1. # Create input data
    2.     with tf.device("/cpu:0"):
    3.         train_glob = os.path.join(RECORDS_ROOT, "train/*/*.JPEG")
    4.         train_files = glob.glob(train_glob)
    5.         if not train_files:
    6.             raise RuntimeError(
    7.                 "No training images found with glob '{}'.".format(train_glob))
    8.         train_dataset = tf.data.Dataset.from_tensor_slices(train_files)
    9.         train_dataset = train_dataset.shuffle(buffer_size=len(train_files)).repeat()
    10.         train_dataset = train_dataset.map(
    11.             read_png, num_parallel_calls=configs.dataset.NUM_PREPROCESS_THREADS)
    12.         train_dataset = train_dataset.map(
    13.             lambda x: tf.random_crop(x, (configs.dataset.crop_size[0], configs.dataset.crop_size[1], 3)))
    14.         train_dataset = train_dataset.batch(configs.dataset.batch_size)
    15.         train_dataset = train_dataset.prefetch(32)
    17.     num_pixels = configs.dataset.batch_size * configs.dataset.crop_size[0] * configs.dataset.crop_size[1]
    19.     # Get training patch from dataset
    20.     x = train_dataset.make_one_shot_iterator().get_next()

    Tensorflow: 1.14.0