检查语言模型的困惑

Question

I created a language model with Keras LSTM and now I want to assess wether it's good so I want to calculate perplexity.

What is the best way to calc perplexity of a model in Python?

Answer 1

I've come up with two versions and attached their corresponding source, please feel free to check the links out.

def perplexity_raw(y_true, y_pred):
    """
    The perplexity metric. Why isn't this part of Keras yet?!
    https://stackoverflow.com/questions/41881308/how-to-calculate-perplexity-of-rnn-in-tensorflow
    https://github.com/keras-team/keras/issues/8267
    """
#     cross_entropy = K.sparse_categorical_crossentropy(y_true, y_pred)
    cross_entropy = K.cast(K.equal(K.max(y_true, axis=-1),
                          K.cast(K.argmax(y_pred, axis=-1), K.floatx())),
                  K.floatx())
    perplexity = K.exp(cross_entropy)
    return perplexity

def perplexity(y_true, y_pred):
    """
    The perplexity metric. Why isn't this part of Keras yet?!
    https://stackoverflow.com/questions/41881308/how-to-calculate-perplexity-of-rnn-in-tensorflow
    https://github.com/keras-team/keras/issues/8267
    """
    cross_entropy = K.sparse_categorical_crossentropy(y_true, y_pred)
    perplexity = K.exp(cross_entropy)
    return perplexity