def _pad_tensors_to_same_length(x, y):
    'Pad x and y so that the results have the same length (second dimension).'
    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)
Pad x and y so that the results have the same length (second dimension).
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)