code: def TestOneInput(input_bytes):
      """Test randomized integer fuzzing input for tf.raw_ops.DataFormatVecPermute."""
      fh = FuzzingHelper(input_bytes)
  
      dtype = fh.get_tf_dtype()
      # Max shape can be 8 in length and randomized from 0-8 without running into
      # a OOM error.
      shape = fh.get_int_list(
          min_length=0, max_length=8, min_int=0, max_int=8
      )
      seed = fh.get_int()
      try:
          x = tf.random.uniform(shape=shape, dtype=dtype, seed=seed)
          src_format_digits = str(
              fh.get_int(min_int=0, max_int=999999999)
          )
          dest_format_digits = str(
              fh.get_int(min_int=0, max_int=999999999)
          )
          _ = tf.raw_ops.DataFormatVecPermute(
              x,
              src_format=src_format_digits,
              dst_format=dest_format_digits,
              name=fh.get_string(),
          )
      except (tf.errors.InvalidArgumentError, ValueError, TypeError):
          pass
  
label_desc: Use image node_id 1 for calling a global function with example usage: TestOneInput(input_bytes) without return types