Refactor NNAPI VTS to remove unreasonable dependence between versions

To make it easier to create the next version of NNAPI, this change
removes the following nonsensical dependence:
- NNAPI 1.0 VTS depends on NNAPI 1.1 and 1.2
- NNAPI 1.1 VTS depends on NNAPI 1.2

In particular, I made the following changes:
- split GeneratedTestHarness.cpp into three separate implementations,
- created a restricted version of Callbacks.h for 1.0 and 1.1,
- removed the dependency on frameworks/ml/nn/HalInterfaces.h,
- refactored Android.bp files for more autonomy between 1.0, 1.1, and 1.2,
- consolidated some common code into Utils.h,
- created structure for sharing code between VTS versions (VtsHalNeuralNetworksV1_0_utils).

Bug: 74827824
Bug: 124462414
Test: VtsHalNeuralnetworksV1_0TargetTest
Test: VtsHalNeuralnetworksV1_1TargetTest
Test: VtsHalNeuralnetworksV1_1CompatV1_0TargetTest
Test: VtsHalNeuralnetworksV1_2TargetTest
Test: VtsHalNeuralnetworksV1_2CompatV1_0TargetTest
Test: VtsHalNeuralnetworksV1_2CompatV1_1TargetTest
Change-Id: I4243d0b5e574255cef1070850f4d0a284f65f54e
Merged-In: I4243d0b5e574255cef1070850f4d0a284f65f54e
(cherry picked from commit 1d6b4659972010b9999dc77fbe65892b8b69d6da)
diff --git a/neuralnetworks/1.1/vts/functional/Android.bp b/neuralnetworks/1.1/vts/functional/Android.bp
index 4fbeac9..ee90ec6 100644
--- a/neuralnetworks/1.1/vts/functional/Android.bp
+++ b/neuralnetworks/1.1/vts/functional/Android.bp
@@ -14,10 +14,41 @@
 // limitations under the License.
 //
 
+cc_defaults {
+    name: "VtsHalNeuralNetworksV1_1TargetTestDefaults",
+    defaults: ["VtsHalTargetTestDefaults"],
+    srcs: [
+        "ValidateModel.cpp",
+        "ValidateRequest.cpp",
+        "VtsHalNeuralnetworks.cpp",
+        "GeneratedTestHarness.cpp",
+    ],
+    shared_libs: [
+        "libfmq",
+        "libnativewindow",
+    ],
+    static_libs: [
+        "android.hardware.neuralnetworks@1.0",
+        "android.hardware.neuralnetworks@1.1",
+        "android.hidl.allocator@1.0",
+        "android.hidl.memory@1.0",
+        "libgmock",
+        "libhidlmemory",
+        "libneuralnetworks_utils",
+        "VtsHalNeuralNetworksV1_0_utils",
+    ],
+    header_libs: [
+        "libneuralnetworks_headers",
+        "libneuralnetworks_generated_test_harness_headers",
+        "libneuralnetworks_generated_tests",
+    ],
+    test_suites: ["general-tests"],
+}
+
 // Tests for V1_0 models using the V1_1 HAL.
 cc_test {
     name: "VtsHalNeuralnetworksV1_1CompatV1_0TargetTest",
-    defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
+    defaults: ["VtsHalNeuralNetworksV1_1TargetTestDefaults"],
     srcs: [
         "GeneratedTestsV1_0.cpp",
     ],
@@ -26,19 +57,19 @@
 // Tests for V1_1 models.
 cc_test {
     name: "VtsHalNeuralnetworksV1_1TargetTest",
-    defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
+    defaults: ["VtsHalNeuralNetworksV1_1TargetTestDefaults"],
     srcs: [
         "BasicTests.cpp",
-        "GeneratedTests.cpp",
+        "GeneratedTestsV1_1.cpp",
     ],
 }
 
 cc_test {
     name: "PresubmitHalNeuralnetworksV1_1TargetTest",
-    defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
+    defaults: ["VtsHalNeuralNetworksV1_1TargetTestDefaults"],
     srcs: [
         "BasicTests.cpp",
-        "GeneratedTests.cpp",
+        "GeneratedTestsV1_1.cpp",
     ],
     cflags: [
         "-DPRESUBMIT_NOT_VTS",
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp
new file mode 100644
index 0000000..d9f64fd
--- /dev/null
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp
@@ -0,0 +1,232 @@
+/*
+ * Copyright (C) 2017 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT 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 <android-base/logging.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/IDevice.h>
+#include <android/hidl/allocator/1.0/IAllocator.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <hidlmemory/mapping.h>
+
+#include <iostream>
+
+#include "1.0/Callbacks.h"
+#include "1.0/Utils.h"
+#include "MemoryUtils.h"
+#include "TestHarness.h"
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace generated_tests {
+
+using ::android::hardware::neuralnetworks::V1_0::ErrorStatus;
+using ::android::hardware::neuralnetworks::V1_0::IPreparedModel;
+using ::android::hardware::neuralnetworks::V1_0::Request;
+using ::android::hardware::neuralnetworks::V1_0::RequestArgument;
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
+using ::android::hardware::neuralnetworks::V1_1::ExecutionPreference;
+using ::android::hardware::neuralnetworks::V1_1::IDevice;
+using ::android::hardware::neuralnetworks::V1_1::Model;
+using ::android::hidl::memory::V1_0::IMemory;
+using ::test_helper::compare;
+using ::test_helper::filter;
+using ::test_helper::for_all;
+using ::test_helper::MixedTyped;
+using ::test_helper::MixedTypedExample;
+using ::test_helper::resize_accordingly;
+
+// Top level driver for models and examples generated by test_generator.py
+// Test driver for those generated from ml/nn/runtime/test/spec
+void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
+                           const std::vector<MixedTypedExample>& examples,
+                           bool hasRelaxedFloat32Model, float fpAtol, float fpRtol) {
+    const uint32_t INPUT = 0;
+    const uint32_t OUTPUT = 1;
+
+    int example_no = 1;
+    for (auto& example : examples) {
+        SCOPED_TRACE(example_no++);
+        const MixedTyped& inputs = example.operands.first;
+        const MixedTyped& golden = example.operands.second;
+
+        const bool hasFloat16Inputs = !inputs.float16Operands.empty();
+        if (hasRelaxedFloat32Model || hasFloat16Inputs) {
+            // TODO: Adjust the error limit based on testing.
+            // If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
+            fpAtol = 5.0f * 0.0009765625f;
+            // Set the relative tolerance to be 5ULP of the corresponding FP precision.
+            fpRtol = 5.0f * 0.0009765625f;
+        }
+
+        std::vector<RequestArgument> inputs_info, outputs_info;
+        uint32_t inputSize = 0, outputSize = 0;
+        // This function only partially specifies the metadata (vector of RequestArguments).
+        // The contents are copied over below.
+        for_all(inputs, [&inputs_info, &inputSize](int index, auto, auto s) {
+            if (inputs_info.size() <= static_cast<size_t>(index)) inputs_info.resize(index + 1);
+            RequestArgument arg = {
+                    .location = {.poolIndex = INPUT,
+                                 .offset = 0,
+                                 .length = static_cast<uint32_t>(s)},
+                    .dimensions = {},
+            };
+            RequestArgument arg_empty = {
+                    .hasNoValue = true,
+            };
+            inputs_info[index] = s ? arg : arg_empty;
+            inputSize += s;
+        });
+        // Compute offset for inputs 1 and so on
+        {
+            size_t offset = 0;
+            for (auto& i : inputs_info) {
+                if (!i.hasNoValue) i.location.offset = offset;
+                offset += i.location.length;
+            }
+        }
+
+        MixedTyped test;  // holding test results
+
+        // Go through all outputs, initialize RequestArgument descriptors
+        resize_accordingly(golden, test);
+        for_all(golden, [&outputs_info, &outputSize](int index, auto, auto s) {
+            if (outputs_info.size() <= static_cast<size_t>(index)) outputs_info.resize(index + 1);
+            RequestArgument arg = {
+                    .location = {.poolIndex = OUTPUT,
+                                 .offset = 0,
+                                 .length = static_cast<uint32_t>(s)},
+                    .dimensions = {},
+            };
+            outputs_info[index] = arg;
+            outputSize += s;
+        });
+        // Compute offset for outputs 1 and so on
+        {
+            size_t offset = 0;
+            for (auto& i : outputs_info) {
+                i.location.offset = offset;
+                offset += i.location.length;
+            }
+        }
+        std::vector<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
+                                          nn::allocateSharedMemory(outputSize)};
+        ASSERT_NE(0ull, pools[INPUT].size());
+        ASSERT_NE(0ull, pools[OUTPUT].size());
+
+        // load data
+        sp<IMemory> inputMemory = mapMemory(pools[INPUT]);
+        sp<IMemory> outputMemory = mapMemory(pools[OUTPUT]);
+        ASSERT_NE(nullptr, inputMemory.get());
+        ASSERT_NE(nullptr, outputMemory.get());
+        char* inputPtr = reinterpret_cast<char*>(static_cast<void*>(inputMemory->getPointer()));
+        char* outputPtr = reinterpret_cast<char*>(static_cast<void*>(outputMemory->getPointer()));
+        ASSERT_NE(nullptr, inputPtr);
+        ASSERT_NE(nullptr, outputPtr);
+        inputMemory->update();
+        outputMemory->update();
+
+        // Go through all inputs, copy the values
+        for_all(inputs, [&inputs_info, inputPtr](int index, auto p, auto s) {
+            char* begin = (char*)p;
+            char* end = begin + s;
+            // TODO: handle more than one input
+            std::copy(begin, end, inputPtr + inputs_info[index].location.offset);
+        });
+
+        inputMemory->commit();
+        outputMemory->commit();
+
+        const Request request = {.inputs = inputs_info, .outputs = outputs_info, .pools = pools};
+
+        // launch execution
+        sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+        ASSERT_NE(nullptr, executionCallback.get());
+        Return<ErrorStatus> executionLaunchStatus =
+                preparedModel->execute(request, executionCallback);
+        ASSERT_TRUE(executionLaunchStatus.isOk());
+        EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
+
+        // retrieve execution status
+        executionCallback->wait();
+        ASSERT_EQ(ErrorStatus::NONE, executionCallback->getStatus());
+
+        // validate results
+        outputMemory->read();
+        copy_back(&test, outputs_info, outputPtr);
+        outputMemory->commit();
+        // Filter out don't cares
+        MixedTyped filtered_golden = filter(golden, is_ignored);
+        MixedTyped filtered_test = filter(test, is_ignored);
+
+        // We want "close-enough" results for float
+        compare(filtered_golden, filtered_test, fpAtol, fpRtol);
+    }
+}
+
+void Execute(const sp<IDevice>& device, std::function<Model(void)> create_model,
+             std::function<bool(int)> is_ignored, const std::vector<MixedTypedExample>& examples) {
+    Model model = create_model();
+
+    // see if service can handle model
+    bool fullySupportsModel = false;
+    Return<void> supportedCall = device->getSupportedOperations_1_1(
+            model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
+                ASSERT_EQ(ErrorStatus::NONE, status);
+                ASSERT_NE(0ul, supported.size());
+                fullySupportsModel = std::all_of(supported.begin(), supported.end(),
+                                                 [](bool valid) { return valid; });
+            });
+    ASSERT_TRUE(supportedCall.isOk());
+
+    // launch prepare model
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(
+            model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+    ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+    // retrieve prepared model
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+
+    // early termination if vendor service cannot fully prepare model
+    if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
+        ASSERT_EQ(nullptr, preparedModel.get());
+        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();
+    }
+    EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    ASSERT_NE(nullptr, preparedModel.get());
+
+    EvaluatePreparedModel(preparedModel, is_ignored, examples,
+                          model.relaxComputationFloat32toFloat16, 1e-5f, 1e-5f);
+}
+
+}  // namespace generated_tests
+}  // namespace neuralnetworks
+}  // namespace hardware
+}  // namespace android
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h
new file mode 100644
index 0000000..ab71b2b
--- /dev/null
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h
@@ -0,0 +1,40 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_V1_1_GENERATED_TEST_HARNESS_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_V1_1_GENERATED_TEST_HARNESS_H
+
+#include <android/hardware/neuralnetworks/1.1/IDevice.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <functional>
+#include <vector>
+#include "TestHarness.h"
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace generated_tests {
+
+void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> create_model,
+             std::function<bool(int)> is_ignored,
+             const std::vector<::test_helper::MixedTypedExample>& examples);
+
+}  // namespace generated_tests
+}  // namespace neuralnetworks
+}  // namespace hardware
+}  // namespace android
+
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_V1_1_GENERATED_TEST_HARNESS_H
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_0.cpp b/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_0.cpp
index e67ef8e..10cf5a9 100644
--- a/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_0.cpp
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_0.cpp
@@ -16,17 +16,16 @@
 
 #define LOG_TAG "neuralnetworks_hidl_hal_test"
 
-#include "VtsHalNeuralnetworks.h"
-
-#include "Callbacks.h"
-#include "GeneratedTestHarness.h"
-#include "TestHarness.h"
-#include "Utils.h"
-
 #include <android-base/logging.h>
 #include <android/hidl/memory/1.0/IMemory.h>
 #include <hidlmemory/mapping.h>
 
+#include "1.0/Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "MemoryUtils.h"
+#include "TestHarness.h"
+#include "VtsHalNeuralnetworks.h"
+
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
@@ -34,8 +33,10 @@
 namespace vts {
 namespace functional {
 
-using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+using ::android::hardware::neuralnetworks::V1_0::OperandLifeTime;
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
+using ::android::hidl::memory::V1_0::IMemory;
 using ::android::nn::allocateSharedMemory;
 using ::test_helper::MixedTypedExample;
 
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTests.cpp b/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_1.cpp
similarity index 83%
rename from neuralnetworks/1.1/vts/functional/GeneratedTests.cpp
rename to neuralnetworks/1.1/vts/functional/GeneratedTestsV1_1.cpp
index 4db1276..079c18c 100644
--- a/neuralnetworks/1.1/vts/functional/GeneratedTests.cpp
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_1.cpp
@@ -16,17 +16,16 @@
 
 #define LOG_TAG "neuralnetworks_hidl_hal_test"
 
-#include "VtsHalNeuralnetworks.h"
-
-#include "Callbacks.h"
-#include "GeneratedTestHarness.h"
-#include "TestHarness.h"
-#include "Utils.h"
-
 #include <android-base/logging.h>
 #include <android/hidl/memory/1.0/IMemory.h>
 #include <hidlmemory/mapping.h>
 
+#include "1.0/Callbacks.h"
+#include "GeneratedTestHarness.h"
+#include "MemoryUtils.h"
+#include "TestHarness.h"
+#include "VtsHalNeuralnetworks.h"
+
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
@@ -34,8 +33,10 @@
 namespace vts {
 namespace functional {
 
-using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+using ::android::hardware::neuralnetworks::V1_0::OperandLifeTime;
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
+using ::android::hidl::memory::V1_0::IMemory;
 using ::android::nn::allocateSharedMemory;
 using ::test_helper::MixedTypedExample;
 
diff --git a/neuralnetworks/1.1/vts/functional/ValidateModel.cpp b/neuralnetworks/1.1/vts/functional/ValidateModel.cpp
index b35a901..fb80d13 100644
--- a/neuralnetworks/1.1/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.1/vts/functional/ValidateModel.cpp
@@ -16,25 +16,22 @@
 
 #define LOG_TAG "neuralnetworks_hidl_hal_test"
 
+#include "1.0/Callbacks.h"
+#include "1.0/Utils.h"
 #include "VtsHalNeuralnetworks.h"
 
-#include "Callbacks.h"
-
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
 namespace V1_1 {
-
-using V1_0::IPreparedModel;
-using V1_0::Operand;
-using V1_0::OperandLifeTime;
-using V1_0::OperandType;
-
 namespace vts {
 namespace functional {
 
-using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+using ::android::hardware::neuralnetworks::V1_0::IPreparedModel;
+using ::android::hardware::neuralnetworks::V1_0::Operand;
+using ::android::hardware::neuralnetworks::V1_0::OperandLifeTime;
+using ::android::hardware::neuralnetworks::V1_0::OperandType;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
 
 ///////////////////////// UTILITY FUNCTIONS /////////////////////////
 
@@ -42,10 +39,10 @@
                                            const V1_1::Model& model) {
     SCOPED_TRACE(message + " [getSupportedOperations_1_1]");
 
-    Return<void> ret =
-        device->getSupportedOperations_1_1(model, [&](ErrorStatus status, const hidl_vec<bool>&) {
-            EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, status);
-        });
+    Return<void> ret = device->getSupportedOperations_1_1(
+            model, [&](ErrorStatus status, const hidl_vec<bool>&) {
+                EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, status);
+            });
     EXPECT_TRUE(ret.isOk());
 }
 
@@ -56,7 +53,7 @@
     sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
     ASSERT_NE(nullptr, preparedModelCallback.get());
     Return<ErrorStatus> prepareLaunchStatus =
-        device->prepareModel_1_1(model, preference, preparedModelCallback);
+            device->prepareModel_1_1(model, preference, preparedModelCallback);
     ASSERT_TRUE(prepareLaunchStatus.isOk());
     ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(prepareLaunchStatus));
 
@@ -87,36 +84,16 @@
     validatePrepareModel(device, message, model, preference);
 }
 
-// Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation,
-// so this is efficiently accomplished by moving the element to the end and
-// resizing the hidl_vec to one less.
-template <typename Type>
-static void hidl_vec_removeAt(hidl_vec<Type>* vec, uint32_t index) {
-    if (vec) {
-        std::rotate(vec->begin() + index, vec->begin() + index + 1, vec->end());
-        vec->resize(vec->size() - 1);
-    }
-}
-
-template <typename Type>
-static uint32_t hidl_vec_push_back(hidl_vec<Type>* vec, const Type& value) {
-    // assume vec is valid
-    const uint32_t index = vec->size();
-    vec->resize(index + 1);
-    (*vec)[index] = value;
-    return index;
-}
-
 static uint32_t addOperand(Model* model) {
     return hidl_vec_push_back(&model->operands,
                               {
-                                  .type = OperandType::INT32,
-                                  .dimensions = {},
-                                  .numberOfConsumers = 0,
-                                  .scale = 0.0f,
-                                  .zeroPoint = 0,
-                                  .lifetime = OperandLifeTime::MODEL_INPUT,
-                                  .location = {.poolIndex = 0, .offset = 0, .length = 0},
+                                      .type = OperandType::INT32,
+                                      .dimensions = {},
+                                      .numberOfConsumers = 0,
+                                      .scale = 0.0f,
+                                      .zeroPoint = 0,
+                                      .lifetime = OperandLifeTime::MODEL_INPUT,
+                                      .location = {.poolIndex = 0, .offset = 0, .length = 0},
                               });
 }
 
@@ -130,10 +107,10 @@
 ///////////////////////// VALIDATE MODEL OPERAND TYPE /////////////////////////
 
 static const int32_t invalidOperandTypes[] = {
-    static_cast<int32_t>(OperandType::FLOAT32) - 1,              // lower bound fundamental
-    static_cast<int32_t>(OperandType::TENSOR_QUANT8_ASYMM) + 1,  // upper bound fundamental
-    static_cast<int32_t>(OperandType::OEM) - 1,                  // lower bound OEM
-    static_cast<int32_t>(OperandType::TENSOR_OEM_BYTE) + 1,      // upper bound OEM
+        static_cast<int32_t>(OperandType::FLOAT32) - 1,              // lower bound fundamental
+        static_cast<int32_t>(OperandType::TENSOR_QUANT8_ASYMM) + 1,  // upper bound fundamental
+        static_cast<int32_t>(OperandType::OEM) - 1,                  // lower bound OEM
+        static_cast<int32_t>(OperandType::TENSOR_OEM_BYTE) + 1,      // upper bound OEM
 };
 
 static void mutateOperandTypeTest(const sp<IDevice>& device, const V1_1::Model& model) {
@@ -226,7 +203,7 @@
 static void mutateOperandZeroPointTest(const sp<IDevice>& device, const V1_1::Model& model) {
     for (size_t operand = 0; operand < model.operands.size(); ++operand) {
         const std::vector<int32_t> invalidZeroPoints =
-            getInvalidZeroPoints(model.operands[operand].type);
+                getInvalidZeroPoints(model.operands[operand].type);
         for (int32_t invalidZeroPoint : invalidZeroPoints) {
             const std::string message = "mutateOperandZeroPointTest: operand " +
                                         std::to_string(operand) + " has zero point of " +
@@ -258,18 +235,18 @@
             break;
         case OperandType::TENSOR_FLOAT32:
             newOperand.dimensions =
-                operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
+                    operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
             newOperand.scale = 0.0f;
             newOperand.zeroPoint = 0;
             break;
         case OperandType::TENSOR_INT32:
             newOperand.dimensions =
-                operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
+                    operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
             newOperand.zeroPoint = 0;
             break;
         case OperandType::TENSOR_QUANT8_ASYMM:
             newOperand.dimensions =
-                operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
+                    operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
             newOperand.scale = operand->scale != 0.0f ? operand->scale : 1.0f;
             break;
         case OperandType::OEM:
@@ -319,10 +296,10 @@
 ///////////////////////// VALIDATE MODEL OPERATION TYPE /////////////////////////
 
 static const int32_t invalidOperationTypes[] = {
-    static_cast<int32_t>(OperationType::ADD) - 1,            // lower bound fundamental
-    static_cast<int32_t>(OperationType::TRANSPOSE) + 1,      // upper bound fundamental
-    static_cast<int32_t>(OperationType::OEM_OPERATION) - 1,  // lower bound OEM
-    static_cast<int32_t>(OperationType::OEM_OPERATION) + 1,  // upper bound OEM
+        static_cast<int32_t>(OperationType::ADD) - 1,            // lower bound fundamental
+        static_cast<int32_t>(OperationType::TRANSPOSE) + 1,      // upper bound fundamental
+        static_cast<int32_t>(OperationType::OEM_OPERATION) - 1,  // lower bound OEM
+        static_cast<int32_t>(OperationType::OEM_OPERATION) + 1,  // upper bound OEM
 };
 
 static void mutateOperationTypeTest(const sp<IDevice>& device, const V1_1::Model& model) {
@@ -333,7 +310,7 @@
                                         std::to_string(invalidOperationType);
             validate(device, message, model, [operation, invalidOperationType](Model* model) {
                 model->operations[operation].type =
-                    static_cast<OperationType>(invalidOperationType);
+                        static_cast<OperationType>(invalidOperationType);
             });
         }
     }
@@ -486,7 +463,7 @@
 static void addOperationOutputTest(const sp<IDevice>& device, const V1_1::Model& model) {
     for (size_t operation = 0; operation < model.operations.size(); ++operation) {
         const std::string message =
-            "addOperationOutputTest: operation " + std::to_string(operation);
+                "addOperationOutputTest: operation " + std::to_string(operation);
         validate(device, message, model, [operation](Model* model) {
             uint32_t index = addOperand(model, OperandLifeTime::MODEL_OUTPUT);
             hidl_vec_push_back(&model->operations[operation].outputs, index);
@@ -498,14 +475,14 @@
 ///////////////////////// 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_cast<int32_t>(ExecutionPreference::LOW_POWER) - 1,        // lower bound
+        static_cast<int32_t>(ExecutionPreference::SUSTAINED_SPEED) + 1,  // upper bound
 };
 
 static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const V1_1::Model& model) {
     for (int32_t preference : invalidExecutionPreferences) {
         const std::string message =
-            "mutateExecutionPreferenceTest: preference " + std::to_string(preference);
+                "mutateExecutionPreferenceTest: preference " + std::to_string(preference);
         validate(device, message, model, [](Model*) {},
                  static_cast<ExecutionPreference>(preference));
     }
diff --git a/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp b/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp
index f4adbab..c549728 100644
--- a/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/1.1/vts/functional/ValidateRequest.cpp
@@ -16,16 +16,16 @@
 
 #define LOG_TAG "neuralnetworks_hidl_hal_test"
 
-#include "VtsHalNeuralnetworks.h"
-
-#include "Callbacks.h"
-#include "TestHarness.h"
-#include "Utils.h"
-
 #include <android-base/logging.h>
 #include <android/hidl/memory/1.0/IMemory.h>
 #include <hidlmemory/mapping.h>
 
+#include "1.0/Callbacks.h"
+#include "1.0/Utils.h"
+#include "MemoryUtils.h"
+#include "TestHarness.h"
+#include "VtsHalNeuralnetworks.h"
+
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
@@ -33,11 +33,15 @@
 namespace vts {
 namespace functional {
 
-using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::ErrorStatus;
+using ::android::hardware::neuralnetworks::V1_0::Request;
+using ::android::hardware::neuralnetworks::V1_0::RequestArgument;
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_1::IPreparedModel;
 using ::android::hidl::memory::V1_0::IMemory;
-using test_helper::for_all;
-using test_helper::MixedTyped;
-using test_helper::MixedTypedExample;
+using ::test_helper::for_all;
+using ::test_helper::MixedTyped;
+using ::test_helper::MixedTypedExample;
 
 ///////////////////////// UTILITY FUNCTIONS /////////////////////////
 
@@ -61,26 +65,6 @@
     ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionReturnStatus);
 }
 
-// Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation,
-// so this is efficiently accomplished by moving the element to the end and
-// resizing the hidl_vec to one less.
-template <typename Type>
-static void hidl_vec_removeAt(hidl_vec<Type>* vec, uint32_t index) {
-    if (vec) {
-        std::rotate(vec->begin() + index, vec->begin() + index + 1, vec->end());
-        vec->resize(vec->size() - 1);
-    }
-}
-
-template <typename Type>
-static uint32_t hidl_vec_push_back(hidl_vec<Type>* vec, const Type& value) {
-    // assume vec is valid
-    const uint32_t index = vec->size();
-    vec->resize(index + 1);
-    (*vec)[index] = value;
-    return index;
-}
-
 ///////////////////////// REMOVE INPUT ////////////////////////////////////
 
 static void removeInputTest(const sp<IPreparedModel>& preparedModel, const Request& request) {
@@ -121,11 +105,13 @@
         for_all(inputs, [&inputs_info, &inputSize](int index, auto, auto s) {
             if (inputs_info.size() <= static_cast<size_t>(index)) inputs_info.resize(index + 1);
             RequestArgument arg = {
-                .location = {.poolIndex = INPUT, .offset = 0, .length = static_cast<uint32_t>(s)},
-                .dimensions = {},
+                    .location = {.poolIndex = INPUT,
+                                 .offset = 0,
+                                 .length = static_cast<uint32_t>(s)},
+                    .dimensions = {},
             };
             RequestArgument arg_empty = {
-                .hasNoValue = true,
+                    .hasNoValue = true,
             };
             inputs_info[index] = s ? arg : arg_empty;
             inputSize += s;
@@ -143,8 +129,10 @@
         for_all(outputs, [&outputs_info, &outputSize](int index, auto, auto s) {
             if (outputs_info.size() <= static_cast<size_t>(index)) outputs_info.resize(index + 1);
             RequestArgument arg = {
-                .location = {.poolIndex = OUTPUT, .offset = 0, .length = static_cast<uint32_t>(s)},
-                .dimensions = {},
+                    .location = {.poolIndex = OUTPUT,
+                                 .offset = 0,
+                                 .length = static_cast<uint32_t>(s)},
+                    .dimensions = {},
             };
             outputs_info[index] = arg;
             outputSize += s;
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
index 08069f2..12bdd3f 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
@@ -20,7 +20,7 @@
 
 #include <android-base/logging.h>
 
-#include "Callbacks.h"
+#include "1.0/Callbacks.h"
 
 namespace android {
 namespace hardware {
@@ -29,7 +29,7 @@
 namespace vts {
 namespace functional {
 
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
 
 static void createPreparedModel(const sp<IDevice>& device, const V1_1::Model& model,
                                 sp<IPreparedModel>* preparedModel) {
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
index f3f587b..3156784 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
@@ -14,8 +14,8 @@
  * limitations under the License.
  */
 
-#ifndef VTS_HAL_NEURALNETWORKS_V1_1_H
-#define VTS_HAL_NEURALNETWORKS_V1_1_H
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_V1_1_VTS_HAL_NEURALNETWORKS_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_V1_1_VTS_HAL_NEURALNETWORKS_H
 
 #include <android/hardware/neuralnetworks/1.0/types.h>
 #include <android/hardware/neuralnetworks/1.1/IDevice.h>
@@ -98,4 +98,4 @@
 
 }  // namespace android::hardware::neuralnetworks::V1_0
 
-#endif  // VTS_HAL_NEURALNETWORKS_V1_1_H
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_V1_1_VTS_HAL_NEURALNETWORKS_H