In Tensorflow dataset api: How to use padded_batch so that a pads with a specific value without specifying the number of pads

Question

If you don\'t specify a padding_values then padded_batch will autopad with 0. However, if you want a different value such as -1, you can\'t just se

Answer 1

You should change padding_values.

dataset = dataset.padded_batch(2, padded_shapes=([None],[None])
                               , padding_values=(tf.constant(-1, dtype=tf.int64)
                                                 ,tf.constant(-1, dtype=tf.int64)))
with tf.Session() as sess:
    print(sess.run([i, data]))
    print(sess.run([i, data]))

[array([[0],
       [2]]), array([[ 0,  1,  2,  3],
       [ 2,  3,  4, -1]])]
[array([[3],
       [9]]), array([[ 3,  6,  5,  4,  3],
       [ 3,  9, -1, -1, -1]])]

Explain

Every entry given in padding_values represents the padding values to use for the respective components. This means that the length of padded_shapes should be equal to the length of padding_values. The latter is used for padding the entire length for every array in here,and the former has the same length and does not need padding -1.For example:

dataset = dataset.padded_batch(2, padded_shapes=([None],[None])
                               , padding_values=(tf.constant(-1, dtype=tf.int64)
                                                 ,tf.constant(-2, dtype=tf.int64)))
with tf.Session() as sess:
    print(sess.run([i, data]))
    print(sess.run([i, data]))

[array([[0],
       [2]]), array([[ 0,  1,  2,  3],
       [ 2,  3,  4, -2]])]
[array([[3],
       [9]]), array([[ 3,  6,  5,  4,  3],
       [ 3,  9, -2, -2, -2]])]