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ONNX header cleaning and updated documentation
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,143 +1,76 @@ | ||
| #ifndef EDDL_EDDL_ONNX_H | ||
| #define EDDL_EDDL_ONNX_H | ||
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| #include <string> | ||
| #include <vector> | ||
| #include <map> | ||
| #include "eddl/net/net.h" | ||
| #include "eddl/layers/layer.h" | ||
| #include "eddl/layers/core/layer_core.h" | ||
| #include "eddl/layers/conv/layer_conv.h" | ||
| #include "eddl/layers/recurrent/layer_recurrent.h" | ||
| #include "eddl/layers/pool/layer_pool.h" | ||
| #include "eddl/layers/core/layer_core.h" | ||
| #include "eddl/layers/layer.h" | ||
| #include "eddl/layers/merge/layer_merge.h" | ||
| #include "eddl/layers/operators/layer_operators.h" | ||
| #include "eddl/layers/normalization/layer_normalization.h" | ||
| #include "eddl/layers/operators/layer_operators.h" | ||
| #include "eddl/layers/pool/layer_pool.h" | ||
| #include "eddl/layers/recurrent/layer_recurrent.h" | ||
| #include "eddl/net/net.h" | ||
| #include <map> | ||
| #include <string> | ||
| #include <vector> | ||
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| enum LOG_LEVEL { | ||
| TRACE = 0, | ||
| DEBUG = 1, | ||
| INFO = 2, | ||
| WARN = 3, | ||
| ERROR = 4, | ||
| NO_LOGS = 5 | ||
| }; | ||
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| // Importing module | ||
| //------------------------------------------------------------------------------ | ||
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| /** | ||
| * @brief Imports ONNX Net from file | ||
| * | ||
| * @param path Path to the file where the net in ONNX format is saved | ||
| * @param mem (default 0) | ||
| * @param log_level Available: LOG_LEVEL::{TRACE, DEBUG, INFO, WARN, ERROR, | ||
| * NO_LOGS}. (default LOG_LEVEL::INFO) | ||
| * | ||
| * @return Net | ||
| */ | ||
| Net *import_net_from_onnx_file(std::string path, int mem = 0, int log_level = LOG_LEVEL::INFO); | ||
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| Net *import_net_from_onnx_pointer(void *serialized_model, size_t model_size, int mem = 0); | ||
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| Net *import_net_from_onnx_string(std::string *model_string, int mem = 0); | ||
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| // Exporting module | ||
| //---------------------------------------------------------------------------------------- | ||
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| /** | ||
| * @brief Saves a model with the onnx format in the file path provided | ||
| * | ||
| * @param net Net to be saved | ||
| * @param path Path to the file where the net in ONNX format will be saved | ||
| * | ||
| * @return (void) | ||
| */ | ||
| void save_net_to_onnx_file(Net *net, string path); | ||
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| // Returns a pointer to the serialized model in Onnx | ||
| size_t serialize_net_to_onnx_pointer(Net *net, void *&serialized_model, bool gradients = false); | ||
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| // Returns a string containing the serialized model in Onnx | ||
| std::string *serialize_net_to_onnx_string(Net *net, bool gradients = false); | ||
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| // Distributed Module | ||
| // --------------------------------------------------------------------------------------- | ||
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| void set_weights_from_onnx(Net *net, std::string *model_string); | ||
| void set_weights_from_onnx_pointer(Net *net, void *ptr_model, size_t model_size); | ||
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| void apply_grads_from_onnx(Net *net, std::string *model_string); | ||
| void apply_grads_from_onnx_pointer(Net *net, void *ptr_onnx, size_t count); | ||
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| //#if defined(cPROTO) | ||
| //# include "serialization/onnx/onnx.pb.h" | ||
| //#endif | ||
| enum LOG_LEVEL{ | ||
| TRACE = 0, | ||
| DEBUG = 1, | ||
| INFO = 2, | ||
| WARN = 3, | ||
| ERROR = 4, | ||
| NO_LOGS = 5 | ||
| }; | ||
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| //Importing module | ||
| //------------------------------------------------------------------------------ | ||
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| Net* import_net_from_onnx_file(std::string path, int mem=0, int log_level= LOG_LEVEL::INFO ); | ||
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| Net* import_net_from_onnx_pointer(void* serialized_model, size_t model_size, int mem=0); | ||
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| Net* import_net_from_onnx_string(std::string* model_string, int mem=0); | ||
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| //#if defined(cPROTO) | ||
| // Net* build_net_onnx(onnx::ModelProto model, int mem); | ||
| //#endif | ||
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| // Exporting module | ||
| //---------------------------------------------------------------------------------------- | ||
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| // Saves a model with the onnx format in the file path provided | ||
| void save_net_to_onnx_file( Net *net, string path ); | ||
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| // Returns a pointer to the serialized model in Onnx | ||
| size_t serialize_net_to_onnx_pointer( Net *net, void * & serialized_model, bool gradients=false ); | ||
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| // Returns a string containing the serialized model in Onnx | ||
| std::string* serialize_net_to_onnx_string(Net* net, bool gradients=false); | ||
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| // Builds the onnx model from the net | ||
| //#if defined(cPROTO) | ||
| // onnx::ModelProto build_onnx_model( Net *net, bool gradients ); | ||
| // | ||
| // // Builds the graph of the ModelProto from the net | ||
| // void set_graph( onnx::ModelProto *model, Net *net, bool gradients ); | ||
| // | ||
| // // Builds a node in the onnx graph from the layer of eddl | ||
| // void build_node_from_layer( Layer *layer, onnx::GraphProto *graph, bool gradients ); | ||
| // | ||
| // // Node builders | ||
| // //---------------------------------------------------------------------------------------- | ||
| // | ||
| // void build_conv_node( LConv *layer, onnx::GraphProto *graph, bool gradients ); | ||
| // | ||
| // void build_gemm_node( LDense *layer, onnx::GraphProto *graph, bool gradients ); | ||
| // | ||
| // void build_maxpool_node( LMaxPool *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_averagepool_node( LAveragePool *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_reshape_node( LReshape *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_permute_node( LPermute *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_relu_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_sigmoid_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_hard_sigmoid_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_tanh_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_exp_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_linear_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_leaky_relu_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_thresholded_relu_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_elu_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_selu_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_softmax_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_softsign_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_softplus_node( LActivation *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_concat_node( LConcat *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_add_node( LAdd *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_sub_node( LSubtract *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_average_node( LAverage *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_matmul_node( LMatMul *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_max_node( LMaximum *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_min_node( LMinimum *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_batchnorm_node( LBatchNorm *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_dropout_node( LDropout *layer, onnx::GraphProto *graph ); | ||
| // | ||
| // void build_upsample_node( LUpSampling *layer, onnx::GraphProto *graph ); | ||
| //#endif | ||
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| // Distributed Module | ||
| // --------------------------------------------------------------------------------------- | ||
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| void set_weights_from_onnx(Net* net, std::string* model_string); | ||
| void set_weights_from_onnx_pointer(Net* net, void *ptr_model, size_t model_size ); | ||
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| void apply_grads_from_onnx(Net* net, std::string* model_string); | ||
| void apply_grads_from_onnx_pointer( Net* net, void * ptr_onnx, size_t count ); | ||
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| //#if defined(cPROTO) | ||
| // map<string, vector<Tensor*> > get_tensors_from_onnx(onnx::ModelProto model); | ||
| //#endif | ||
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| #endif //EDDL_EDDL_ONNX_H | ||
| #endif // EDDL_EDDL_ONNX_H |
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