code: def train(model, **kwargs):
      """Trains progressive GAN for stage `stage_id`.
  
      Args:
        model: An model object having all information of progressive GAN model,
            e.g. the return of build_model().
        **kwargs: A dictionary of
            'train_root_dir': A string of root directory of training logs.
            'master': Name of the TensorFlow master to use.
            'task': The Task ID. This value is used when training with multiple
                workers to identify each worker.
            'save_summaries_num_images': Save summaries in this number of images.
            'debug_hook': Whether to attach the debug hook to the training session.
      Returns:
        None.
      """
      logging.info(
          "stage_id=%d, num_blocks=%d, num_images=%d",
          model.stage_id,
          model.num_blocks,
          model.num_images,
      )
  
      scaffold = make_scaffold(
          model.stage_id, model.optimizer_var_list, **kwargs
      )
  
      logdir = make_train_sub_dir(model.stage_id, **kwargs)
      print("starting training, logdir: {}".format(logdir))
      hooks = []
      if model.stage_train_time_limit is None:
          hooks.append(
              tf.train.StopAtStepHook(last_step=model.num_images)
          )
      hooks.append(
          tf.train.LoggingTensorHook(
              [make_status_message(model)], every_n_iter=1
          )
      )
      hooks.append(
          TrainTimeHook(model.train_time, model.stage_train_time_limit)
      )
      if kwargs["debug_hook"]:
          hooks.append(ProganDebugHook())
      tfgan.gan_train(
          model.gan_train_ops,
          logdir=logdir,
          get_hooks_fn=tfgan.get_sequential_train_hooks(
              tfgan.GANTrainSteps(1, 1)
          ),
          hooks=hooks,
          master=kwargs["master"],
          is_chief=(kwargs["task"] == 0),
          scaffold=scaffold,
          save_checkpoint_secs=600,
          save_summaries_steps=(kwargs["save_summaries_num_images"]),
      )
  
imports: import os
  import time
  from absl import logging
  from magenta.models.gansynth.lib import networks
  import numpy
  import tensorflow.compat.v1
  import tensorflow_gan
label_desc: Use image node_id 16 for calling a global function with example usage: train(model) without return types