Function cook_graph

compiler/circlechef/core/src/ModelChef.cpp:219–519

};

template <typename T> void cook_graph(const T &graph, CookParams &cp)
{
  LOGGER(l);

  std::vector<flatbuffers::Offset<::circle::Buffer>> &buffer_vec = cp.buffer_vec;
  std::vector<flatbuffers::Offset<::circle::OperatorCode>> &code_vec = cp.code_vec;
  std::vector<flatbuffers::Offset<::circle::SubGraph>> &subgraph_vec = cp.subgraph_vec;
  std::unique_ptr<flatbuffers::FlatBufferBuilder> &flatbuffer_builder = cp.flatbuffer_builder;
  std::map<circle::BuiltinOperator, int32_t> &builtin_code_map = cp.builtin_code_map;

  // Operand-related
  std::vector<flatbuffers::Offset<::circle::Tensor>> tensor_vec;

  // Operation-related
  std::vector<flatbuffers::Offset<::circle::Operator>> operator_vec;

  // default name for graph
  std::string graph_name = cp.noname;
  if (graph.has_name())
    graph_name = graph.name();

  // Tensor Name -> Tensor ID mapping (per Graph)
  std::map<std::string, int32_t> symbol_table;

  auto lookup = [&symbol_table, &graph_name](const std::string &name) {
    if (symbol_table.find(name) != symbol_table.end())
      return symbol_table.at(name);
    else if (name == "")
      return -1; // -1 in circle means that optional input tensor is empty.
    else
    {
      std::string msg = "circlechef : input not found in " + graph_name + " graph";
      throw std::runtime_error(msg.c_str());
    }
  };

  int32_t buffer_start = buffer_vec.size();
  int32_t buffer_index = 0;

  // Create buffer(s) 1~n(I) for input(s)
  const auto size_input = graph.input_size();
  for (int ci = 0; ci < size_input; ++ci)
  {
    circle::BufferBuilder buffer_builder{*flatbuffer_builder};
    buffer_vec.emplace_back(buffer_builder.Finish());
  }
  // Create buffer(s) n(I)+1~n(I)+n(O) for output(s)
  const auto size_output = graph.output_size();
  for (int co = 0; co < size_output; ++co)
  {
    circle::BufferBuilder buffer_builder{*flatbuffer_builder};
    buffer_vec.emplace_back(buffer_builder.Finish());
  }

  auto input_names = as_dataset(graph.input()).vectorize();
  auto output_names = as_dataset(graph.output()).vectorize();

  for (const auto &operand : graph.operand())