
+ state.SkipWithError(
+ ("Key generation error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ auto in_params = keymintTest->getOperationParams(transform);
+ AuthorizationSet out_params;
+ string message = keymintTest->GenerateMessage(msgSize);
+
+ for (auto _ : state) {
+ state.PauseTiming();
+ auto error = keymintTest->Begin(KeyPurpose::ENCRYPT, in_params, &out_params);
+ if (error != ErrorCode::OK) {
+ state.SkipWithError(
+ ("Encryption begin error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ out_params.Clear();
+ state.ResumeTiming();
+ if (!keymintTest->Process(message, in_params, &out_params)) {
+ state.SkipWithError(
+ ("Encryption error, " + std::to_string(keymintTest->getError())).c_str());
+ break;
+ }
+ }
+}
+
+static void decrypt(benchmark::State& state, string transform, int keySize, int msgSize) {
+ addDefaultLabel(state);
+ if (!keymintTest->GenerateKey(transform, keySize)) {
+ state.SkipWithError(
+ ("Key generation error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ AuthorizationSet out_params;
+ AuthorizationSet in_params = keymintTest->getOperationParams(transform);
+ string message = keymintTest->GenerateMessage(msgSize);
+ auto error = keymintTest->Begin(KeyPurpose::ENCRYPT, in_params, &out_params);
+ if (error != ErrorCode::OK) {
+ state.SkipWithError(
+ ("Encryption begin error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ auto encryptedMessage = keymintTest->Process(message, in_params, &out_params);
+ if (!encryptedMessage) {
+ state.SkipWithError(
+ ("Encryption error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ in_params.push_back(out_params);
+ out_params.Clear();
+ for (auto _ : state) {
+ state.PauseTiming();
+ error = keymintTest->Begin(KeyPurpose::DECRYPT, in_params, &out_params);
+ if (error != ErrorCode::OK) {
+ state.SkipWithError(
+ ("Decryption begin error, " + std::to_string(keymintTest->getError())).c_str());
+ return;
+ }
+ state.ResumeTiming();
+ if (!keymintTest->Process(*encryptedMessage, in_params, &out_params)) {
+ state.SkipWithError(
+ ("Decryption error, " + std::to_string(keymintTest->getError())).c_str());
+ break;
+ }
+ }
+}
+
+// clang-format off
+// AES
+#define BENCHMARK_KM_CIPHER_ALL_AES_KEYS(transform) \
+ BENCHMARK_KM_CIPHER_ALL_MSGS(transform, 128) \
+ BENCHMARK_KM_CIPHER_ALL_MSGS(transform, 256)
+
+BENCHMARK_KM_CIPHER_ALL_AES_KEYS(AES/CBC/NoPadding);
+BENCHMARK_KM_CIPHER_ALL_AES_KEYS(AES/CBC/PKCS7Padding);
+BENCHMARK_KM_CIPHER_ALL_AES_KEYS(AES/CTR/NoPadding);
+BENCHMARK_KM_CIPHER_ALL_AES_KEYS(AES/ECB/NoPadding);
+BENCHMARK_KM_CIPHER_ALL_AES_KEYS(AES/ECB/PKCS7Padding);
+BENCHMARK_KM_CIPHER_ALL_AES_KEYS(AES/GCM/NoPadding);
+
+// Triple DES
+BENCHMARK_KM_CIPHER_ALL_MSGS(DESede/CBC/NoPadding, 168);
+BENCHMARK_KM_CIPHER_ALL_MSGS(DESede/CBC/PKCS7Padding, 168);
+BENCHMARK_KM_CIPHER_ALL_MSGS(DESede/ECB/NoPadding, 168);
+BENCHMARK_KM_CIPHER_ALL_MSGS(DESede/ECB/PKCS7Padding, 168);
+
+#define BENCHMARK_KM_CIPHER_ALL_RSA_KEYS(transform, msgSize) \
+ BENCHMARK_KM_CIPHER(transform, 2048, msgSize) \
+ BENCHMARK_KM_CIPHER(transform, 3072, msgSize) \
+ BENCHMARK_KM_CIPHER(transform, 4096, msgSize)
+
+BENCHMARK_KM_CIPHER_ALL_RSA_KEYS(RSA/ECB/NoPadding, SMALL_MESSAGE_SIZE);
+BENCHMARK_KM_CIPHER_ALL_RSA_KEYS(RSA/ECB/PKCS1Padding, SMALL_MESSAGE_SIZE);
+BENCHMARK_KM_CIPHER_ALL_RSA_KEYS(RSA/ECB/OAEPPadding, SMALL_MESSAGE_SIZE);
+
+// clang-format on
+} // namespace aidl::android::hardware::security::keymint::test
+
+int main(int argc, char** argv) {
+ ::benchmark::Initialize(&argc, argv);
+ base::CommandLine::Init(argc, argv);
+ base::CommandLine* command_line = base::CommandLine::ForCurrentProcess();
+ auto service_name = command_line->GetSwitchValueASCII("service_name");
+ if (service_name.empty()) {
+ service_name =
+ std::string(
+ aidl::android::hardware::security::keymint::IKeyMintDevice::descriptor) +
+ "/default";
+ }
+ std::cerr << service_name << std::endl;
+ aidl::android::hardware::security::keymint::test::keymintTest =
+ aidl::android::hardware::security::keymint::test::KeyMintBenchmarkTest::newInstance(
+ service_name.c_str());
+ if (!aidl::android::hardware::security::keymint::test::keymintTest) {
+ return 1;
+ }
+ ::benchmark::RunSpecifiedBenchmarks();
+}
diff --git a/security/keymint/aidl/vts/performance/README b/security/keymint/aidl/vts/performance/README
new file mode 100644
index 0000000..1221ad8
--- /dev/null
+++ b/security/keymint/aidl/vts/performance/README
@@ -0,0 +1,28 @@
+# KeyMint Benchmark
+
+The KeyMint Benchmark is a standalone tool for measuring the performance of
+ KeyMint implementations.
+
+## Building
+
+Build:
+`m VtsAidlKeyMintBenchmarkTest`
+
+Transfer to device/emulator:
+`adb sync data`
+
+The benchmark executable will be located at
+ `data/benchmarktest/VtsAidlKeyMintBenchmarkTest` on the device.
+
+## Usage
+
+KeyMint Benchmark is built on [Google microbenchmark
+library](https://github.com/google/benchmark). All of the commandline arguments
+provided by the microbenchmark library are valid, such as
+`--benchmark_filter=<regex>` or `benchmark_out_format={json|console|csv}`.
+In addition to the command line arguments provided by microbenchmark,
+`--service_name=<service_name>` is provided to allow specification of the KeyMint
+fully qualified service name, e.g. specify
+`--service_name=android.hardware.security.keymint.IKeyMintDevice/default` to
+benchmark default implementation of KeyMint.
+
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, ×pec));
+ 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(¶ms));
+ 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/Demux.cpp b/tv/tuner/1.1/default/Demux.cpp
index 66c95dc..f4e4a91 100644
--- a/tv/tuner/1.1/default/Demux.cpp
+++ b/tv/tuner/1.1/default/Demux.cpp
@@ -27,12 +27,16 @@
namespace implementation {
#define WAIT_TIMEOUT 3000000000
+
Demux::Demux(uint32_t demuxId, sp<Tuner> tuner) {
mDemuxId = demuxId;
mTunerService = tuner;
}
-Demux::~Demux() {}
+Demux::~Demux() {
+ mFrontendInputThreadRunning = false;
+ std::lock_guard<std::mutex> lock(mFrontendInputThreadLock);
+}
Return<Result> Demux::setFrontendDataSource(uint32_t frontendId) {
ALOGV("%s", __FUNCTION__);
@@ -171,6 +175,8 @@
mFilters.clear();
mLastUsedFilterId = -1;
mTunerService->removeDemux(mDemuxId);
+ mFrontendInputThreadRunning = false;
+ std::lock_guard<std::mutex> lock(mFrontendInputThreadLock);
return Result::SUCCESS;
}
@@ -322,6 +328,7 @@
}
void Demux::startFrontendInputLoop() {
+ mFrontendInputThreadRunning = true;
pthread_create(&mFrontendInputThread, NULL, __threadLoopFrontend, this);
pthread_setname_np(mFrontendInputThread, "frontend_input_thread");
}
@@ -334,8 +341,6 @@
void Demux::frontendInputThreadLoop() {
std::lock_guard<std::mutex> lock(mFrontendInputThreadLock);
- mFrontendInputThreadRunning = true;
-
if (!mDvrPlayback) {
ALOGW("[Demux] No software Frontend input configured. Ending Frontend thread loop.");
mFrontendInputThreadRunning = false;
diff --git a/tv/tuner/1.1/default/Dvr.cpp b/tv/tuner/1.1/default/Dvr.cpp
index 3a4ef1b..93bb6a8 100644
--- a/tv/tuner/1.1/default/Dvr.cpp
+++ b/tv/tuner/1.1/default/Dvr.cpp
@@ -37,7 +37,10 @@
mDemux = demux;
}
-Dvr::~Dvr() {}
+Dvr::~Dvr() {
+ mDvrThreadRunning = false;
+ lock_guard<mutex> lock(mDvrThreadLock);
+}
Return<void> Dvr::getQueueDesc(getQueueDesc_cb _hidl_cb) {
ALOGV("%s", __FUNCTION__);
@@ -118,6 +121,9 @@
Return<Result> Dvr::start() {
ALOGV("%s", __FUNCTION__);
+ if (mDvrThreadRunning) {
+ return Result::SUCCESS;
+ }
if (!mCallback) {
return Result::NOT_INITIALIZED;
@@ -128,6 +134,7 @@
}
if (mType == DvrType::PLAYBACK) {
+ mDvrThreadRunning = true;
pthread_create(&mDvrThread, NULL, __threadLoopPlayback, this);
pthread_setname_np(mDvrThread, "playback_waiting_loop");
} else if (mType == DvrType::RECORD) {
@@ -144,7 +151,6 @@
ALOGV("%s", __FUNCTION__);
mDvrThreadRunning = false;
-
lock_guard<mutex> lock(mDvrThreadLock);
mIsRecordStarted = false;
@@ -164,6 +170,8 @@
Return<Result> Dvr::close() {
ALOGV("%s", __FUNCTION__);
+ mDvrThreadRunning = false;
+ lock_guard<mutex> lock(mDvrThreadLock);
return Result::SUCCESS;
}
@@ -199,7 +207,6 @@
void Dvr::playbackThreadLoop() {
ALOGD("[Dvr] playback threadLoop start.");
lock_guard<mutex> lock(mDvrThreadLock);
- mDvrThreadRunning = true;
while (mDvrThreadRunning) {
uint32_t efState = 0;
diff --git a/tv/tuner/1.1/default/Filter.cpp b/tv/tuner/1.1/default/Filter.cpp
index 6b2413c..2e29aa9 100644
--- a/tv/tuner/1.1/default/Filter.cpp
+++ b/tv/tuner/1.1/default/Filter.cpp
@@ -77,7 +77,10 @@
}
}
-Filter::~Filter() {}
+Filter::~Filter() {
+ mFilterThreadRunning = false;
+ std::lock_guard<std::mutex> lock(mFilterThreadLock);
+}
Return<void> Filter::getId64Bit(getId64Bit_cb _hidl_cb) {
ALOGV("%s", __FUNCTION__);
@@ -137,15 +140,14 @@
Return<Result> Filter::start() {
ALOGV("%s", __FUNCTION__);
-
+ mFilterThreadRunning = true;
return startFilterLoop();
}
Return<Result> Filter::stop() {
ALOGV("%s", __FUNCTION__);
-
mFilterThreadRunning = false;
-
+ std::lock_guard<std::mutex> lock(mFilterThreadLock);
return Result::SUCCESS;
}
@@ -185,6 +187,8 @@
Return<Result> Filter::close() {
ALOGV("%s", __FUNCTION__);
+ mFilterThreadRunning = false;
+ std::lock_guard<std::mutex> lock(mFilterThreadLock);
return mDemux->removeFilter(mFilterId);
}
@@ -331,9 +335,11 @@
}
void Filter::filterThreadLoop() {
- ALOGD("[Filter] filter %" PRIu64 " threadLoop start.", mFilterId);
+ if (!mFilterThreadRunning) {
+ return;
+ }
std::lock_guard<std::mutex> lock(mFilterThreadLock);
- mFilterThreadRunning = true;
+ ALOGD("[Filter] filter %" PRIu64 " threadLoop start.", mFilterId);
// For the first time of filter output, implementation needs to send the filter
// Event Callback without waiting for the DATA_CONSUMED to init the process.
@@ -382,6 +388,9 @@
// We do not wait for the last round of written data to be read to finish the thread
// because the VTS can verify the reading itself.
for (int i = 0; i < SECTION_WRITE_COUNT; i++) {
+ if (!mFilterThreadRunning) {
+ break;
+ }
while (mFilterThreadRunning && mIsUsingFMQ) {
status_t status = mFilterEventFlag->wait(
static_cast<uint32_t>(DemuxQueueNotifyBits::DATA_CONSUMED), &efState,
@@ -417,9 +426,8 @@
break;
}
}
- mFilterThreadRunning = false;
+ break;
}
-
ALOGD("[Filter] filter thread ended.");
}
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/tv/tuner/1.1/vts/functional/FilterTests.cpp b/tv/tuner/1.1/vts/functional/FilterTests.cpp
index d8fad3d..1617642 100644
--- a/tv/tuner/1.1/vts/functional/FilterTests.cpp
+++ b/tv/tuner/1.1/vts/functional/FilterTests.cpp
@@ -274,6 +274,7 @@
AssertionResult FilterTests::stopFilter(uint64_t filterId) {
EXPECT_TRUE(mFilters[filterId]) << "Test with getNewlyOpenedFilterId first.";
Result status = mFilters[filterId]->stop();
+
return AssertionResult(status == Result::SUCCESS);
}
diff --git a/tv/tuner/1.1/vts/functional/FrontendTests.cpp b/tv/tuner/1.1/vts/functional/FrontendTests.cpp
index 0948f74..887f8b8 100644
--- a/tv/tuner/1.1/vts/functional/FrontendTests.cpp
+++ b/tv/tuner/1.1/vts/functional/FrontendTests.cpp
@@ -305,6 +305,36 @@
return AssertionResult(status == Result::SUCCESS);
}
+AssertionResult FrontendTests::linkCiCam(uint32_t ciCamId) {
+ sp<android::hardware::tv::tuner::V1_1::IFrontend> frontend_1_1;
+ frontend_1_1 = android::hardware::tv::tuner::V1_1::IFrontend::castFrom(mFrontend);
+ if (frontend_1_1 == nullptr) {
+ EXPECT_TRUE(false) << "Couldn't get 1.1 IFrontend from the Hal implementation.";
+ return failure();
+ }
+
+ Result status;
+ uint32_t ltsId;
+ frontend_1_1->linkCiCam(ciCamId, [&](Result r, uint32_t id) {
+ status = r;
+ ltsId = id;
+ });
+
+ return AssertionResult(status == Result::SUCCESS);
+}
+
+AssertionResult FrontendTests::unlinkCiCam(uint32_t ciCamId) {
+ sp<android::hardware::tv::tuner::V1_1::IFrontend> frontend_1_1;
+ frontend_1_1 = android::hardware::tv::tuner::V1_1::IFrontend::castFrom(mFrontend);
+ if (frontend_1_1 == nullptr) {
+ EXPECT_TRUE(false) << "Couldn't get 1.1 IFrontend from the Hal implementation.";
+ return failure();
+ }
+
+ Result status = frontend_1_1->unlinkCiCam(ciCamId);
+ return AssertionResult(status == Result::SUCCESS);
+}
+
void FrontendTests::verifyFrontendStatusExt1_1(vector<FrontendStatusTypeExt1_1> statusTypes,
vector<FrontendStatusExt1_1> expectStatuses) {
ASSERT_TRUE(mFrontend) << "Frontend is not opened yet.";
@@ -465,6 +495,10 @@
ASSERT_TRUE(feId != INVALID_ID);
ASSERT_TRUE(openFrontendById(feId));
ASSERT_TRUE(setFrontendCallback());
+ if (frontendConf.canConnectToCiCam) {
+ ASSERT_TRUE(linkCiCam(frontendConf.ciCamId));
+ ASSERT_TRUE(unlinkCiCam(frontendConf.ciCamId));
+ }
ASSERT_TRUE(tuneFrontend(frontendConf, false /*testWithDemux*/));
verifyFrontendStatusExt1_1(frontendConf.tuneStatusTypes, frontendConf.expectTuneStatuses);
ASSERT_TRUE(stopTuneFrontend(false /*testWithDemux*/));
diff --git a/tv/tuner/1.1/vts/functional/FrontendTests.h b/tv/tuner/1.1/vts/functional/FrontendTests.h
index 243d9de..43c1579 100644
--- a/tv/tuner/1.1/vts/functional/FrontendTests.h
+++ b/tv/tuner/1.1/vts/functional/FrontendTests.h
@@ -123,6 +123,9 @@
AssertionResult closeFrontend();
AssertionResult getFrontendDtmbCaps(uint32_t);
+ AssertionResult linkCiCam(uint32_t ciCamId);
+ AssertionResult unlinkCiCam(uint32_t ciCamId);
+
void getFrontendIdByType(FrontendType feType, uint32_t& feId);
void tuneTest(FrontendConfig frontendConf);
void scanTest(FrontendConfig frontend, FrontendScanType type);
diff --git a/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TargetTest.cpp b/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TargetTest.cpp
index 2dcb9a1..2e6c87f 100644
--- a/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TargetTest.cpp
+++ b/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TargetTest.cpp
@@ -211,6 +211,11 @@
mFrontendTests.getFrontendDtmbCapsTest();
}
+TEST_P(TunerFrontendHidlTest, LinkToCiCam) {
+ description("Test Frontend link to CiCam");
+ mFrontendTests.tuneTest(frontendArray[defaultFrontend]);
+}
+
INSTANTIATE_TEST_SUITE_P(
PerInstance, TunerBroadcastHidlTest,
testing::ValuesIn(android::hardware::getAllHalInstanceNames(ITuner::descriptor)),
diff --git a/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TestConfigurations.h b/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TestConfigurations.h
index beae223..ecdf683 100644
--- a/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TestConfigurations.h
+++ b/tv/tuner/1.1/vts/functional/VtsHalTvTunerV1_1TestConfigurations.h
@@ -103,6 +103,8 @@
struct FrontendConfig {
bool isSoftwareFe;
+ bool canConnectToCiCam;
+ uint32_t ciCamId;
FrontendType type;
FrontendSettings settings;
FrontendSettingsExt1_1 settingsExt1_1;
@@ -121,6 +123,7 @@
static FrontendConfig frontendScanArray[SCAN_MAX];
static FilterConfig filterArray[FILTER_MAX];
static DvrConfig dvrArray[DVR_MAX];
+static int defaultFrontend = DVBT;
/** Configuration array for the frontend tune test */
inline void initFrontendConfig() {
@@ -150,6 +153,8 @@
frontendArray[DVBT].tuneStatusTypes = types;
frontendArray[DVBT].expectTuneStatuses = statuses;
frontendArray[DVBT].isSoftwareFe = true;
+ frontendArray[DVBT].canConnectToCiCam = true;
+ frontendArray[DVBT].ciCamId = 0;
frontendArray[DVBT].settingsExt1_1.settingExt.dvbt({
.transmissionMode =
android::hardware::tv::tuner::V1_1::FrontendDvbtTransmissionMode::MODE_8K_E,
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/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositeEffect.aidl b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositeEffect.aidl
index 8cb259f..0995d2d 100644
--- a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositeEffect.aidl
+++ b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositeEffect.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * 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.
+ *////////////////////////////////////////////////////////////////////////////////
// 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/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositePrimitive.aidl b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositePrimitive.aidl
index 3071dce3..0b4b527 100644
--- a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositePrimitive.aidl
+++ b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/CompositePrimitive.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * 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.
+ *////////////////////////////////////////////////////////////////////////////////
// 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/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/Effect.aidl b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/Effect.aidl
index 5ed4dc5..0d2b340 100644
--- a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/Effect.aidl
+++ b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/Effect.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * 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.
+ *////////////////////////////////////////////////////////////////////////////////
// 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/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/EffectStrength.aidl b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/EffectStrength.aidl
index 802d236..808644a 100644
--- a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/EffectStrength.aidl
+++ b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/EffectStrength.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * 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.
+ *////////////////////////////////////////////////////////////////////////////////
// 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/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibrator.aidl b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibrator.aidl
index 2de1d7b..1f2d946 100644
--- a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibrator.aidl
+++ b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibrator.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * 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.
+ *////////////////////////////////////////////////////////////////////////////////
// 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
@@ -33,6 +48,8 @@
android.hardware.vibrator.Effect[] getSupportedAlwaysOnEffects();
void alwaysOnEnable(in int id, in android.hardware.vibrator.Effect effect, in android.hardware.vibrator.EffectStrength strength);
void alwaysOnDisable(in int id);
+ float getResonantFrequency();
+ float getQFactor();
const int CAP_ON_CALLBACK = 1;
const int CAP_PERFORM_CALLBACK = 2;
const int CAP_AMPLITUDE_CONTROL = 4;
@@ -40,4 +57,6 @@
const int CAP_EXTERNAL_AMPLITUDE_CONTROL = 16;
const int CAP_COMPOSE_EFFECTS = 32;
const int CAP_ALWAYS_ON_CONTROL = 64;
+ const int CAP_GET_RESONANT_FREQUENCY = 128;
+ const int CAP_GET_Q_FACTOR = 256;
}
diff --git a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorCallback.aidl b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorCallback.aidl
index 3a1e7d8..f99ecc1 100644
--- a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorCallback.aidl
+++ b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorCallback.aidl
@@ -1,14 +1,29 @@
-///////////////////////////////////////////////////////////////////////////////
+/*
+ * 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.
+ *////////////////////////////////////////////////////////////////////////////////
// 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/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorManager.aidl b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorManager.aidl
index 99cd448..8e3ac88 100644
--- a/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorManager.aidl
+++ b/vibrator/aidl/aidl_api/android.hardware.vibrator/current/android/hardware/vibrator/IVibratorManager.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/vibrator/aidl/android/hardware/vibrator/IVibrator.aidl b/vibrator/aidl/android/hardware/vibrator/IVibrator.aidl
index cd7b603..cba76dc 100644
--- a/vibrator/aidl/android/hardware/vibrator/IVibrator.aidl
+++ b/vibrator/aidl/android/hardware/vibrator/IVibrator.aidl
@@ -52,6 +52,14 @@
* Whether alwaysOnEnable/alwaysOnDisable is supported.
*/
const int CAP_ALWAYS_ON_CONTROL = 1 << 6;
+ /**
+ * Whether getResonantFrequency is supported.
+ */
+ const int CAP_GET_RESONANT_FREQUENCY = 1 << 7;
+ /**
+ * Whether getQFactor is supported.
+ */
+ const int CAP_GET_Q_FACTOR = 1 << 8;
/**
* Determine capabilities of the vibrator HAL (CAP_* mask)
@@ -230,4 +238,20 @@
* @param id The device-specific always-on source ID to disable.
*/
void alwaysOnDisable(in int id);
+
+ /**
+ * Retrieve the measured resonant frequency of the actuator. This may not be supported
+ * and this support is reflected in getCapabilities (CAP_GET_RESONANT_FREQUENCY)
+ *
+ * @return Measured resonant frequency in Hz.
+ */
+ float getResonantFrequency();
+
+ /**
+ * Retrieve the measured Q factor. This may not be supported
+ * and this support is reflected in getCapabilities (CAP_GET_Q_FACTOR)
+ *
+ * @return Measured Q factor.
+ */
+ float getQFactor();
}
diff --git a/vibrator/aidl/default/Vibrator.cpp b/vibrator/aidl/default/Vibrator.cpp
index 1021e62..bf61bfe 100644
--- a/vibrator/aidl/default/Vibrator.cpp
+++ b/vibrator/aidl/default/Vibrator.cpp
@@ -27,12 +27,16 @@
static constexpr int32_t kComposeDelayMaxMs = 1000;
static constexpr int32_t kComposeSizeMax = 256;
+static constexpr float kResonantFrequency = 150.0;
+static constexpr float kQFactor = 11.0;
+
ndk::ScopedAStatus Vibrator::getCapabilities(int32_t* _aidl_return) {
LOG(INFO) << "Vibrator reporting capabilities";
*_aidl_return = IVibrator::CAP_ON_CALLBACK | IVibrator::CAP_PERFORM_CALLBACK |
IVibrator::CAP_AMPLITUDE_CONTROL | IVibrator::CAP_EXTERNAL_CONTROL |
IVibrator::CAP_EXTERNAL_AMPLITUDE_CONTROL | IVibrator::CAP_COMPOSE_EFFECTS |
- IVibrator::CAP_ALWAYS_ON_CONTROL;
+ IVibrator::CAP_ALWAYS_ON_CONTROL | IVibrator::CAP_GET_RESONANT_FREQUENCY |
+ IVibrator::CAP_GET_Q_FACTOR;
return ndk::ScopedAStatus::ok();
}
@@ -201,6 +205,16 @@
return ndk::ScopedAStatus::ok();
}
+ndk::ScopedAStatus Vibrator::getResonantFrequency(float *resonantFreqHz) {
+ *resonantFreqHz = kResonantFrequency;
+ return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Vibrator::getQFactor(float *qFactor) {
+ *qFactor = kQFactor;
+ return ndk::ScopedAStatus::ok();
+}
+
} // namespace vibrator
} // namespace hardware
} // namespace android
diff --git a/vibrator/aidl/default/include/vibrator-impl/Vibrator.h b/vibrator/aidl/default/include/vibrator-impl/Vibrator.h
index c3f3616..a2af963 100644
--- a/vibrator/aidl/default/include/vibrator-impl/Vibrator.h
+++ b/vibrator/aidl/default/include/vibrator-impl/Vibrator.h
@@ -44,6 +44,8 @@
ndk::ScopedAStatus getSupportedAlwaysOnEffects(std::vector<Effect>* _aidl_return) override;
ndk::ScopedAStatus alwaysOnEnable(int32_t id, Effect effect, EffectStrength strength) override;
ndk::ScopedAStatus alwaysOnDisable(int32_t id) override;
+ ndk::ScopedAStatus getResonantFrequency(float *resonantFreqHz) override;
+ ndk::ScopedAStatus getQFactor(float *qFactor) override;
};
} // namespace vibrator
diff --git a/vibrator/aidl/vts/VtsHalVibratorTargetTest.cpp b/vibrator/aidl/vts/VtsHalVibratorTargetTest.cpp
index adbb0cf..2540d0b 100644
--- a/vibrator/aidl/vts/VtsHalVibratorTargetTest.cpp
+++ b/vibrator/aidl/vts/VtsHalVibratorTargetTest.cpp
@@ -538,6 +538,28 @@
}
}
+TEST_P(VibratorAidl, GetResonantFrequency) {
+ float resonantFrequency;
+ Status status = vibrator->getResonantFrequency(&resonantFrequency);
+ if (capabilities & IVibrator::CAP_GET_RESONANT_FREQUENCY) {
+ ASSERT_NE(resonantFrequency, 0);
+ EXPECT_EQ(status.exceptionCode(), Status::EX_NONE);
+ } else {
+ EXPECT_EQ(status.exceptionCode(), Status::EX_UNSUPPORTED_OPERATION);
+ }
+}
+
+TEST_P(VibratorAidl, GetQFactor) {
+ float qFactor;
+ Status status = vibrator->getQFactor(&qFactor);
+ if (capabilities & IVibrator::CAP_GET_Q_FACTOR) {
+ ASSERT_NE(qFactor, 0);
+ EXPECT_EQ(status.exceptionCode(), Status::EX_NONE);
+ } else {
+ EXPECT_EQ(status.exceptionCode(), Status::EX_UNSUPPORTED_OPERATION);
+ }
+}
+
std::vector<std::tuple<int32_t, int32_t>> GenerateVibratorMapping() {
std::vector<std::tuple<int32_t, int32_t>> tuples;
auto managerAidlNames = android::getAidlHalInstanceNames(IVibratorManager::descriptor);
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 5613357..cd0edbe 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..07f7f47 100644
--- a/wifi/1.5/vts/functional/wifi_chip_hidl_test.cpp
+++ b/wifi/1.5/vts/functional/wifi_chip_hidl_test.cpp
@@ -147,6 +147,7 @@
* setCoexUnsafeChannels
*/
TEST_P(WifiChipHidlTest, setCoexUnsafeChannels) {
+ configureChipForIfaceType(IfaceType::STA, true);
// Test with empty vector of CoexUnsafeChannels
std::vector<IWifiChip::CoexUnsafeChannel> vec;
const auto& statusEmpty =
@@ -195,10 +196,12 @@
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);