code: def main(_):
      """The entrypoint."""
  
      config = _process_config()
  
      run_config = _get_run_config(config)
  
      kwargs = {
          "data_hparams": config["data_hparams_train"],
          "hparams": config["model_hparams"],
      }
      model = utils.check_or_get_instance_with_redundant_kwargs(
          config["model"],
          kwargs=kwargs,
          module_paths=["texar.tf.models", "texar.tf.custom"],
      )
  
      data_hparams = {
          "train": config["data_hparams_train"],
          "eval": config["data_hparams_eval"],
      }
  
      exor = Executor(
          model=model, data_hparams=data_hparams, config=run_config
      )
  
      exor.train_and_evaluate(
          max_train_steps=config["max_train_steps"],
          eval_steps=config["eval_steps"],
      )
  
file_path: texar/bin/train.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import tempfile
  import yaml
  import tensorflow
  from texar.tf import utils
  from texar.tf.run import Executor
label_desc: Use image node_id 3 for calling a global function with example usage: main(_) without return types