docs: def get_padding(x, padding_value=0):
    """Return float tensor representing the padding values in x.
  
    Args:
      x: int tensor with any shape
      padding_value: int value that
  
    Returns:
      flaot tensor with same shape as x containing values 0 or 1.
        0 -> non-padding, 1 -> padding
    """
    with tf.name_scope("padding"):
      return tf.to_float(tf.equal(x, padding_value))