code: def _output_dir_or_default():
      """Returns a path to the output directory."""
      if FLAGS.output_dir:
          output_dir = FLAGS.output_dir
          trainer_lib.log("Using --output_dir {}".format(output_dir))
          return os.path.expanduser(output_dir)
  
      # Else, generate a default output dir (under the user's home directory).
      try:
          dataset_name = gin.query_parameter(
              "data_streams.dataset_name"
          )
      except ValueError:
          dataset_name = "random"
      output_name = "{model_name}_{dataset_name}_{timestamp}".format(
          model_name=gin.query_parameter(
              "train.model"
          ).configurable.name,
          dataset_name=dataset_name,
          timestamp=datetime.datetime.now().strftime("%Y%m%d_%H%M"),
      )
      output_dir = os.path.join("~", "trax", output_name)
      output_dir = os.path.expanduser(output_dir)
      print()
      trainer_lib.log("No --output_dir specified")
      trainer_lib.log("Using default output_dir: {}".format(output_dir))
      return output_dir
  
imports: import atexit
  import datetime
  import functools
  import os
  from absl import app
  from absl import flags
  from absl import logging
  import gin
  import jax
  from jax.lib import xla_extension
  import tensorflow.compat.v2
  from trax import fastmath
  from trax import trainer_flags
  from trax.supervised import trainer_lib
  from trax.tf_numpy import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: _output_dir_or_default() and returns: output_dir, os