code: def data_to_tfrecord(images, labels, filename):
      
      if os.path.isfile(filename):
          print("%s exists" % filename)
          return
      print("Converting data into %s ..." % filename)
      # cwd = os.getcwd()
      writer = tf.python_io.TFRecordWriter(filename)
      for index, img in enumerate(images):
          img_raw = img.tobytes()
          # Visualize a image
          # tl.visualize.frame(np.asarray(img, dtype=np.uint8), second=1, saveable=False, name='frame', fig_idx=1236)
          label = int(labels[index])
          # print(label)
          # Convert the bytes back to image as follow:
          # image = Image.frombytes('RGB', (32, 32), img_raw)
          # image = np.fromstring(img_raw, np.float32)
          # image = image.reshape([32, 32, 3])
          # tl.visualize.frame(np.asarray(image, dtype=np.uint8), second=1, saveable=False, name='frame', fig_idx=1236)
          example = tf.train.Example(
              features=tf.train.Features(
                  feature={
                      "label": tf.train.Feature(int64_list=tf.train.Int64List(value=[label])),
                      'img_raw': tf.train.Feature(bytes_list=tf.train.BytesList(value=[img_raw])),
                  }
              )
          )
          writer.write(example.SerializeToString())  # Serialize To String
      writer.close()
docs: Save data into TFRecord.