检查语言模型的复杂性 [英] Check perplexity of a Language Model

问题描述

我使用 Keras LSTM 创建了一个语言模型，现在我想评估它是否好，所以我想计算困惑度.

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

在 Python 中计算模型复杂度的最佳方法是什么?

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

推荐答案

我想出了两个版本并附上了它们对应的源代码，请随时查看链接.

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

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