Merge "Fix VTS ValidationTest for 1.2 ops." (fa3f021f) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.2/vts/functional/ValidateModel.cpp

+119 −26

Original line number	Diff line number	Diff line
		@@ -224,8 +224,9 @@ static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
		case OperandType::TENSOR_INT32:
		return {1};
		case OperandType::TENSOR_QUANT8_ASYMM:
		case OperandType::TENSOR_QUANT16_ASYMM:
		return {-1, 256};
		case OperandType::TENSOR_QUANT16_ASYMM:
		return {-32769, 32768};
		default:
		return {};
		}
		@@ -291,30 +292,42 @@ static void mutateOperand(Operand* operand, OperandType type) {
		*operand = newOperand;
		}

		static bool mutateOperationOperandTypeSkip(size_t operand, const Model& model) {
		// LSH_PROJECTION's second argument is allowed to have any type. This is the
		// only operation that currently has a type that can be anything independent
		// from any other type. Changing the operand type to any other type will
		// result in a valid model for LSH_PROJECTION. If this is the case, skip the
		// test.
		static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, const Model& model) {
		// Do not test OEM types
		if (type == model.operands[operand].type \|\| type == OperandType::OEM \|\|
		type == OperandType::TENSOR_OEM_BYTE) {
		return true;
		}
		for (const Operation& operation : model.operations) {
		if (operation.type == OperationType::LSH_PROJECTION && operand == operation.inputs[1]) {
		// Skip mutateOperationOperandTypeTest for the following operations.
		// - LSH_PROJECTION's second argument is allowed to have any type.
		// - ARGMIN and ARGMAX's first argument can be any of TENSOR_(FLOAT32\|INT32\|QUANT8_ASYMM).
		// - CAST's argument can be any of TENSOR_(FLOAT32\|INT32\|QUANT8_ASYMM).
		switch (operation.type) {
		case OperationType::LSH_PROJECTION: {
		if (operand == operation.inputs[1]) {
		return true;
		}
		} break;
		case OperationType::CAST:
		case OperationType::ARGMAX:
		case OperationType::ARGMIN: {
		if (type == OperandType::TENSOR_FLOAT32 \|\| type == OperandType::TENSOR_INT32 \|\|
		type == OperandType::TENSOR_QUANT8_ASYMM) {
		return true;
		}
		} break;
		default:
		break;
		}
		}
		return false;
		}

		static void mutateOperationOperandTypeTest(const sp<IDevice>& device, const Model& model) {
		for (size_t operand = 0; operand < model.operands.size(); ++operand) {
		if (mutateOperationOperandTypeSkip(operand, model)) {
		continue;
		}
		for (OperandType invalidOperandType : hidl_enum_range<OperandType>{}) {
		// Do not test OEM types
		if (invalidOperandType == model.operands[operand].type \|\|
		invalidOperandType == OperandType::OEM \|\|
		invalidOperandType == OperandType::TENSOR_OEM_BYTE) {
		if (mutateOperationOperandTypeSkip(operand, invalidOperandType, model)) {
		continue;
		}
		const std::string message = "mutateOperationOperandTypeTest: operand " +
		@@ -406,8 +419,26 @@ static void removeOperand(Model* model, uint32_t index) {
		removeValueAndDecrementGreaterValues(&model->outputIndexes, index);
		}

		static bool removeOperandSkip(size_t operand, const Model& model) {
		for (const Operation& operation : model.operations) {
		// Skip removeOperandTest for the following operations.
		// - SPLIT's outputs are not checked during prepareModel.
		if (operation.type == OperationType::SPLIT) {
		for (const size_t outOprand : operation.outputs) {
		if (operand == outOprand) {
		return true;
		}
		}
		}
		}
		return false;
		}

		static void removeOperandTest(const sp<IDevice>& device, const Model& model) {
		for (size_t operand = 0; operand < model.operands.size(); ++operand) {
		if (removeOperandSkip(operand, model)) {
		continue;
		}
		const std::string message = "removeOperandTest: operand " + std::to_string(operand);
		validate(device, message, model,
		[operand](Model* model) { removeOperand(model, operand); });
		@@ -433,15 +464,76 @@ static void removeOperationTest(const sp<IDevice>& device, const Model& model) {

		///////////////////////// REMOVE OPERATION INPUT /////////////////////////

		static bool removeOperationInputSkip(const Operation& op, size_t input) {
		// Skip removeOperationInputTest for the following operations.
		// - CONCATENATION has at least 2 inputs, with the last element being INT32.
		// - CONV_2D, DEPTHWISE_CONV_2D, MAX_POOL_2D, AVERAGE_POOL_2D, L2_POOL_2D, RESIZE_BILINEAR,
		// SPACE_TO_DEPTH, SPACE_TO_DEPTH, SPACE_TO_BATCH_ND, BATCH_TO_SPACE_ND can have an optional
		// layout parameter.
		// - L2_NORMALIZATION, LOCAL_RESPONSE_NORMALIZATION, SOFTMAX can have an optional axis
		// parameter.
		switch (op.type) {
		case OperationType::CONCATENATION: {
		if (op.inputs.size() > 2 && input != op.inputs.size() - 1) {
		return true;
		}
		} break;
		case OperationType::DEPTHWISE_CONV_2D: {
		if ((op.inputs.size() == 12 && input == 11) \|\| (op.inputs.size() == 9 && input == 8)) {
		return true;
		}
		} break;
		case OperationType::CONV_2D:
		case OperationType::AVERAGE_POOL_2D:
		case OperationType::MAX_POOL_2D:
		case OperationType::L2_POOL_2D: {
		if ((op.inputs.size() == 11 && input == 10) \|\| (op.inputs.size() == 8 && input == 7)) {
		return true;
		}
		} break;
		case OperationType::RESIZE_BILINEAR: {
		if (op.inputs.size() == 4 && input == 3) {
		return true;
		}
		} break;
		case OperationType::SPACE_TO_DEPTH:
		case OperationType::DEPTH_TO_SPACE:
		case OperationType::BATCH_TO_SPACE_ND: {
		if (op.inputs.size() == 3 && input == 2) {
		return true;
		}
		} break;
		case OperationType::SPACE_TO_BATCH_ND: {
		if (op.inputs.size() == 4 && input == 3) {
		return true;
		}
		} break;
		case OperationType::L2_NORMALIZATION: {
		if (op.inputs.size() == 2 && input == 1) {
		return true;
		}
		} break;
		case OperationType::LOCAL_RESPONSE_NORMALIZATION: {
		if (op.inputs.size() == 6 && input == 5) {
		return true;
		}
		} break;
		case OperationType::SOFTMAX: {
		if (op.inputs.size() == 3 && input == 2) {
		return true;
		}
		} break;
		default:
		break;
		}
		return false;
		}

		static void removeOperationInputTest(const sp<IDevice>& device, const Model& model) {
		for (size_t operation = 0; operation < model.operations.size(); ++operation) {
		for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
		const Operation& op = model.operations[operation];
		// CONCATENATION has at least 2 inputs, with the last element being
		// INT32. Skip this test if removing one of CONCATENATION's
		// inputs still produces a valid model.
		if (op.type == OperationType::CONCATENATION && op.inputs.size() > 2 &&
		input != op.inputs.size() - 1) {
		if (removeOperationInputSkip(op, input)) {
		continue;
		}
		const std::string message = "removeOperationInputTest: operation " +
		@@ -479,12 +571,13 @@ static void removeOperationOutputTest(const sp<IDevice>& device, const Model& mo

		///////////////////////// ADD OPERATION INPUT /////////////////////////

		static bool addOperationInputSkip(const Operation& operation) {
		static bool addOperationInputSkip(const Operation& op) {
		// Skip addOperationInputTest for the following operations.
		// L2_NORMALIZATION, LOCAL_RESPONSE_NORMALIZATION, SOFTMAX can have an optional axis parameter.
		if (operation.type == OperationType::L2_NORMALIZATION \|\|
		operation.type == OperationType::LOCAL_RESPONSE_NORMALIZATION \|\|
		operation.type == OperationType::SOFTMAX) {
		// - L2_NORMALIZATION, LOCAL_RESPONSE_NORMALIZATION, SOFTMAX can have an optional INT32 axis
		// parameter.
		if ((op.type == OperationType::L2_NORMALIZATION && op.inputs.size() == 1) \|\|
		(op.type == OperationType::LOCAL_RESPONSE_NORMALIZATION && op.inputs.size() == 5) \|\|
		(op.type == OperationType::SOFTMAX && op.inputs.size() == 2)) {
		return true;
		}
		return false;