Method FlattenInputs

tensorflow/python/framework/python_op_gen.cc:187–233

}

string GenEagerPythonOp::FlattenInputs(
    const std::vector<int>* input_indices,
    std::vector<string>* output_sizes) const {
  string inputs;
  enum { STARTING, WAS_LIST_INPUT, WAS_SOLO_INPUT } inputs_state = STARTING;
  const int n = input_indices != nullptr ? input_indices->size()
                                         : op_def_.input_arg_size();
  for (int j = 0; j < n; ++j) {
    const int i = input_indices ? (*input_indices)[j] : j;
    const auto& arg(op_def_.input_arg(i));
    const bool is_list =
        !arg.type_list_attr().empty() || !arg.number_attr().empty();
    if (is_list) {
      if (inputs_state == WAS_SOLO_INPUT) {
        strings::StrAppend(&inputs, "] + ");
      } else if (inputs_state == WAS_LIST_INPUT) {
        strings::StrAppend(&inputs, " + ");
      }
      strings::StrAppend(&inputs, "list(", param_names_[i].GetRenameTo(), ")");
      inputs_state = WAS_LIST_INPUT;
      if (output_sizes != nullptr) {
        if (!arg.number_attr().empty()) {
          output_sizes->emplace_back(AttrVarName(arg.number_attr(), nullptr));
        } else {
          output_sizes->emplace_back(
              strings::StrCat("len(", param_names_[i].GetRenameTo(), ")"));
        }
      }
    } else {
      if (inputs_state == WAS_SOLO_INPUT) {
        strings::StrAppend(&inputs, ", ");
      } else if (inputs_state == WAS_LIST_INPUT) {
        strings::StrAppend(&inputs, " + [");
      } else {
        strings::StrAppend(&inputs, "[");
      }
      strings::StrAppend(&inputs, param_names_[i].GetRenameTo());
      inputs_state = WAS_SOLO_INPUT;
      if (output_sizes != nullptr) output_sizes->emplace_back();
    }
  }
  if (inputs_state == STARTING) return "[]";
  if (inputs_state == WAS_SOLO_INPUT) {
    strings::StrAppend(&inputs, "]");
  }
  return inputs;
}

string GenEagerPythonOp::Code() {
  if (api_def_.visibility() == ApiDef::SKIP) {