Merge changes from topic "quant_coupling" (5c305e52) · Commits · e / os / android_hardware_interfaces

current.txt

+2 −2

Original line number	Diff line number	Diff line
		@@ -579,7 +579,7 @@ f1109cbb10297b7429a11fab42afa912710b303c9bf20bd5cdb8bd57b9c84186 android.hardwar
		9d8ee57c490ffeaa28f702eaea8d198cb510e4bbfb99e6cb5f63e73341057c7c android.hardware.neuralnetworks@1.1::types
		fb382e986c10b8fbb797a8546e8f9ea6d1107bfe6f3fb7e57f6bbbf1f807a906 android.hardware.neuralnetworks@1.2::IDevice
		40e71cd693de5b832325c5d8f081f2ff20a7ba2b89d401cee5b4b3eb0e241681 android.hardware.neuralnetworks@1.2::IPreparedModel
		71c0f7127335e5b74d1615d5e7f129831b43ffbae5318ad0924d7d8d8910a859 android.hardware.neuralnetworks@1.2::types
		72de91c3feba4b19c159cd1c413cbea596b78240caa43e31194e20e6f5b05c49 android.hardware.neuralnetworks@1.2::types
		a785a57447a81e9c130eef6904c3a5c256076c6a04588c40620ebd6fa2660d77 android.hardware.radio@1.2::types
		1a6e2bd289f22931c526b21916910f1d4c436b7acb9556e4243de4ce8e6cc2e4 android.hardware.soundtrigger@2.0::ISoundTriggerHwCallback
		fd65298e1e09e0e3c781ab18305920d757dbe55a3b459ce17814ec5cf6dfee99 android.hardware.wifi@1.0::IWifiP2pIface
		@@ -602,7 +602,7 @@ a3eddd9bbdc87e8c22764070037dd1154f1cf006e6fba93364c4f85d4c134a19 android.hardwar
		9e59fffceed0dd72a9799e04505db5f777bbbea1af0695ba4107ef6d967c6fda android.hardware.neuralnetworks@1.3::IDevice
		4a6c3b3556da951b4def21ba579a227c022980fe4465df6cdfbe20628fa75f5a android.hardware.neuralnetworks@1.3::IPreparedModel
		94e803236398bed1febb11cc21051bc42ec003700139b099d6c479e02a7ca3c3 android.hardware.neuralnetworks@1.3::IPreparedModelCallback
		c511b1427b1c3f76af90967bbddaaf250db983a8d3abb9ff189fb5a807cf3d4d android.hardware.neuralnetworks@1.3::types
		554baa3b317e077b850afcbaac99daeef56861b1786540e56275a4fcad1f43e3 android.hardware.neuralnetworks@1.3::types
		3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi
		a64467bae843569f0d465c5be7f0c7a5b987985b55a3ef4794dd5afc68538650 android.hardware.wifi.supplicant@1.3::ISupplicant
		44445b8a03d7b9e68b2fbd954672c18a8fce9e32851b0692f4f4ab3407f86ecb android.hardware.wifi.supplicant@1.3::ISupplicantStaIface

neuralnetworks/1.2/types.hal

+6 −5

Original line number	Diff line number	Diff line
		@@ -2448,15 +2448,17 @@ enum OperationType : int32_t {
		* 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}.
		* 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}.
		* 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.
		@@ -4124,7 +4126,6 @@ enum OperationType : int32_t {
		* * 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,

neuralnetworks/1.3/types.hal

+9 −6

Original line number	Diff line number	Diff line
		@@ -2375,15 +2375,17 @@ enum OperationType : int32_t {
		* 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}.
		* 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}.
		* 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.
		@@ -4034,6 +4036,7 @@ enum OperationType : int32_t {
		* * {@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
		*
		@@ -4044,14 +4047,14 @@ enum OperationType : int32_t {
		* 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} tensor,
		* 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 = @1.2::OperationType:SELECT,

neuralnetworks/1.3/vts/functional/CompilationCachingTests.cpp

+14 −28

Original line number	Diff line number	Diff line
		@@ -456,8 +456,7 @@ TEST_P(CompilationCachingTest, CacheSavingAndRetrieval) {
		}

		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		}

		TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
		@@ -519,8 +518,7 @@ TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
		}

		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		}

		TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
		@@ -541,8 +539,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -566,8 +563,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -590,8 +586,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -615,8 +610,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -727,8 +721,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -752,8 +745,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -776,8 +768,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -801,8 +792,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -914,8 +904,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -937,8 +926,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
		saveModelToCache(model, modelCache, dataCache, &preparedModel);
		ASSERT_NE(preparedModel, nullptr);
		// Execute and verify results.
		EvaluatePreparedModel(preparedModel, testModel,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModel, /testKind=/TestKind::GENERAL);
		// Check if prepareModelFromCache fails.
		preparedModel = nullptr;
		ErrorStatus status;
		@@ -1082,8 +1070,7 @@ TEST_P(CompilationCachingTest, SaveToCache_TOCTOU) {
		ASSERT_EQ(preparedModel, nullptr);
		} else {
		ASSERT_NE(preparedModel, nullptr);
		EvaluatePreparedModel(preparedModel, testModelAdd,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModelAdd, /testKind=/TestKind::GENERAL);
		}
		}
		}
		@@ -1144,8 +1131,7 @@ TEST_P(CompilationCachingTest, PrepareFromCache_TOCTOU) {
		ASSERT_EQ(preparedModel, nullptr);
		} else {
		ASSERT_NE(preparedModel, nullptr);
		EvaluatePreparedModel(preparedModel, testModelAdd,
		/testDynamicOutputShape=/false);
		EvaluatePreparedModel(preparedModel, testModelAdd, /testKind=/TestKind::GENERAL);
		}
		}
		}

neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp

+129 −21

Original line number	Diff line number	Diff line
		@@ -79,6 +79,21 @@ struct TestConfig {
		Executor executor;
		MeasureTiming measureTiming;
		OutputType outputType;
		// `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, MeasureTiming measureTiming, OutputType outputType)
		: executor(executor),
		measureTiming(measureTiming),
		outputType(outputType),
		reportSkipping(true) {}
		TestConfig(Executor executor, MeasureTiming measureTiming, OutputType outputType,
		bool reportSkipping)
		: executor(executor),
		measureTiming(measureTiming),
		outputType(outputType),
		reportSkipping(reportSkipping) {}
		};

		} // namespace
		@@ -219,7 +234,10 @@ static std::shared_ptr<::android::nn::ExecutionBurstController> CreateBurst(
		}

		void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,
		const TestConfig& testConfig) {
		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)) {
		@@ -290,6 +308,12 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo

		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 "
		@@ -343,44 +367,117 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo
		}

		void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,
		bool testDynamicOutputShape) {
		TestKind testKind) {
		std::initializer_list<OutputType> outputTypesList;
		std::initializer_list<MeasureTiming> measureTimingList;
		std::initializer_list<Executor> executorList;

		if (testDynamicOutputShape) {
		outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};
		switch (testKind) {
		case TestKind::GENERAL: {
		outputTypesList = {OutputType::FULLY_SPECIFIED};
		measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
		executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};
		} else {
		outputTypesList = {OutputType::FULLY_SPECIFIED};
		} break;
		case TestKind::DYNAMIC_SHAPE: {
		outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};
		measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
		executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};
		} break;
		case TestKind::QUANTIZATION_COUPLING: {
		LOG(FATAL) << "Wrong TestKind for EvaluatePreparedModel";
		return;
		} break;
		}

		for (const OutputType outputType : outputTypesList) {
		for (const MeasureTiming measureTiming : measureTimingList) {
		for (const Executor executor : executorList) {
		const TestConfig testConfig = {.executor = executor,
		.measureTiming = measureTiming,
		.outputType = outputType};
		const TestConfig testConfig(executor, measureTiming, outputType);
		EvaluatePreparedModel(preparedModel, testModel, testConfig);
		}
		}
		}
		}

		void Execute(const sp<IDevice>& device, const TestModel& testModel, bool testDynamicOutputShape) {
		void EvaluatePreparedCoupledModels(const sp<IPreparedModel>& preparedModel,
		const TestModel& testModel,
		const sp<IPreparedModel>& preparedCoupledModel,
		const TestModel& coupledModel) {
		std::initializer_list<OutputType> outputTypesList = {OutputType::FULLY_SPECIFIED};
		std::initializer_list<MeasureTiming> measureTimingList = {MeasureTiming::NO,
		MeasureTiming::YES};
		std::initializer_list<Executor> executorList = {Executor::ASYNC, Executor::SYNC,
		Executor::BURST};

		for (const OutputType outputType : outputTypesList) {
		for (const MeasureTiming measureTiming : measureTimingList) {
		for (const Executor executor : executorList) {
		const TestConfig testConfig(executor, measureTiming, outputType,
		/reportSkipping=/false);
		bool baseSkipped = false;
		EvaluatePreparedModel(preparedModel, testModel, testConfig, &baseSkipped);
		bool coupledSkipped = false;
		EvaluatePreparedModel(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 sp<IDevice>& device, const TestModel& testModel, TestKind testKind) {
		Model model = createModel(testModel);
		if (testDynamicOutputShape) {
		if (testKind == TestKind::DYNAMIC_SHAPE) {
		makeOutputDimensionsUnspecified(&model);
		}

		sp<IPreparedModel> preparedModel;
		switch (testKind) {
		case TestKind::GENERAL: {
		createPreparedModel(device, model, &preparedModel);
		if (preparedModel == nullptr) return;

		EvaluatePreparedModel(preparedModel, testModel, testDynamicOutputShape);
		EvaluatePreparedModel(preparedModel, testModel, TestKind::GENERAL);
		} break;
		case TestKind::DYNAMIC_SHAPE: {
		createPreparedModel(device, model, &preparedModel);
		if (preparedModel == nullptr) return;
		EvaluatePreparedModel(preparedModel, testModel, TestKind::DYNAMIC_SHAPE);
		} break;
		case TestKind::QUANTIZATION_COUPLING: {
		ASSERT_TRUE(testModel.hasQuant8AsymmOperands());
		createPreparedModel(device, model, &preparedModel, /reportSkipping/ false);
		TestModel signedQuantizedModel = convertQuant8AsymmOperandsToSigned(testModel);
		sp<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(preparedModel, testModel, preparedCoupledModel,
		signedQuantizedModel);
		} break;
		}
		}

		void GeneratedTestBase::SetUp() {
		@@ -403,12 +500,19 @@ class GeneratedTest : public GeneratedTestBase {};
		// Tag for the dynamic output shape tests
		class DynamicOutputShapeTest : public GeneratedTest {};

		// Tag for the dynamic output shape tests
		class DISABLED_QuantizationCouplingTest : public GeneratedTest {};

		TEST_P(GeneratedTest, Test) {
		Execute(kDevice, kTestModel, /testDynamicOutputShape=/false);
		Execute(kDevice, kTestModel, /testKind=/TestKind::GENERAL);
		}

		TEST_P(DynamicOutputShapeTest, Test) {
		Execute(kDevice, kTestModel, /testDynamicOutputShape=/true);
		Execute(kDevice, kTestModel, /testKind=/TestKind::DYNAMIC_SHAPE);
		}

		TEST_P(DISABLED_QuantizationCouplingTest, Test) {
		Execute(kDevice, kTestModel, /testKind=/TestKind::QUANTIZATION_COUPLING);
		}

		INSTANTIATE_GENERATED_TEST(GeneratedTest,
		@@ -417,4 +521,8 @@ INSTANTIATE_GENERATED_TEST(GeneratedTest,
		INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest,
		[](const TestModel& testModel) { return !testModel.expectFailure; });

		INSTANTIATE_GENERATED_TEST(DISABLED_QuantizationCouplingTest, [](const TestModel& testModel) {
		return testModel.hasQuant8AsymmOperands() && testModel.operations.size() == 1;
		});

		} // namespace android::hardware::neuralnetworks::V1_3::vts::functional