(**kwargs)
return list(range(start_stage_id, get_total_num_stages(**kwargs)))
Returns a list of stage ids.

  Args:
    **kwargs: A dictionary of
        'train_root_dir': A string of root directory of training logs.
        'num_resolutions': An integer of number of progressive resolutions.
Returns a list of stage ids.
Returns a list of stage ids .
def get_stage_ids(**kwargs):
  """Returns a list of stage ids.

  Args:
    **kwargs: A dictionary of
        'train_root_dir': A string of root directory of training logs.
        'num_resolutions': An integer of number of progressive resolutions.
  """
  train_sub_dirs = [
      sub_dir for sub_dir in tf.gfile.ListDirectory(kwargs['train_root_dir'])
      if sub_dir.startswith('stage_')
  ]

  # If fresh start, start with start_stage_id = 0
  # If has been trained for n = len(train_sub_dirs) stages, start with the last
  # stage, i.e. start_stage_id = n - 1.
  start_stage_id = max(0, len(train_sub_dirs) - 1)

  return list(range(start_stage_id, get_total_num_stages(**kwargs)))
def get_stage_ids ( * * kwargs ) : train_sub_dirs = [ sub_dir for sub_dir in tf . gfile . ListDirectory ( kwargs [ 'train_root_dir' ] ) if sub_dir . startswith ( 'stage_' ) ] # If fresh start, start with start_stage_id = 0 # If has been trained for n = len(train_sub_dirs) stages, start with the last # stage, i.e. start_stage_id = n - 1. start_stage_id = max ( 0 , len ( train_sub_dirs ) - 1 ) return list ( range ( start_stage_id , get_total_num_stages ( * * kwargs ) ) )