Keras accuracy metric for sequence predicting with padding

train.py

"""
Description:
When we handle the word sequence predicting problem on Keras, we add paddings at the last of blank space.
But this makes wrong calculation at Keras default accuracy function. (It calculate the padding as correct too). 

To solved that problem, I made new custom function for word sequence predicting problem.
It isn't calculate accuracy of the padding section, only calculate at actual word part

Junseong Kim, codertimo@gmail.com
"""

"""
New Accuracy Function for padding sequence
"""
import keras.backend as K
def word_acc(y_true, y_pred):
    a = K.argmax(y_pred, axis=-1)
    b = K.tf.reduce_max(y_true, axis=-1)
    b = K.tf.cast(b, K.tf.int64)
    
    total_index = K.tf.count_nonzero(a+b, 1)
    wrong_index = K.tf.count_nonzero(a-b, 1)

    total_index = K.tf.reduce_sum(total_index)
    wrong_index = K.tf.reduce_sum(wrong_index)
    
    correct_index = K.cast(total_index-wrong_index, K.floatx())
    total_index = K.cast(total_index, K.floatx())
    
    acc = K.tf.divide(correct_index, total_index)
    
    return K.cast(acc,K.floatx())

## Usage
model.compile(loss="sparse_categorical_crossentropy", optimizer="adam", metrics=[acc_cal])
model.fit(x, y, epochs=10)