False,
        bazel_config_name='tensorrt')

    environ_save = dict(environ_cp)
    for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):

      if validate_cuda_config(environ_cp):
        cuda_env_names = [
            'TF_CUDA_VERSION',
            'TF_CUBLAS_VERSION',
            'TF_CUDNN_VERSION',
            'TF_TENSORRT_VERSION',
            'TF_NCCL_VERSION',
            'TF_CUDA_PATHS',

  // Process output names.
  std::vector<string> output_names_vec;
  if (output_names) {
    output_names_vec.reserve(noutputs);
    for (int i = 0; i < noutputs; ++i) {
      output_names_vec.push_back(string(output_names[i]));
    }
  }

  // Process control output names.
  std::vector<string> control_output_names_vec;
  if (control_output_names) {

            underlying_devices_[component_index], underlying_devices_[0])) {
      // Device names are from different address spaces, or we can't figure out
      // whether they are, so we'll fully-qualify everything.
      return underlying_devices_;
    }
  }
  std::vector<std::string> local_names;
  local_names.reserve(underlying_devices_.size());
  for (const DeviceNameUtils::ParsedName& parsed_component :

                         std::unique_ptr<tensorflow::Graph>* graph,
                         tensorflow::FunctionLibraryDefinition* flib_def,
                         std::vector<std::string>* control_ret_node_names,
                         bool* control_rets_updated) override {
    // Inject failure to function instantiation if finding a node that contains
    // the given node name (error_node_) and requested device (error_device_).