code: def _create_moving_sequence(image, pad_lefts, total_padding):
      """Create a moving image sequence from the given image a left padding values.
  
      Args:
        image: [in_h, in_w, n_channels] uint8 array
        pad_lefts: [sequence_length, 2] int32 array of left padding values
        total_padding: tensor of padding values, (pad_h, pad_w)
  
      Returns:
        [sequence_length, out_h, out_w, n_channels] uint8 image sequence, where
          out_h = in_h + pad_h, out_w = in_w + out_w
      """
  
      with tf.name_scope("moving_sequence"):
  
          def get_padded_image(args):
              (pad_left,) = args
              pad_right = total_padding - pad_left
              padding = tf.stack([pad_left, pad_right], axis=-1)
              z = tf.zeros((1, 2), dtype=pad_left.dtype)
              padding = tf.concat([padding, z], axis=0)
              return tf.pad(image, padding)
  
          padded_images = tf.map_fn(
              get_padded_image,
              [pad_lefts],
              dtype=tf.uint8,
              infer_shape=False,
          )
  
      return padded_images
  
imports: import collections
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: _create_moving_sequence(image, pad_lefts, total_padding) and returns: padded_images, tf