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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
*
* 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 __TFLITE_LOADER_LOADER_H__
#define __TFLITE_LOADER_LOADER_H__
#include "schema_generated.h"
#include "graph/Graph.h"
#include <fstream>
#include <map>
namespace tflite_loader
{
/**
* @brief TFLite model loader
*/
class Loader
{
public:
/**
* @brief Construct a new Loader object
*
* @param graph reference on graph
*/
explicit Loader(neurun::graph::Graph &graph) : _graph(graph){};
~Loader() = default;
/**
* @brief Load a model from file
*
* @param file_path
*/
void loadFromFile(const char *file_path);
/**
* @brief Load a model from buffer
*
* @param ref Pointers on begin and end of buffer
*/
void loadFromBuffer(std::pair<const char *, const char *> ref);
private:
void loadModel();
// Helper functions
// Load subgraphs
void loadSubgraph(const tflite::SubGraph *subgraph);
// Load data from buffer to tensor on index
void loadConstantTensor(const tflite::Buffer *buffer, const uint32_t &index);
// Create operands form tflite::Tensor
void loadOperand(const tflite::Tensor *tensor);
// Create operations from tflite::Operator
void loadOperation(const tflite::Operator *op);
// Load Strides and Paddings from options to param
template <typename Param, typename OptionsType>
void loadStridesAndPaddings(Param ¶m, const OptionsType *options);
// Load Pool2D param
template <typename Param> void loadPool2D(Param ¶m, const tflite::Pool2DOptions *options);
// Create new Operand from Shape and TypeInfo
template <typename T>
neurun::model::OperandIndex createOperand(const uint8_t *ptr, const neurun::model::Shape &shape,
const neurun::model::TypeInfo &type_info);
// Operations
void loadConv2D(const tflite::Operator *op);
void loadDepthwiseConv2D(const tflite::Operator *op);
void loadTransposeConv(const tflite::Operator *op);
void loadAvgPool2D(const tflite::Operator *op);
void loadReshape(const tflite::Operator *op);
void loadSoftmax(const tflite::Operator *op);
void loadMaxPool2D(const tflite::Operator *op);
void loadConcatenation(const tflite::Operator *op);
void loadFC(const tflite::Operator *op);
void loadAdd(const tflite::Operator *op);
void loadSub(const tflite::Operator *op);
void loadMul(const tflite::Operator *op);
void loadDiv(const tflite::Operator *op);
void loadRelu(const tflite::Operator *op);
void loadRelu6(const tflite::Operator *op);
void loadRsqrt(const tflite::Operator *op);
void loadSqrt(const tflite::Operator *op);
void loadSquaredDifference(const tflite::Operator *op);
void loadTanh(const tflite::Operator *op);
void loadTranspose(const tflite::Operator *op);
void loadMean(const tflite::Operator *op);
void loadCustom(const tflite::Operator *op);
private:
// Buffer for loading (if needed)
std::vector<char> _buffer;
// Reference on loadable Graph
neurun::graph::Graph &_graph;
// Mapping from tflite tensor index to Graph OperandIndex
std::map<uint32_t, neurun::model::OperandIndex> _tensor_to_operand;
// Mapping from operator code to BuiltinOperator
std::vector<tflite::BuiltinOperator> _op_code_to_builtin_op;
std::unordered_map<uint32_t, std::string> _opcode_index_to_custom_opcode;
};
} // namespace tflite_loader
#endif //__TFLITE_LOADER_LOADER_H__
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