mindspore/predict/include/tensor.h

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/**
* 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.
*/
#ifndef PREDICT_INCLUDE_TENSOR_H_
#define PREDICT_INCLUDE_TENSOR_H_
#include <memory>
#include <vector>
#include "dlpack/dlpack.h"
#include "schema/inner/ms_generated.h"
#define MSPREDICT_API __attribute__((visibility("default")))
namespace mindspore {
namespace predict {
///\brief Allocator definition of MindSpore predict.
class Allocator;
///\brief Tensor definition of MindSpore predict.
class MSPREDICT_API Tensor {
public:
///\brief Constructor of MindSpore predict tensor.
///
///\param[in] tensor Define the parameters of the tensor.
///\param[in] copyData Malloc data for the tensor, and copy origin data from
/// input tensor.
///
///\return Instance of MindSpore predict tensor.
Tensor(const Tensor &tensor, bool copyData = false);
///\brief Constructor of MindSpore predict tensor.
///
///\param[in] dt Data Type of the tensor, see introduction to 'enum DataType'
/// for supported type.
///\param[in] dims Dimension Values such as height and width, which defined
/// the shape of the tensor.
///\param[in] format Tensor format, see introduction to 'enum Format' for
/// supported format.
///\param[in] data Data of the tensor.
///
///\return Instance of MindSpore predict tensor.
///
///\note
/// Length of data should align with dt, format and dims, otherwise the
/// application might run into unexpected error,
/// such as segment fault.
/// For example, dt is DT_FLOAT, format is FORMAT_NCHW, dims is [1,3,300,300],
/// then minimum length of data should
/// be 1 * 3 * 300 * 300 * sizeof(float).
Tensor(DataType dt, const std::vector<int64_t> &dims, Format format, void *data);
///\brief Destructor of MindSpore predict tensor.
~Tensor();
///\brief Get MindSpore predict tensor.
///
///\param[in] Definition of the tensor.
///
///\return Address of MindSpore predict tensor.
static Tensor *CopyFromTensorDef(const TensorDef &tensordef);
///\brief Get dtype of MindSpore predict tensor.
///
///\return Dtype of MindSpore predict tensor.
DLDataType GetTensorDtype() const;
///\brief Get data of MindSpore predict tensor.
///
///\return Address of MindSpore predict tensor data.
void *GetData() const;
///\brief Set data of MindSpore predict tensor.
///
///\param[in] data Address for data of the MindSpore predict tensor instance.
///
///\note
/// Length of data should align with dt, format and dims, otherwise the
/// application might run into unexpected error,
/// such as segment fault.
/// For example, dt is DT_FLOAT, format is FORMAT_NCHW, dims is [1,3,300,300],
/// then minimum length of data should
/// be 1 * 3 * 300 * 300 * sizeof(float).
void SetData(void *data);
///\brief Get data type of MindSpore predict tensor.
///
///\return Data Type of the tensor.
DataType GetDataType() const;
///\brief Set data type of MindSpore predict tensor.
///
///\param[in] dt Data Type of the tensor, see introduction to 'enum DataType'
/// for supported type.
void SetDataType(DataType dt);
///\brief Get number of dimension of MindSpore predict tensor.
///
///\return Number of dimension of the MindSpore predict tensor.
int GetNDim() const;
///\brief Get dimension of MindSpore predict tensor.
///
///\return Dimension of the MindSpore predict tensor.
std::vector<int64_t> GetDims() const;
///\brief Set dimension of MindSpore predict tensor.
///
///\param[in] dims Vector that has values of dimension.
void SetDims(const std::vector<int64_t> &dims);
///\brief Get format of MindSpore predict tensor.
///
///\return Format of the MindSpore predict tensor.
Format GetFormat() const { return format; }
///\brief Set format of MindSpore predict tensor.
///
///\param[in] format Format of the tensor.
void SetFormat(Format format) { this->format = format; }
///\brief Get reference count of MindSpore predict tensor.
///
///\return Reference count of the MindSpore predict tensor.
int RefCount() { return refCount; }
///\brief Increase reference count of MindSpore predict tensor.
///
///\param[in] ref The increase of the reference count.
void AddRef(int ref) { refCount += ref; }
///\brief Decrease reference count of MindSpore predict tensor.
///
///\param[in] ref The decrease of the reference count.
void DefRef(int ref) { refCount -= ref; }
///\brief Get element size of MindSpore predict tensor.
///
///\return Element size of MindSpore predict tensor.
size_t GetElementSize() const;
///\brief Get data size of MindSpore predict tensor.
///
///\return Data size of MindSpore predict tensor.
size_t GetDataSize() const;
///\brief Get element size of MindSpore predict tensor in NC4HW4 format.
///
///\param[in] isNhwc Whether the current format is NHWC.
///
///\return Element size of MindSpore predict tensor in NC4HW4 format.
size_t GetNC4HW4ElementSize(bool isNhwc);
///\brief Get data size of MindSpore predict tensor in NC4HW4 format.
///
///\param[in] isNhwc Whether the current format is NHWC.
///
///\return Data size of MindSpore predict tensor in NC4HW4 format.
size_t GetNC4HW4DataSize(bool isNhwc);
///\brief Malloc data for the MindSpore predict tensor.
///
///\param[in] allocator The malloc source for data.
///\param[in] refCount The reference count of the data.
///
///\return Return RET_OK if the data is successfully allocated, otherwhise return RET_ERROR.
int MallocData(std::shared_ptr<Allocator> allocator = nullptr, int refCount = 0);
///\brief Free the MindSpore predict tensor.
void FreeTensor();
///\brief Free the data of MindSpore predict tensor.
void ForceFreeData();
///\brief Free the data of MindSpore predict tensor.
void FreeData();
///\brief Compare data size of MindSpore predict tensor in NC4HW4 format.
///
///\param[in] dst The compare tensor.
///
///\return The result of fuction.
bool CompareShape(const Tensor &dst);
///\brief Compare shape of MindSpore predict tensor with another shape.
///
///\param[in] other The compare shape information.
///
///\return The result of function.
bool CompareShape(const std::vector<int64_t> &other);
///\brief Get instance of MindSpore predict tensor.
///
///\return Instance of MindSpore predict dlTensor.
DLTensor *GetDLTensor() { return &dlTensor; }
///\brief Get height of MindSpore predict tensor.
///
///\return Height of MindSpore predict tensor.
int64_t Height() const;
///\brief Get width of MindSpore predict tensor.
///
///\return Width of MindSpore predict tensor.
int64_t Width() const;
///\brief Get channel of MindSpore predict tensor.
///
///\return Channel of MindSpore predict tensor.
int64_t Channel() const;
///\brief Get batch of MindSpore predict tensor.
///
///\return Batch of MindSpore predict tensor.
int64_t Batch() const;
///\brief Get stride of MindSpore predict tensor.
///
///\param[in] index the index of stride.
///
///\return Stride of MindSpore predict tensor.
int64_t Stride(int index) const;
///\brief Set stride of MindSpore predict tensor by input.
///
///\param[in] index Index of stride
///\param[in] stride The stride to set
void SetStride(int index, int64_t stride);
///\brief Set stride of MindSpore predict tensor by dims.
void SetStride();
void SetScale(bool isScale = true);
private:
bool isScale = false;
int refCount = 0;
int isConst;
Format format;
DLTensor dlTensor;
std::shared_ptr<Allocator> allocator = nullptr;
std::vector<float> scale;
std::vector<int> zeroPoint;
};
} // namespace predict
} // namespace mindspore
#endif // PREDICT_INCLUDE_TENSOR_H_