我使用 Keras LSTM 创建了一个语言模型，现在我想评估它是否良好，因此我想计算困惑度。
在 Python 中计算模型的困惑度的最佳方法是什么？
我已经提出了两个版本并附上了相应的来源，请随时查看链接。
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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