(self, split)
return ds.prefetch(tf.contrib.data.AUTOTUNE)
Loads the underlying dataset split from disk.

    Args:
      split: Name of the split to load.

    Returns:
      Returns a `tf.data.Dataset` object with a tuple of image and label tensor.
Loads the underlying dataset split from disk.
Loads the underlying dataset split from disk .
def _load_dataset(self, split):
    """Loads the underlying dataset split from disk.

    Args:
      split: Name of the split to load.

    Returns:
      Returns a `tf.data.Dataset` object with a tuple of image and label tensor.
    """
    if FLAGS.data_fake_dataset:
      return self._make_fake_dataset(split)
    ds = tfds.load(
        self._tfds_name,
        split=split,
        data_dir=FLAGS.tfds_data_dir,
        as_dataset_kwargs={"shuffle_files": False})
    ds = self._replace_labels(split, ds)
    ds = ds.map(self._parse_fn)
    return ds.prefetch(tf.contrib.data.AUTOTUNE)
def _load_dataset ( self , split ) : if FLAGS . data_fake_dataset : return self . _make_fake_dataset ( split ) ds = tfds . load ( self . _tfds_name , split = split , data_dir = FLAGS . tfds_data_dir , as_dataset_kwargs = { "shuffle_files" : False } ) ds = self . _replace_labels ( split , ds ) ds = ds . map ( self . _parse_fn ) return ds . prefetch ( tf . contrib . data . AUTOTUNE )