Merge changes from topic "nnapi-aosp-sync" (ebce6577) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp

+2 −2

Original line number	Diff line number	Diff line
		@@ -242,8 +242,8 @@ void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> c
		// launch prepare model
		sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
		ASSERT_NE(nullptr, preparedModelCallback.get());
		Return<ErrorStatus> prepareLaunchStatus =
		device->prepareModel_1_1(model, preparedModelCallback);
		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));

neuralnetworks/1.1/IDevice.hal

+4 −1

Original line number	Diff line number	Diff line
		@@ -102,6 +102,8 @@ interface IDevice extends @1.0::IDevice {
		* Multiple threads can 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 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
		@@ -115,6 +117,7 @@ interface IDevice extends @1.0::IDevice {
		* - INVALID_ARGUMENT if one of the input arguments is
		* invalid
		*/
		prepareModel_1_1(Model model, IPreparedModelCallback callback)
		prepareModel_1_1(Model model, ExecutionPreference preference,
		IPreparedModelCallback callback)
		generates (ErrorStatus status);
		};

neuralnetworks/1.1/types.hal

+21 −0

Original line number	Diff line number	Diff line
		@@ -382,3 +382,24 @@ struct Model {
		*/
		bool relaxComputationFloat32toFloat16;
		};

		/**
		* Execution preferences.
		*/
		enum ExecutionPreference : int32_t {
		/**
		* Prefer executing in a way that minimizes battery drain.
		* This is desirable for compilations that will be executed often.
		*/
		LOW_POWER = 0,
		/**
		* Prefer returning a single answer as fast as possible, even if this causes
		* more power consumption.
		*/
		FAST_SINGLE_ANSWER = 1,
		/**
		* Prefer maximizing the throughput of successive frames, for example when
		* processing successive frames coming from the camera.
		*/
		SUSTAINED_SPEED = 2,
		};

neuralnetworks/1.1/vts/functional/ValidateModel.cpp

+31 −5

Original line number	Diff line number	Diff line
		@@ -50,13 +50,13 @@ static void validateGetSupportedOperations(const sp<IDevice>& device, const std:
		}

		static void validatePrepareModel(const sp<IDevice>& device, const std::string& message,
		const V1_1::Model& model) {
		const V1_1::Model& model, ExecutionPreference preference) {
		SCOPED_TRACE(message + " [prepareModel_1_1]");

		sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
		ASSERT_NE(nullptr, preparedModelCallback.get());
		Return<ErrorStatus> prepareLaunchStatus =
		device->prepareModel_1_1(model, preparedModelCallback);
		device->prepareModel_1_1(model, preference, preparedModelCallback);
		ASSERT_TRUE(prepareLaunchStatus.isOk());
		ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(prepareLaunchStatus));

		@@ -67,15 +67,24 @@ static void validatePrepareModel(const sp<IDevice>& device, const std::string& m
		ASSERT_EQ(nullptr, preparedModel.get());
		}

		static bool validExecutionPreference(ExecutionPreference preference) {
		return preference == ExecutionPreference::LOW_POWER \|\|
		preference == ExecutionPreference::FAST_SINGLE_ANSWER \|\|
		preference == ExecutionPreference::SUSTAINED_SPEED;
		}

		// Primary validation function. This function will take a valid model, apply a
		// mutation to it to invalidate the model, then pass it to interface calls that
		// use the model. Note that the model here is passed by value, and any mutation
		// to the model does not leave this function.
		static void validate(const sp<IDevice>& device, const std::string& message, V1_1::Model model,
		const std::function<void(Model*)>& mutation) {
		const std::function<void(Model*)>& mutation,
		ExecutionPreference preference = ExecutionPreference::FAST_SINGLE_ANSWER) {
		mutation(&model);
		if (validExecutionPreference(preference)) {
		validateGetSupportedOperations(device, message, model);
		validatePrepareModel(device, message, model);
		}
		validatePrepareModel(device, message, model, preference);
		}

		// Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation,
		@@ -486,6 +495,22 @@ static void addOperationOutputTest(const sp<IDevice>& device, const V1_1::Model&
		}
		}

		///////////////////////// 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 sp<IDevice>& device, const V1_1::Model& model) {
		for (int32_t preference : invalidExecutionPreferences) {
		const std::string message =
		"mutateExecutionPreferenceTest: preference " + std::to_string(preference);
		validate(device, message, model, [](Model*) {},
		static_cast<ExecutionPreference>(preference));
		}
		}

		////////////////////////// ENTRY POINT //////////////////////////////

		void ValidationTest::validateModel(const V1_1::Model& model) {
		@@ -503,6 +528,7 @@ void ValidationTest::validateModel(const V1_1::Model& model) {
		removeOperationOutputTest(device, model);
		addOperationInputTest(device, model);
		addOperationOutputTest(device, model);
		mutateExecutionPreferenceTest(device, model);
		}

		} // namespace functional

neuralnetworks/1.1/vts/functional/ValidateRequest.cpp

+2 −2

Original line number	Diff line number	Diff line
		@@ -60,8 +60,8 @@ static void createPreparedModel(const sp<IDevice>& device, const V1_1::Model& mo
		// launch prepare model
		sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
		ASSERT_NE(nullptr, preparedModelCallback.get());
		Return<ErrorStatus> prepareLaunchStatus =
		device->prepareModel_1_1(model, preparedModelCallback);
		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));