()
return output_dir
Returns a path to the output directory.
Returns a path to the output directory.
Returns a path to the output directory .
def _output_dir_or_default():
  """Returns a path to the output directory."""
  if FLAGS.output_dir:
    output_dir = FLAGS.output_dir
    trainer_lib.log('Using --output_dir {}'.format(output_dir))
    return os.path.expanduser(output_dir)

  # Else, generate a default output dir (under the user's home directory).
  try:
    dataset_name = gin.query_parameter('data_streams.dataset_name')
  except ValueError:
    dataset_name = 'random'
  output_name = '{model_name}_{dataset_name}_{timestamp}'.format(
      model_name=gin.query_parameter('train.model').configurable.name,
      dataset_name=dataset_name,
      timestamp=datetime.datetime.now().strftime('%Y%m%d_%H%M'),
  )
  output_dir = os.path.join('~', 'trax', output_name)
  output_dir = os.path.expanduser(output_dir)
  print()
  trainer_lib.log('No --output_dir specified')
  trainer_lib.log('Using default output_dir: {}'.format(output_dir))
  return output_dir
def _output_dir_or_default ( ) : if FLAGS . output_dir : output_dir = FLAGS . output_dir trainer_lib . log ( 'Using --output_dir {}' . format ( output_dir ) ) return os . path . expanduser ( output_dir ) # Else, generate a default output dir (under the user's home directory). try : dataset_name = gin . query_parameter ( 'data_streams.dataset_name' ) except ValueError : dataset_name = 'random' output_name = '{model_name}_{dataset_name}_{timestamp}' . format ( model_name = gin . query_parameter ( 'train.model' ) . configurable . name , dataset_name = dataset_name , timestamp = datetime . datetime . now ( ) . strftime ( '%Y%m%d_%H%M' ) , ) output_dir = os . path . join ( '~' , 'trax' , output_name ) output_dir = os . path . expanduser ( output_dir ) print ( ) trainer_lib . log ( 'No --output_dir specified' ) trainer_lib . log ( 'Using default output_dir: {}' . format ( output_dir ) ) return output_dir