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serialization.h 8.46 KB
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/**
* Copyright 2020 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_INCLUDE_API_SERIALIZATION_H
#define MINDSPORE_INCLUDE_API_SERIALIZATION_H
#include <string>
#include <vector>
#include <map>
#include <memory>
#include "include/api/status.h"
#include "include/api/types.h"
#include "include/api/model.h"
#include "include/api/graph.h"
#include "include/api/dual_abi_helper.h"
namespace mindspore {
/// \brief The Serialization class is used to summarize methods for reading and writing model files.
class MS_API Serialization {
public:
/// \brief Loads a model file from memory buffer.
///
/// \param[in] model_data A buffer filled by model file.
/// \param[in] data_size The size of the buffer.
/// \param[in] model_type The Type of model file, options are ModelType::kMindIR, ModelType::kOM.
/// \param[out] graph The output parameter, an object saves graph data.
/// \param[in] dec_key The decryption key, key length is 16, 24, or 32. Not supported on MindSpore Lite.
/// \param[in] dec_mode The decryption mode, optional options are AES-GCM, AES-CBC. Not supported on MindSpore Lite.
///
/// \return Status.
inline static Status Load(const void *model_data, size_t data_size, ModelType model_type, Graph *graph,
const Key &dec_key = {}, const std::string &dec_mode = kDecModeAesGcm);
/// \brief Loads a model file from path.
///
/// \param[in] file The path of model file.
/// \param[in] model_type The Type of model file, options are ModelType::kMindIR, ModelType::kOM.
/// \param[out] graph The output parameter, an object saves graph data.
/// \param[in] dec_key The decryption key, key length is 16, 24, or 32. Not supported on MindSpore Lite.
/// \param[in] dec_mode The decryption mode, optional options are AES-GCM, AES-CBC. Not supported on MindSpore Lite.
///
/// \return Status.
inline static Status Load(const std::string &file, ModelType model_type, Graph *graph, const Key &dec_key = {},
const std::string &dec_mode = kDecModeAesGcm);
/// \brief Load multiple models from multiple files, MindSpore Lite does not provide this feature.
///
/// \param[in] files The path of model files.
/// \param[in] model_type The Type of model file, options are ModelType::kMindIR, ModelType::kOM.
/// \param[out] graphs The output parameter, an object saves graph data.
/// \param[in] dec_key The decryption key, key length is 16, 24, or 32.
/// \param[in] dec_mode The decryption mode, optional options are AES-GCM, AES-CBC.
///
/// \return Status.
inline static Status Load(const std::vector<std::string> &files, ModelType model_type, std::vector<Graph> *graphs,
const Key &dec_key = {}, const std::string &dec_mode = kDecModeAesGcm);
/// \brief Configure model parameters, MindSpore Lite does not provide this feature.
///
/// \param[in] parameters The parameters.
/// \param[in] model The model.
///
/// \return Status.
inline static Status SetParameters(const std::map<std::string, Buffer> &parameters, Model *model);
/// \brief Export training model from memory buffer, MindSpore Lite does not provide this feature.
///
/// \param[in] model The model data.
/// \param[in] model_type The model file type.
/// \param[out] model_data The model buffer.
/// \param[in] quantization_type The quantification type.
/// \param[in] export_inference_only Whether to export a reasoning only model.
/// \param[in] output_tensor_name The set the name of the output tensor of the exported reasoning model, default as
/// empty, and export the complete reasoning model.
///
/// \return Status.
inline static Status ExportModel(const Model &model, ModelType model_type, Buffer *model_data,
QuantizationType quantization_type = kNoQuant, bool export_inference_only = true,
const std::vector<std::string> &output_tensor_name = {});
/// \brief Export training model from file.
///
/// \param[in] model The model data.
/// \param[in] model_type The model file type.
/// \param[in] model_file The path of exported model file.
/// \param[in] quantization_type The quantification type.
/// \param[in] export_inference_only Whether to export a reasoning only model.
/// \param[in] output_tensor_name The set the name of the output tensor of the exported reasoning model, default as
/// empty, and export the complete reasoning model.
///
/// \return Status.
inline static Status ExportModel(const Model &model, ModelType model_type, const std::string &model_file,
QuantizationType quantization_type = kNoQuant, bool export_inference_only = true,
std::vector<std::string> output_tensor_name = {});
private:
static Status Load(const void *model_data, size_t data_size, ModelType model_type, Graph *graph, const Key &dec_key,
const std::vector<char> &dec_mode);
static Status Load(const std::vector<char> &file, ModelType model_type, Graph *graph);
static Status Load(const std::vector<char> &file, ModelType model_type, Graph *graph, const Key &dec_key,
const std::vector<char> &dec_mode);
static Status Load(const std::vector<std::vector<char>> &files, ModelType model_type, std::vector<Graph> *graphs,
const Key &dec_key, const std::vector<char> &dec_mode);
static Status SetParameters(const std::map<std::vector<char>, Buffer> &parameters, Model *model);
static Status ExportModel(const Model &model, ModelType model_type, const std::vector<char> &model_file,
QuantizationType quantization_type, bool export_inference_only,
const std::vector<std::vector<char>> &output_tensor_name);
static Status ExportModel(const Model &model, ModelType model_type, Buffer *model_data,
QuantizationType quantization_type, bool export_inference_only,
const std::vector<std::vector<char>> &output_tensor_name);
};
Status Serialization::Load(const void *model_data, size_t data_size, ModelType model_type, Graph *graph,
const Key &dec_key, const std::string &dec_mode) {
return Load(model_data, data_size, model_type, graph, dec_key, StringToChar(dec_mode));
}
Status Serialization::Load(const std::string &file, ModelType model_type, Graph *graph, const Key &dec_key,
const std::string &dec_mode) {
return Load(StringToChar(file), model_type, graph, dec_key, StringToChar(dec_mode));
}
Status Serialization::Load(const std::vector<std::string> &files, ModelType model_type, std::vector<Graph> *graphs,
const Key &dec_key, const std::string &dec_mode) {
return Load(VectorStringToChar(files), model_type, graphs, dec_key, StringToChar(dec_mode));
}
Status Serialization::SetParameters(const std::map<std::string, Buffer> &parameters, Model *model) {
return SetParameters(MapStringToChar<Buffer>(parameters), model);
}
Status Serialization::ExportModel(const Model &model, ModelType model_type, const std::string &model_file,
QuantizationType quantization_type, bool export_inference_only,
std::vector<std::string> output_tensor_name) {
return ExportModel(model, model_type, StringToChar(model_file), quantization_type, export_inference_only,
VectorStringToChar(output_tensor_name));
}
Status Serialization::ExportModel(const Model &model, ModelType model_type, Buffer *model_data,
QuantizationType quantization_type, bool export_inference_only,
const std::vector<std::string> &output_tensor_name) {
return ExportModel(model, model_type, model_data, quantization_type, export_inference_only,
VectorStringToChar(output_tensor_name));
}
} // namespace mindspore
#endif // MINDSPORE_INCLUDE_API_SERIALIZATION_H
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