Keras 检查语言模型的复杂性
我用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Keras 检查语言模型的复杂性,keras,nlp,lstm,language-model,perplexity,Keras,Nlp,Lstm,Language Model,Perplexity,我用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 用Python计算模型复杂性的最佳方法是什么?我已经提出了两个版本并附上了相应的源代码,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/h
用Python计算模型复杂性的最佳方法是什么?我已经提出了两个版本并附上了相应的源代码,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