Driver.cpp File Reference

#include "tflchef/ModelChef.h"
#include <google/protobuf/io/coded_stream.h>
#include <google/protobuf/io/zero_copy_stream_impl.h>
#include <google/protobuf/text_format.h>
#include <arser/arser.h>
#include <fstream>
#include <iostream>

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Functions
int	entry (int argc, char **argv)
	Dump IR for given arguments.

Function Documentation

entry()

int entry	(	int	argc,
		char **	argv
	)

Dump IR for given arguments.

Call example: $ ./build/compiler/encodump/encodump \ –frontend build/compiler/enco/frontend/caffe/libenco_caffe_frontend.so \ –frontend-arg build/compiler/enco/test/caffe/Convolution_003.prototxt \ –frontend-arg build/compiler/enco/test/caffe/Convolution_003.caffemodel

HDF5 layout is like below

GROUP "/" ㄴGROUP "name" ㄴATTRIBUTE "0" ㄴDATA (0): "input_01:0" ㄴATTRIBUTE "1" ㄴDATA (0): "input_02:0" ㄴGROUP "value" ㄴDATASET "0" ㄴDATA ... ㄴDATASET "1" ㄴDATA ...

Definition at line 28 of file Driver.cpp.

{
  arser::Arser arser;
  arser.add_argument("recipe").help("Source recipe file path to convert");
  arser.add_argument("tflite").help("Target tflite file path");
 
  try
  {
    arser.parse(argc, argv);
  }
  catch (const std::runtime_error &err)
  {
    std::cout << err.what() << std::endl;
    std::cout << arser;
    return 255;
  }
 
  int32_t model_version = 1;
 
  ::tflchef::ModelRecipe model_recipe;
 
  std::string recipe_path = arser.get<std::string>("recipe");
  // Load model recipe from a file
  {
    std::ifstream is{recipe_path};
    google::protobuf::io::IstreamInputStream iis{&is};
    if (!google::protobuf::TextFormat::Parse(&iis, &model_recipe))
    {
      std::cerr << "ERROR: Failed to parse recipe '" << recipe_path << "'" << std::endl;
      return 255;
    }
 
    if (model_recipe.has_version())
    {
      model_version = model_recipe.version();
    }
  }
 
  if (model_version > 1)
  {
    std::cerr << "ERROR: Unsupported recipe version: " << model_version << ", '" << recipe_path
              << "'" << std::endl;
    return 255;
  }
 
  auto generated_model = tflchef::cook(model_recipe);
 
  std::string tflite_path = arser.get<std::string>("tflite");
  // Dump generated model into a file
  {
    std::ofstream os{tflite_path, std::ios::binary};
    os.write(generated_model.base(), generated_model.size());
  }
 
  return 0;
}

References tflchef::cook().