f4bb1de2fe46de99c03dba0b9c76685a998b4276,preprocessing.py,,get_input_tensors,#Any#Any#Any#Any#Any#Any#Any#Any#,183

Before Change

    dataset = dataset.map(
        functools.partial(batch_parse_tf_example, batch_size))
    if random_rotation:
        dataset = dataset.map(_random_rotation_pyfunc)

    return dataset.make_one_shot_iterator().get_next()

After Change

    if random_rotation:
        // Unbatch the dataset so we can rotate it
        dataset = dataset.apply(tf.data.experimental.unbatch())
        dataset = dataset.apply(tf.data.experimental.map_and_batch(
            _random_rotation, batch_size))

    return dataset.make_one_shot_iterator().get_next()

Instances