code: def _pad_tensors_to_same_length(x, y):
    
    with tf.name_scope("pad_to_same_length"):
      x_length = tf.shape(x)[1]
      y_length = tf.shape(y)[1]
  
      max_length = tf.maximum(x_length, y_length)
  
      x = tf.pad(x, [[0, 0], [0, max_length - x_length], [0, 0]])
      y = tf.pad(y, [[0, 0], [0, max_length - y_length]])
      return x, y
docs: Pad x and y so that the results have the same length (second dimension).