Merge "Refactor NN API VTS tests and add v1.1 tests" (e31495a2) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.0/vts/functional/Android.bp

+31 −4

Original line number	Diff line number	Diff line
		@@ -14,22 +14,49 @@
		// limitations under the License.
		//

		cc_test {
		name: "VtsHalNeuralnetworksV1_0TargetTest",
		cc_library_static {
		name: "VtsHalNeuralnetworksTest_utils",
		srcs: [
		"Callbacks.cpp",
		"GeneratedTestHarness.cpp",
		"Models.cpp",
		"VtsHalNeuralnetworksV1_0TargetTest.cpp",
		"GeneratedTestHarness.cpp",
		],
		defaults: ["VtsHalTargetTestDefaults"],
		export_include_dirs: ["."],
		static_libs: [
		"android.hardware.neuralnetworks@1.0",
		"android.hardware.neuralnetworks@1.1",
		"android.hidl.allocator@1.0",
		"android.hidl.memory@1.0",
		"libhidlmemory",
		"libneuralnetworks_utils",
		],
		header_libs: [
		"libneuralnetworks_headers",
		"libneuralnetworks_generated_test_harness_headers",
		"libneuralnetworks_generated_tests",
		],
		}

		cc_test {
		name: "VtsHalNeuralnetworksV1_0TargetTest",
		srcs: [
		"VtsHalNeuralnetworksV1_0.cpp",
		"VtsHalNeuralnetworksV1_0BasicTest.cpp",
		"VtsHalNeuralnetworksV1_0GeneratedTest.cpp",
		],
		defaults: ["VtsHalTargetTestDefaults"],
		static_libs: [
		"android.hardware.neuralnetworks@1.0",
		"android.hardware.neuralnetworks@1.1",
		"android.hidl.allocator@1.0",
		"android.hidl.memory@1.0",
		"libhidlmemory",
		"libneuralnetworks_utils",
		"VtsHalNeuralnetworksTest_utils",
		],
		header_libs: [
		"libneuralnetworks_headers",
		"libneuralnetworks_generated_test_harness_headers",
		"libneuralnetworks_generated_tests",
		],

neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp

+110 −57

Original line number	Diff line number	Diff line
		@@ -16,9 +16,15 @@

		#include "Callbacks.h"
		#include "TestHarness.h"
		#include "VtsHalNeuralnetworksV1_0TargetTest.h"
		#include "Utils.h"

		#include <android-base/logging.h>
		#include <android/hardware/neuralnetworks/1.0/IDevice.h>
		#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
		#include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
		#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
		#include <android/hardware/neuralnetworks/1.0/types.h>
		#include <android/hidl/allocator/1.0/IAllocator.h>
		#include <android/hidl/memory/1.0/IMemory.h>
		#include <hidlmemory/mapping.h>
		#include <iostream>
		@@ -26,11 +32,6 @@
		namespace android {
		namespace hardware {
		namespace neuralnetworks {
		namespace V1_0 {
		namespace vts {
		namespace functional {
		// allocator helper
		hidl_memory allocateSharedMemory(int64_t size, const std::string& type = "ashmem");

		namespace generated_tests {
		using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
		@@ -64,54 +65,10 @@ void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* sr

		// Top level driver for models and examples generated by test_generator.py
		// Test driver for those generated from ml/nn/runtime/test/spec
		void Execute(const sp<IDevice>& device, std::function<Model(void)> create_model,
		std::function<bool(int)> is_ignored,
		void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
		const std::vector<MixedTypedExampleType>& examples) {
		const uint32_t INPUT = 0;
		const uint32_t OUTPUT = 1;
		Model model = create_model();

		// see if service can handle model
		ErrorStatus supportedStatus;
		bool fullySupportsModel = false;
		Return<void> supportedCall = device->getSupportedOperations(
		model, [&](ErrorStatus status, const hidl_vec<bool>& supported) {
		supportedStatus = status;
		ASSERT_NE(0ul, supported.size());
		fullySupportsModel =
		std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
		});
		ASSERT_TRUE(supportedCall.isOk());
		ASSERT_EQ(ErrorStatus::NONE, supportedStatus);

		// launch prepare model
		sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
		ASSERT_NE(nullptr, preparedModelCallback.get());
		Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
		ASSERT_TRUE(prepareLaunchStatus.isOk());

		// retrieve prepared model
		preparedModelCallback->wait();
		ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
		sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
		if (fullySupportsModel) {
		EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
		} else {
		EXPECT_TRUE(prepareReturnStatus == ErrorStatus::NONE \|\|
		prepareReturnStatus == ErrorStatus::GENERAL_FAILURE);
		}

		// early termination if vendor service cannot fully prepare model
		if (!fullySupportsModel && prepareReturnStatus == ErrorStatus::GENERAL_FAILURE) {
		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;
		return;
		}
		ASSERT_NE(nullptr, preparedModel.get());

		int example_no = 1;
		for (auto& example : examples) {
		@@ -167,8 +124,8 @@ void Execute(const sp<IDevice>& device, std::function<Model(void)> create_model,
		offset += i.location.length;
		}
		}
		std::vector<hidl_memory> pools = {allocateSharedMemory(inputSize),
		allocateSharedMemory(outputSize)};
		std::vector<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
		nn::allocateSharedMemory(outputSize)};
		ASSERT_NE(0ull, pools[INPUT].size());
		ASSERT_NE(0ull, pools[OUTPUT].size());

		@@ -221,11 +178,107 @@ void Execute(const sp<IDevice>& device, std::function<Model(void)> create_model,
		}
		}

		void Execute(sp<V1_0::IDevice>& device, std::function<V1_0::Model(void)> create_model,
		std::function<bool(int)> is_ignored,
		const std::vector<MixedTypedExampleType>& examples) {
		V1_0::Model model = create_model();

		// see if service can handle model
		bool fullySupportsModel = false;
		ErrorStatus supportedStatus;
		sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
		ASSERT_NE(nullptr, preparedModelCallback.get());

		Return<void> supportedCall = device->getSupportedOperations(
		model, [&](ErrorStatus status, const hidl_vec<bool>& supported) {
		supportedStatus = status;
		ASSERT_NE(0ul, supported.size());
		fullySupportsModel =
		std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
		});
		ASSERT_TRUE(supportedCall.isOk());
		ASSERT_EQ(ErrorStatus::NONE, supportedStatus);
		Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
		ASSERT_TRUE(prepareLaunchStatus.isOk());

		// retrieve prepared model
		preparedModelCallback->wait();
		ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
		sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
		if (fullySupportsModel) {
		EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
		} else {
		EXPECT_TRUE(prepareReturnStatus == ErrorStatus::NONE \|\|
		prepareReturnStatus == ErrorStatus::GENERAL_FAILURE);
		}

		// early termination if vendor service cannot fully prepare model
		if (!fullySupportsModel && prepareReturnStatus == ErrorStatus::GENERAL_FAILURE) {
		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;
		return;
		}
		ASSERT_NE(nullptr, preparedModel.get());

		EvaluatePreparedModel(preparedModel, is_ignored, examples);
		}

		void Execute(sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> create_model,
		std::function<bool(int)> is_ignored,
		const std::vector<MixedTypedExampleType>& examples) {
		V1_1::Model model = create_model();

		// see if service can handle model
		bool fullySupportsModel = false;
		ErrorStatus supportedStatus;
		sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
		ASSERT_NE(nullptr, preparedModelCallback.get());

		Return<void> supportedCall = device->getSupportedOperations_1_1(
		model, [&](ErrorStatus status, const hidl_vec<bool>& supported) {
		supportedStatus = status;
		ASSERT_NE(0ul, supported.size());
		fullySupportsModel =
		std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
		});
		ASSERT_TRUE(supportedCall.isOk());
		ASSERT_EQ(ErrorStatus::NONE, supportedStatus);
		Return<ErrorStatus> prepareLaunchStatus =
		device->prepareModel_1_1(model, preparedModelCallback);
		ASSERT_TRUE(prepareLaunchStatus.isOk());

		// retrieve prepared model
		preparedModelCallback->wait();
		ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
		sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
		if (fullySupportsModel) {
		EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
		} else {
		EXPECT_TRUE(prepareReturnStatus == ErrorStatus::NONE \|\|
		prepareReturnStatus == ErrorStatus::GENERAL_FAILURE);
		}

		// early termination if vendor service cannot fully prepare model
		if (!fullySupportsModel && prepareReturnStatus == ErrorStatus::GENERAL_FAILURE) {
		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;
		return;
		}
		ASSERT_NE(nullptr, preparedModel.get());

		EvaluatePreparedModel(preparedModel, is_ignored, examples);
		}

		} // namespace generated_tests

		} // namespace functional
		} // namespace vts
		} // namespace V1_0
		} // namespace neuralnetworks
		} // namespace hardware
		} // namespace android

neuralnetworks/1.0/vts/functional/Models.cpp

+24 −29

Original line number	Diff line number	Diff line
		@@ -17,19 +17,22 @@
		#define LOG_TAG "neuralnetworks_hidl_hal_test"

		#include "Models.h"
		#include "Utils.h"

		#include <android-base/logging.h>
		#include <android/hidl/allocator/1.0/IAllocator.h>
		#include <android/hidl/memory/1.0/IMemory.h>
		#include <hidlmemory/mapping.h>
		#include <vector>

		using ::android::sp;

		namespace android {
		namespace hardware {
		namespace neuralnetworks {
		namespace V1_0 {
		namespace vts {
		namespace functional {

		// create a valid model
		Model createValidTestModel() {
		V1_1::Model createValidTestModel_1_1() {
		const std::vector<float> operand2Data = {5.0f, 6.0f, 7.0f, 8.0f};
		const uint32_t size = operand2Data.size() * sizeof(float);

		@@ -103,39 +106,34 @@ Model createValidTestModel() {
		}

		// create first invalid model
		Model createInvalidTestModel1() {
		Model model = createValidTestModel();
		V1_1::Model createInvalidTestModel1_1_1() {
		Model model = createValidTestModel_1_1();
		model.operations[0].type = static_cast<OperationType>(0xDEADBEEF); /* INVALID */
		return model;
		}

		// create second invalid model
		Model createInvalidTestModel2() {
		Model model = createValidTestModel();
		V1_1::Model createInvalidTestModel2_1_1() {
		Model model = createValidTestModel_1_1();
		const uint32_t operand1 = 0;
		const uint32_t operand5 = 4; // INVALID OPERAND
		model.inputIndexes = std::vector<uint32_t>({operand1, operand5 /* INVALID OPERAND */});
		return model;
		}

		// allocator helper
		hidl_memory allocateSharedMemory(int64_t size, const std::string& type = "ashmem") {
		hidl_memory memory;

		sp<IAllocator> allocator = IAllocator::getService(type);
		if (!allocator.get()) {
		return {};
		V1_0::Model createValidTestModel_1_0() {
		V1_1::Model model = createValidTestModel_1_1();
		return nn::convertToV1_0(model);
		}

		Return<void> ret = allocator->allocate(size, [&](bool success, const hidl_memory& mem) {
		ASSERT_TRUE(success);
		memory = mem;
		});
		if (!ret.isOk()) {
		return {};
		V1_0::Model createInvalidTestModel1_1_0() {
		V1_1::Model model = createInvalidTestModel1_1_1();
		return nn::convertToV1_0(model);
		}

		return memory;
		V1_0::Model createInvalidTestModel2_1_0() {
		V1_1::Model model = createInvalidTestModel2_1_1();
		return nn::convertToV1_0(model);
		}

		// create a valid request
		@@ -154,8 +152,8 @@ Request createValidTestRequest() {
		std::vector<RequestArgument> outputs = {{
		.location = {.poolIndex = OUTPUT, .offset = 0, .length = outputSize}, .dimensions = {},
		}};
		std::vector<hidl_memory> pools = {allocateSharedMemory(inputSize),
		allocateSharedMemory(outputSize)};
		std::vector<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
		nn::allocateSharedMemory(outputSize)};
		if (pools[INPUT].size() == 0 \|\| pools[OUTPUT].size() == 0) {
		return {};
		}
		@@ -199,9 +197,6 @@ Request createInvalidTestRequest2() {
		return request;
		}

		} // namespace functional
		} // namespace vts
		} // namespace V1_0
		} // namespace neuralnetworks
		} // namespace hardware
		} // namespace android

neuralnetworks/1.0/vts/functional/Models.h

+13 −14

Original line number	Diff line number	Diff line
		@@ -16,28 +16,27 @@

		#define LOG_TAG "neuralnetworks_hidl_hal_test"

		#include "VtsHalNeuralnetworksV1_0TargetTest.h"
		#include <android/hardware/neuralnetworks/1.1/types.h>

		namespace android {
		namespace hardware {
		namespace neuralnetworks {
		namespace V1_0 {
		namespace vts {
		namespace functional {

		// create the model
		Model createValidTestModel();
		Model createInvalidTestModel1();
		Model createInvalidTestModel2();
		// create V1_1 model
		V1_1::Model createValidTestModel_1_1();
		V1_1::Model createInvalidTestModel1_1_1();
		V1_1::Model createInvalidTestModel2_1_1();

		// create V1_0 model
		V1_0::Model createValidTestModel_1_0();
		V1_0::Model createInvalidTestModel1_1_0();
		V1_0::Model createInvalidTestModel2_1_0();

		// create the request
		Request createValidTestRequest();
		Request createInvalidTestRequest1();
		Request createInvalidTestRequest2();
		V1_0::Request createValidTestRequest();
		V1_0::Request createInvalidTestRequest1();
		V1_0::Request createInvalidTestRequest2();

		} // namespace functional
		} // namespace vts
		} // namespace V1_0
		} // namespace neuralnetworks
		} // namespace hardware
		} // namespace android

neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0.cpp

0 → 100644

+73 −0

Original line number	Diff line number	Diff line
		/*
		* Copyright (C) 2018 The Android Open Source Project
		*
		* Licensed under the Apache License, Version 2.0 (the "License");
		* you may not use this file except in compliance with the License.
		* You may obtain a copy of the License at
		*
		* http://www.apache.org/licenses/LICENSE-2.0
		*
		* Unless required by applicable law or agreed to in writing, software
		* distributed under the License is distributed on an "AS IS" BASIS,
		* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
		* See the License for the specific language governing permissions and
		* limitations under the License.
		*/

		#define LOG_TAG "neuralnetworks_hidl_hal_test"

		#include "VtsHalNeuralnetworksV1_0.h"
		#include "Utils.h"

		#include <android-base/logging.h>

		using ::android::hardware::hidl_memory;
		using ::android::hidl::allocator::V1_0::IAllocator;
		using ::android::hidl::memory::V1_0::IMemory;
		using ::android::sp;

		namespace android {
		namespace hardware {
		namespace neuralnetworks {
		namespace V1_0 {
		namespace vts {
		namespace functional {

		// allocator helper
		hidl_memory allocateSharedMemory(int64_t size) {
		return nn::allocateSharedMemory(size);
		}

		// A class for test environment setup
		NeuralnetworksHidlEnvironment::NeuralnetworksHidlEnvironment() {}

		NeuralnetworksHidlEnvironment::~NeuralnetworksHidlEnvironment() {}

		NeuralnetworksHidlEnvironment* NeuralnetworksHidlEnvironment::getInstance() {
		// This has to return a "new" object because it is freed inside
		// ::testing::AddGlobalTestEnvironment when the gtest is being torn down
		static NeuralnetworksHidlEnvironment* instance = new NeuralnetworksHidlEnvironment();
		return instance;
		}

		void NeuralnetworksHidlEnvironment::registerTestServices() {
		registerTestService<V1_0::IDevice>();
		}

		// The main test class for NEURALNETWORK HIDL HAL.
		NeuralnetworksHidlTest::~NeuralnetworksHidlTest() {}

		void NeuralnetworksHidlTest::SetUp() {
		device = ::testing::VtsHalHidlTargetTestBase::getService<V1_0::IDevice>(
		NeuralnetworksHidlEnvironment::getInstance());
		ASSERT_NE(nullptr, device.get());
		}

		void NeuralnetworksHidlTest::TearDown() {}

		} // namespace functional
		} // namespace vts
		} // namespace V1_0
		} // namespace neuralnetworks
		} // namespace hardware
		} // namespace android