(config)
Initializes data normalizer.
Initializes data normalizer.
Initializes data normalizer .
def init_data_normalizer(config):
  """Initializes data normalizer."""
  normalizer = data_normalizer.registry[config['data_normalizer']](config)
  if normalizer.exists():
    return

  if config['task'] == 0:
    tf.reset_default_graph()
    data_helper = data_helpers.registry[config['data_type']](config)
    real_images, _ = data_helper.provide_data(batch_size=10)

    # Save normalizer.
    # Note if normalizer has been saved, save() is no-op. To regenerate the
    # normalizer, delete the normalizer file in train_root_dir/assets
    normalizer.save(real_images)
  else:
    while not normalizer.exists():
      time.sleep(5)
def init_data_normalizer ( config ) : normalizer = data_normalizer . registry [ config [ 'data_normalizer' ] ] ( config ) if normalizer . exists ( ) : return if config [ 'task' ] == 0 : tf . reset_default_graph ( ) data_helper = data_helpers . registry [ config [ 'data_type' ] ] ( config ) real_images , _ = data_helper . provide_data ( batch_size = 10 ) # Save normalizer. # Note if normalizer has been saved, save() is no-op. To regenerate the # normalizer, delete the normalizer file in train_root_dir/assets normalizer . save ( real_images ) else : while not normalizer . exists ( ) : time . sleep ( 5 )