ocr.py 文件源码

def create_ctc_loss(logits, labels, timesteps, label_seq_lengths):
  with tf.variable_scope('CTC_Loss'):
    print()
    print("Labels shape")
    print(labels)
    print()
    print("Logits shape")
    print(logits)
    print()
    print("Labels len  shape")
    print(label_seq_lengths)

    # logits = tf.Print(logits, [logits], "Logits")
    ctc_loss = tf.nn.ctc_loss(labels, 
                   logits, 
                   timesteps)

    cost = tf.reduce_mean(ctc_loss, name='ctc')

    # The total loss is defined as the cross entropy loss plus all of the weight
    # decay terms (L2 loss).
    return cost