Run the reinforcement learning loop.

def main(unused_argv):
  """Run the reinforcement learning loop."""

  print('Wiping dir %s' % FLAGS.base_dir, flush=True)
  shutil.rmtree(FLAGS.base_dir, ignore_errors=True)
  dirs = [fsdb.models_dir(), fsdb.selfplay_dir(), fsdb.holdout_dir(),
          fsdb.eval_dir(), fsdb.golden_chunk_dir(), fsdb.working_dir()]
  for d in dirs:
    ensure_dir_exists(d);

  # Copy the flag files so there's no chance of them getting accidentally
  # overwritten while the RL loop is running.
  flags_dir = os.path.join(FLAGS.base_dir, 'flags')
  shutil.copytree(FLAGS.flags_dir, flags_dir)
  FLAGS.flags_dir = flags_dir

  # Copy the target model to the models directory so we can find it easily.
  shutil.copy(FLAGS.target_path, os.path.join(fsdb.models_dir(), 'target.pb'))

  logging.getLogger().addHandler(
      logging.FileHandler(os.path.join(FLAGS.base_dir, 'rl_loop.log')))
  formatter = logging.Formatter('[%(asctime)s] %(message)s',
                                '%Y-%m-%d %H:%M:%S')
  for handler in logging.getLogger().handlers:
    handler.setFormatter(formatter)

  with logged_timer('Total time'):
    try:
      rl_loop()
    finally:
      asyncio.get_event_loop().close()