Saves FLAGS and hparams to output_dir.

def save_metadata(hparams):
  """Saves FLAGS and hparams to output_dir."""
  output_dir = os.path.expanduser(FLAGS.output_dir)
  if not tf.gfile.Exists(output_dir):
    tf.gfile.MakeDirs(output_dir)

  # Save FLAGS in txt file
  if hasattr(FLAGS, "flags_into_string"):
    flags_str = FLAGS.flags_into_string()
    t2t_flags_str = "\n".join([
        "--%s=%s" % (f.name, f.value)
        for f in FLAGS.flags_by_module_dict()["tensor2tensor.utils.flags"]
    ])
  else:
    flags_dict = FLAGS.__dict__["__flags"]
    flags_str = "\n".join(
        ["--%s=%s" % (name, str(f)) for (name, f) in flags_dict.items()])
    t2t_flags_str = None

  flags_txt = os.path.join(output_dir, "flags.txt")
  with tf.gfile.Open(flags_txt, "w") as f:
    f.write(flags_str)

  if t2t_flags_str:
    t2t_flags_txt = os.path.join(output_dir, "flags_t2t.txt")
    with tf.gfile.Open(t2t_flags_txt, "w") as f:
      f.write(t2t_flags_str)

  # Save hparams as hparams.json
  new_hparams = hparams_lib.copy_hparams(hparams)
  # Modality class is not JSON serializable so remove.
  new_hparams.del_hparam("modality")

  hparams_fname = os.path.join(output_dir, "hparams.json")
  with tf.gfile.Open(hparams_fname, "w") as f:
    f.write(new_hparams.to_json(indent=0, sort_keys=True))