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luoyang authored 2021-04-12 11:42 . Fix codex warning
/**
* Copyright 2020-2021 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.
*/
#ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_EXECUTE_H_
#define MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_EXECUTE_H_
#include <string>
#include <vector>
#include <map>
#include <memory>
#include "include/api/context.h"
#include "include/api/types.h"
#include "minddata/dataset/include/constants.h"
#include "minddata/dataset/include/transforms.h"
namespace mindspore {
namespace dataset {
class DeviceResource;
// class to run tensor operations in eager mode
class Execute {
public:
/// \brief Constructor
// FIXME - Temporarily overload Execute to support both TensorOperation and TensorTransform
explicit Execute(std::shared_ptr<TensorOperation> op, MapTargetDevice deviceType = MapTargetDevice::kCpu,
uint32_t device_id = 0);
explicit Execute(std::shared_ptr<TensorTransform> op, MapTargetDevice deviceType = MapTargetDevice::kCpu,
uint32_t device_id = 0);
explicit Execute(std::reference_wrapper<TensorTransform> op, MapTargetDevice deviceType = MapTargetDevice::kCpu,
uint32_t device_id = 0);
explicit Execute(TensorTransform *op, MapTargetDevice deviceType = MapTargetDevice::kCpu, uint32_t device_id = 0);
explicit Execute(std::vector<std::shared_ptr<TensorOperation>> ops,
MapTargetDevice deviceType = MapTargetDevice::kCpu, uint32_t device_id = 0);
explicit Execute(std::vector<std::shared_ptr<TensorTransform>> ops,
MapTargetDevice deviceType = MapTargetDevice::kCpu, uint32_t device_id = 0);
explicit Execute(const std::vector<std::reference_wrapper<TensorTransform>> ops,
MapTargetDevice deviceType = MapTargetDevice::kCpu, uint32_t device_id = 0);
explicit Execute(const std::vector<TensorTransform *> &ops, MapTargetDevice deviceType = MapTargetDevice::kCpu,
uint32_t device_id = 0);
/// \brief Destructor
~Execute();
/// \brief callable function to execute the TensorOperation in eager mode
/// \param[in] input Tensor to be transformed
/// \param[out] output Transformed tensor
/// \return Status code
Status operator()(const mindspore::MSTensor &input, mindspore::MSTensor *output);
/// \brief callable function to execute the TensorOperation in eager mode
/// \param[in] input_tensor_list List of Tensor to be transformed
/// \param[out] out Result tensor after transform
/// \return - Status
Status operator()(const std::vector<mindspore::MSTensor> &input_tensor_list, std::vector<mindspore::MSTensor> *out);
Status DeviceMemoryRelease();
std::string AippCfgGenerator();
private:
Status ParseTransforms_();
Status validate_device_();
std::vector<std::shared_ptr<TensorTransform>> transforms_;
std::vector<std::shared_ptr<TensorOperation>> ops_;
MapTargetDevice device_type_;
std::shared_ptr<DeviceResource> device_resource_;
struct ExtraInfo;
std::shared_ptr<ExtraInfo> info_;
};
} // namespace dataset
} // namespace mindspore
#endif // MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_EXECUTE_H_
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https://gitee.com/mindspore/mindspore.git
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mindspore
mindspore
mindspore
r1.2

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