Loading neuralnetworks/1.2/vts/functional/ValidateModel.cpp +6 −0 Original line number Diff line number Diff line Loading @@ -325,6 +325,7 @@ static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, con // - ARGMIN and ARGMAX's first argument can be any of // TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM). // - CAST's argument can be any of TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM). // - RANDOM_MULTINOMIAL's argument can be either TENSOR_FLOAT16 or TENSOR_FLOAT32. switch (operation.type) { case OperationType::LSH_PROJECTION: { if (operand == operation.inputs[1]) { Loading @@ -339,6 +340,11 @@ static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, con return true; } } break; case OperationType::RANDOM_MULTINOMIAL: { if (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32) { return true; } } break; default: break; } Loading Loading
neuralnetworks/1.2/vts/functional/ValidateModel.cpp +6 −0 Original line number Diff line number Diff line Loading @@ -325,6 +325,7 @@ static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, con // - ARGMIN and ARGMAX's first argument can be any of // TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM). // - CAST's argument can be any of TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM). // - RANDOM_MULTINOMIAL's argument can be either TENSOR_FLOAT16 or TENSOR_FLOAT32. switch (operation.type) { case OperationType::LSH_PROJECTION: { if (operand == operation.inputs[1]) { Loading @@ -339,6 +340,11 @@ static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, con return true; } } break; case OperationType::RANDOM_MULTINOMIAL: { if (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32) { return true; } } break; default: break; } Loading