CTCLossExactPathTest.py

import numpy as np
import tensorflow as tf

def CTCLossExactPathTest():
  
    BIG_NEG_NUMBER = -100
    logit = np.array([[BIG_NEG_NUMBER, 0., BIG_NEG_NUMBER, BIG_NEG_NUMBER],
                      [0., BIG_NEG_NUMBER, BIG_NEG_NUMBER, BIG_NEG_NUMBER],
                      [BIG_NEG_NUMBER, BIG_NEG_NUMBER, 0., BIG_NEG_NUMBER]])
    """
    Take softmax will give us:
    softmax = [[0., 1., 0., 0.],
               [1., 0., 0., 0.],
               [0., 0., 1., 0.]]
    """
    
    logit = tf.constant(logit, dtype='float32')
    # label = [1, 0, 2]
#     target = tf.SparseTensor(indices=[[0, 0], [0, 2]], values=[1, 2], dense_shape=[1, 3])  # this line gave error!
    target = tf.SparseTensor(indices=[[0, 0], [0, 1], [0, 2]], values=[1, 0, 2], dense_shape=[1, 3])

    seq = tf.constant(np.array([3]), dtype='int32')
    logit = tf.expand_dims(logit, axis=1)

    # CTC loss
    loss = tf.nn.ctc_loss(target, logit, seq)

    # run session
    with tf.Session() as sess:
        prob = sess.run([loss])
        print('Tensorflow CTC calculated negative log prob = %.4f' % prob[0])
        
    # neg log probability should give us 0.
    assert prob[0] == 0.

CTCLossExactPathTest()