code: def main(_):
      tf.gfile.MakeDirs(FLAGS.data_dir)
      tf.gfile.MakeDirs(FLAGS.tmp_dir)
  
      # Create problem if not already defined
      problem_name = (
          "gym_discrete_problem_with_agent_on_%s" % FLAGS.game
      )
      if problem_name not in registry.Registries.problems:
          gym_env.register_game(FLAGS.game)
  
      # Generate
      tf.logging.info(
          "Running %s environment for %d steps for trajectories.",
          FLAGS.game,
          FLAGS.num_env_steps,
      )
      problem = registry.problem(problem_name)
      problem.settable_num_steps = FLAGS.num_env_steps
      problem.settable_eval_phase = FLAGS.eval
      problem.generate_data(FLAGS.data_dir, FLAGS.tmp_dir)
  
      # Log stats
      if problem.statistics.number_of_dones:
          mean_reward = (
              problem.statistics.sum_of_rewards
              / problem.statistics.number_of_dones
          )
          tf.logging.info(
              "Mean reward: %.2f, Num dones: %d",
              mean_reward,
              problem.statistics.number_of_dones,
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.data_generators import gym_env
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: main(_) without return types