Class Serialization
Defined in File serialization.h
Class Documentation
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class Serialization
The Serialization class is used to summarize methods for reading and writing model files.
Public Static Functions
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static inline 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)
Loads a model file from memory buffer.
- 参数
model_data – [in] A buffer filled by model file.
data_size – [in] The size of the buffer.
model_type – [in] The Type of model file, options are ModelType::kMindIR, ModelType::kOM.
graph – [out] The output parameter, an object saves graph data.
dec_key – [in] The decryption key, key length is 16, 24, or 32. Not supported on MindSpore Lite.
dec_mode – [in] The decryption mode, optional options are AES-GCM, AES-CBC. Not supported on MindSpore Lite.
- 返回
Status.
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static inline Status Load(const std::string &file, ModelType model_type, Graph *graph, const Key &dec_key = {}, const std::string &dec_mode = kDecModeAesGcm)
Loads a model file from path.
- 参数
file – [in] The path of model file.
model_type – [in] The Type of model file, options are ModelType::kMindIR, ModelType::kOM.
graph – [out] The output parameter, an object saves graph data.
dec_key – [in] The decryption key, key length is 16, 24, or 32. Not supported on MindSpore Lite.
dec_mode – [in] The decryption mode, optional options are AES-GCM, AES-CBC. Not supported on MindSpore Lite.
- 返回
Status.
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static inline 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)
Load multiple models from multiple files, MindSpore Lite does not provide this feature.
- 参数
files – [in] The path of model files.
model_type – [in] The Type of model file, options are ModelType::kMindIR, ModelType::kOM.
graphs – [out] The output parameter, an object saves graph data.
dec_key – [in] The decryption key, key length is 16, 24, or 32.
dec_mode – [in] The decryption mode, optional options are AES-GCM, AES-CBC.
- 返回
Status.
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static inline Status SetParameters(const std::map<std::string, Buffer> ¶meters, Model *model)
Configure model parameters, MindSpore Lite does not provide this feature.
- 参数
parameters – [in] The parameters.
model – [in] The model.
- 返回
Status.
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static inline 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 = {})
Export training model from memory buffer, MindSpore Lite does not provide this feature.
- 参数
model – [in] The model data.
model_type – [in] The model file type.
model_data – [out] The model buffer.
quantization_type – [in] The quantification type.
export_inference_only – [in] Whether to export a reasoning only model.
output_tensor_name – [in] The set the name of the output tensor of the exported reasoning model, default as empty, and export the complete reasoning model.
- 返回
Status.
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static inline 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 = {})
Export training model from file.
- 参数
model – [in] The model data.
model_type – [in] The model file type.
model_file – [in] The path of exported model file.
quantization_type – [in] The quantification type.
export_inference_only – [in] Whether to export a reasoning only model.
output_tensor_name – [in] The set the name of the output tensor of the exported reasoning model, default as empty, and export the complete reasoning model.
- 返回
Status.
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static inline Status ExportWeightsCollaborateWithMicro(const Model &model, ModelType model_type, const std::string &weight_file, bool is_inference = true, bool enable_fp16 = false, const std::vector<std::string> &changeable_weights_name = {})
Experimental feature. Export model's weights, which can be used in micro only.
- 参数
model – [in] The model data.
model_type – [in] The model file type.
weight_file – [in] The path of exported weight file.
is_inference – [in] Whether to export weights from a reasoning model. Currently, only support this is
true
.enable_fp16 – [in] Float-weight is whether to be saved in float16 format.
changeable_weights_name – [in] The set the name of these weight tensors, whose shape is changeable.
- 返回
Status.
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static inline 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)