code: def main(unused_argv):
      absl.flags.FLAGS.alsologtostderr = True
      # Set hyperparams from json args and defaults
      flags = lib_flags.Flags()
      # Config hparams
      if FLAGS.config:
          config_module = importlib.import_module(
              "magenta.models.gansynth.configs.{}".format(FLAGS.config)
          )
          flags.load(config_module.hparams)
      # Command line hparams
      flags.load_json(FLAGS.hparams)
      # Set default flags
      lib_model.set_flags(flags)
  
      print("Flags:")
      flags.print_values()
  
      # Create training directory
      flags["train_root_dir"] = util.expand_path(
          flags["train_root_dir"]
      )
      if not tf.gfile.Exists(flags["train_root_dir"]):
          tf.gfile.MakeDirs(flags["train_root_dir"])
  
      # Save the flags to help with loading the model latter
      fname = os.path.join(flags["train_root_dir"], "experiment.json")
      with tf.gfile.Open(fname, "w") as f:
          json.dump(flags, f)  # pytype: disable=wrong-arg-types
  
      # Run training
      run(flags)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import importlib
  import json
  import os
  import time
  from absl import logging
  import absl.flags
  from magenta.models.gansynth.lib import data_helpers
  from magenta.models.gansynth.lib import data_normalizer
  from magenta.models.gansynth.lib import flags
  from magenta.models.gansynth.lib import model
  from magenta.models.gansynth.lib import train_util
  from magenta.models.gansynth.lib import util
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: main(unused_argv) without return types