release-request-bde3636e-2b2d-4fd8-96bd-229c183f7fbe-for-git_pi-release-435799... (b1b8acf9) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.0/types.hal

+2 −31

Original line number	Diff line number	Diff line
		@@ -1002,21 +1002,6 @@ enum DeviceStatus : int32_t {
		UNKNOWN,
		};

		/**
		* A typed operation.
		*/
		struct OperationTuple {
		/**
		* The type of operation.
		*/
		OperationType operationType;

		/**
		* The input data type of operation.
		*/
		OperandType operandType;
		};

		/**
		* Performance information for the reference workload.
		*
		@@ -1038,20 +1023,6 @@ struct PerformanceInfo {
		* The capabilities of a driver.
		*/
		struct Capabilities {
		/**
		* A collection of typed operations supported by the driver.
		*/
		vec<OperationTuple> supportedOperationTuples;

		/**
		* Indicates whether a driver caches its prepared model for reuse the next
		* time the application begins. This is useful because the model may have
		* been prepared in a previous run.
		*
		* True if caching is supported, false otherwise.
		*/
		bool cachesCompilation;

		/**
		* Driver performance when operating on float32 data.
		*/
		@@ -1144,9 +1115,9 @@ struct Operand {
		*/
		struct Operation {
		/**
		* The tuple describing the operation type and input type.
		* The operation type.
		*/
		OperationTuple opTuple;
		OperationType type;

		/**
		* Describes the table that contains the indexes of the inputs of the

+2 −5

Original line number	Diff line number	Diff line
		@@ -78,9 +78,7 @@ Model createValidTestModel() {
		};

		const std::vector<Operation> operations = {{
		.opTuple = {OperationType::ADD, OperandType::TENSOR_FLOAT32},
		.inputs = {operand1, operand2, operand3},
		.outputs = {operand4},
		.type = OperationType::ADD, .inputs = {operand1, operand2, operand3}, .outputs = {operand4},
		}};

		const std::vector<uint32_t> inputIndexes = {operand1};
		@@ -107,8 +105,7 @@ Model createValidTestModel() {
		// create first invalid model
		Model createInvalidTestModel1() {
		Model model = createValidTestModel();
		model.operations[0].opTuple = {static_cast<OperationType>(0xDEADBEEF) /* INVALID */,
		OperandType::TENSOR_FLOAT32};
		model.operations[0].type = static_cast<OperationType>(0xDEADBEEF); /* INVALID */
		return model;
		}

+0 −3

Original line number	Diff line number	Diff line
		@@ -107,9 +107,6 @@ TEST_F(NeuralnetworksHidlTest, GetCapabilitiesTest) {
		Return<void> ret =
		device->getCapabilities([](ErrorStatus status, const Capabilities& capabilities) {
		EXPECT_EQ(ErrorStatus::NONE, status);
		EXPECT_NE(nullptr, capabilities.supportedOperationTuples.data());
		EXPECT_NE(0ull, capabilities.supportedOperationTuples.size());
		EXPECT_EQ(0u, static_cast<uint32_t>(capabilities.cachesCompilation) & ~0x1);
		EXPECT_LT(0.0f, capabilities.float32Performance.execTime);
		EXPECT_LT(0.0f, capabilities.float32Performance.powerUsage);
		EXPECT_LT(0.0f, capabilities.quantized8Performance.execTime);