code: def _get_global_variable_names(name, tuple_path):
      """Get the global variables names for ground truth.
  
      Args:
        name: Python `str`. Name of the sample transformation.
        tuple_path: Tuple path of the part of the ground truth we're saving. See
          `nest.flatten_with_tuple_paths`.
  
      Returns:
        mean_name: Variable name to use for the mean.
        sem_name: Variable name to use for the standard error of the mean.
        std_name: Variable name to use for the standard deviation.
        sestd_name: Variable name to use for the standard deviation standard error.
      """
      if tuple_path:
          path_suffix = "_" + "_".join(
              str(p).upper() for p in tuple_path
          )
      else:
          path_suffix = ""
  
      upper_name = name.upper()
      mean_name = "{}{}_MEAN".format(upper_name, path_suffix)
      sem_name = "{}{}_MEAN_STANDARD_ERROR".format(
          upper_name, path_suffix
      )
      std_name = "{}{}_STANDARD_DEVIATION".format(
          upper_name, path_suffix
      )
      sestd_name = "{}{}_STANDARD_DEVIATION_STANDARD_ERROR".format(
          upper_name, path_suffix
      )
  
      return mean_name, sem_name, std_name, sestd_name
  
imports: from inference_gym.internal import array_to_source
label_desc: Use image node_id 1 for calling a global function with example usage: _get_global_variable_names(name, tuple_path) and returns: mean_name,  sem_name,  std_name,  sestd_name