code: def _build_mask_ds(mask, mask_offset):
    
    mask_ds = tf.data.Dataset.from_tensor_slices(mask)
    mask_ds = mask_ds.repeat()
    mask_ds = mask_ds.skip(mask_offset)
    return mask_ds
docs: Build the mask dataset to indicate which element to skip.
  
    Args:
      mask: `tf.Tensor`, binary mask to apply to all following elements. This
        mask should have a length 100.
      mask_offset: `tf.Tensor`, Integer specifying from how much the mask
        should be shifted for the first element.
  
    Returns:
      mask_ds: `tf.data.Dataset`, a dataset returning False for examples to skip
        and True for examples to keep.