mindspore2022/mindspore/ccsrc/dataset/kernels/tensor_op.cc

71 lines
2.7 KiB
C++

/**
* Copyright 2019 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "dataset/kernels/tensor_op.h"
#include <iostream>
#include <memory>
#include <mutex>
#include <vector>
namespace mindspore {
namespace dataset {
// Name: Compute()
// Description: This Compute() take 1 Tensor and produce 1 Tensor.
// The derived class should override this function otherwise error.
Status TensorOp::Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) {
IO_CHECK(input, output);
if (!OneToOne()) {
return Status(StatusCode::kUnexpectedError, "Wrong Compute() function is called. This is not 1-1 TensorOp.");
} else {
return Status(StatusCode::kUnexpectedError,
"Is this TensorOp 1-1? If yes, please implement this Compute() in the derived class.");
}
}
// Name: Compute()
// Description: This Compute() take multiple Tensors from different columns and produce multiple Tensors too.
// The derived class should override this function otherwise error.
Status TensorOp::Compute(const std::vector<std::shared_ptr<Tensor>> &input,
std::vector<std::shared_ptr<Tensor>> *output) {
IO_CHECK_VECTOR(input, output);
if (OneToOne()) {
output->resize(1);
return Compute(input[0], &(*output)[0]);
}
return Status(StatusCode::kUnexpectedError,
"Is this TensorOp oneToOne? If no, please implement this Compute() in the derived class.");
}
void TensorOp::Print(std::ostream &out) const { out << "TensorOp" << std::endl; }
Status TensorOp::OutputShape(const std::vector<TensorShape> &inputs, std::vector<TensorShape> &outputs) {
if (inputs.size() != NumInput())
return Status(StatusCode::kUnexpectedError,
"The size of the input argument vector does not match the number of inputs");
outputs = inputs;
return Status::OK();
}
Status TensorOp::OutputType(const std::vector<DataType> &inputs, std::vector<DataType> &outputs) {
if (inputs.size() != NumInput())
return Status(StatusCode::kUnexpectedError,
"The size of the input argument vector does not match the number of inputs");
outputs = inputs;
return Status::OK();
}
} // namespace dataset
} // namespace mindspore