Merge "Add new OperandType TENSOR_QUANT16_ASYMM." (f637f04a) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp

+4 −6

Original line number	Original line	Diff line number	Diff line
	@@ -45,13 +45,10 @@ using ::test_helper::bool8;
	using ::test_helper::compare;		using ::test_helper::compare;
	using ::test_helper::expectMultinomialDistributionWithinTolerance;		using ::test_helper::expectMultinomialDistributionWithinTolerance;
	using ::test_helper::filter;		using ::test_helper::filter;
	using ::test_helper::Float32Operands;
	using ::test_helper::for_all;		using ::test_helper::for_all;
	using ::test_helper::for_each;		using ::test_helper::for_each;
	using ::test_helper::Int32Operands;
	using ::test_helper::MixedTyped;		using ::test_helper::MixedTyped;
	using ::test_helper::MixedTypedExample;		using ::test_helper::MixedTypedExample;
	using ::test_helper::Quant8Operands;
	using ::test_helper::resize_accordingly;		using ::test_helper::resize_accordingly;

	template <typename T>		template <typename T>
	@@ -67,12 +64,13 @@ void copy_back_(std::map<int, std::vector<T>>* dst, const std::vector<RequestArg
	void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* src) {		void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* src) {
	copy_back_(&dst->float32Operands, ra, src);		copy_back_(&dst->float32Operands, ra, src);
	copy_back_(&dst->int32Operands, ra, src);		copy_back_(&dst->int32Operands, ra, src);
	copy_back_(&dst->quant8Operands, ra, src);		copy_back_(&dst->quant8AsymmOperands, ra, src);
	copy_back_(&dst->quant16Operands, ra, src);		copy_back_(&dst->quant16SymmOperands, ra, src);
	copy_back_(&dst->float16Operands, ra, src);		copy_back_(&dst->float16Operands, ra, src);
	copy_back_(&dst->bool8Operands, ra, src);		copy_back_(&dst->bool8Operands, ra, src);
	copy_back_(&dst->quant8ChannelOperands, ra, src);		copy_back_(&dst->quant8ChannelOperands, ra, src);
	static_assert(7 == MixedTyped::kNumTypes,		copy_back_(&dst->quant16AsymmOperands, ra, src);
			static_assert(8 == MixedTyped::kNumTypes,
	"Number of types in MixedTyped changed, but copy_back function wasn't updated");		"Number of types in MixedTyped changed, but copy_back function wasn't updated");
	}		}

neuralnetworks/1.2/types.hal

+13 −1

Original line number	Original line	Diff line number	Diff line
	@@ -76,6 +76,18 @@ enum OperandType : @1.0::OperandType {
	* where C is an index in the Channel dimension.		* where C is an index in the Channel dimension.
	*/		*/
	TENSOR_QUANT8_SYMM_PER_CHANNEL = 11,		TENSOR_QUANT8_SYMM_PER_CHANNEL = 11,
			/**
			* A tensor of 16 bit unsigned integers that represent real numbers.
			*
			* Attached to this tensor are two numbers that can be used to convert the
			* 16 bit integer to the real value and vice versa. These two numbers are:
			* - scale: a 32 bit floating point value greater than zero.
			* - zeroPoint: a 32 bit integer, in range [0, 65535].
			*
			* The formula is:
			* real_value = (integer_value - zeroPoint) * scale.
			*/
			TENSOR_QUANT16_ASYMM = 12,
	/* ADDING A NEW FUNDAMENTAL TYPE REQUIRES UPDATING THE VALUE OF		/* ADDING A NEW FUNDAMENTAL TYPE REQUIRES UPDATING THE VALUE OF
	* OperandTypeRange::OPERAND_FUNDAMENTAL_MAX.		* OperandTypeRange::OPERAND_FUNDAMENTAL_MAX.
	*/		*/
	@@ -89,7 +101,7 @@ enum OperandType : @1.0::OperandType {
	*/		*/
	enum OperandTypeRange : uint32_t {		enum OperandTypeRange : uint32_t {
	OPERAND_FUNDAMENTAL_MIN = 0,		OPERAND_FUNDAMENTAL_MIN = 0,
	OPERAND_FUNDAMENTAL_MAX = 11,		OPERAND_FUNDAMENTAL_MAX = 12,
	OPERAND_OEM_MIN = 10000,		OPERAND_OEM_MIN = 10000,
	OPERAND_OEM_MAX = 10001,		OPERAND_OEM_MAX = 10001,
	};		};

neuralnetworks/1.2/vts/functional/ValidateModel.cpp

+5 −0

Original line number	Original line	Diff line number	Diff line
	@@ -161,6 +161,7 @@ static uint32_t getInvalidRank(OperandType type) {
	case OperandType::TENSOR_FLOAT32:		case OperandType::TENSOR_FLOAT32:
	case OperandType::TENSOR_INT32:		case OperandType::TENSOR_INT32:
	case OperandType::TENSOR_QUANT8_ASYMM:		case OperandType::TENSOR_QUANT8_ASYMM:
			case OperandType::TENSOR_QUANT16_ASYMM:
	case OperandType::TENSOR_QUANT16_SYMM:		case OperandType::TENSOR_QUANT16_SYMM:
	case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:		case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
	return 0;		return 0;
	@@ -199,6 +200,7 @@ static float getInvalidScale(OperandType type) {
	case OperandType::TENSOR_INT32:		case OperandType::TENSOR_INT32:
	return -1.0f;		return -1.0f;
	case OperandType::TENSOR_QUANT8_ASYMM:		case OperandType::TENSOR_QUANT8_ASYMM:
			case OperandType::TENSOR_QUANT16_ASYMM:
	case OperandType::TENSOR_QUANT16_SYMM:		case OperandType::TENSOR_QUANT16_SYMM:
	return 0.0f;		return 0.0f;
	default:		default:
	@@ -233,6 +235,8 @@ static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
	return {1};		return {1};
	case OperandType::TENSOR_QUANT8_ASYMM:		case OperandType::TENSOR_QUANT8_ASYMM:
	return {-1, 256};		return {-1, 256};
			case OperandType::TENSOR_QUANT16_ASYMM:
			return {-1, 65536};
	case OperandType::TENSOR_QUANT16_SYMM:		case OperandType::TENSOR_QUANT16_SYMM:
	return {-32769, -1, 1, 32768};		return {-32769, -1, 1, 32768};
	default:		default:
	@@ -288,6 +292,7 @@ static void mutateOperand(Operand* operand, OperandType type) {
	newOperand.zeroPoint = 0;		newOperand.zeroPoint = 0;
	break;		break;
	case OperandType::TENSOR_QUANT8_ASYMM:		case OperandType::TENSOR_QUANT8_ASYMM:
			case OperandType::TENSOR_QUANT16_ASYMM:
	case OperandType::TENSOR_QUANT16_SYMM:		case OperandType::TENSOR_QUANT16_SYMM:
	newOperand.dimensions =		newOperand.dimensions =
	operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});		operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});