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) {
    control_output_names_vec.reserve(ncontrol_outputs);

      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =
        TF_NewShapeAndTypeList(input_shapes_vec.size());
    for (size_t i = 0; i < input_shapes_vec.size(); ++i) {
      const auto& input_shape = input_shapes_vec[i];
      if (input_shape.has_value()) {

  }
  std::vector<tensorflow::CoordinatedTask> task_vec(tasks.length);
  auto* task_iter = static_cast<const tensorflow::CoordinatedTask*>(tasks.data);
  for (size_t i = 0; i < tasks.length; ++i) {
    task_vec[i].set_job_name(task_iter->job_name());
    task_vec[i].set_task_id(task_iter->task_id());
    ++task_iter;
  }
  auto results = coord_agent->GetTaskState(task_vec);
  if (!results.ok()) {

   1EB2; 1EB3; Case map
   1EB4; 1EB5; Case map
   1EB6; 1EB7; Case map
   1EB8; 1EB9; Case map
   1EBA; 1EBB; Case map
   1EBC; 1EBD; Case map
   1EBE; 1EBF; Case map
   1EC0; 1EC1; Case map
   1EC2; 1EC3; Case map
   1EC4; 1EC5; Case map
   1EC6; 1EC7; Case map
   1EC8; 1EC9; Case map
   1ECA; 1ECB; Case map
   1ECC; 1ECD; Case map
   1ECE; 1ECF; Case map
   1ED0; 1ED1; Case map
   1ED2; 1ED3; Case map