codekansas/keras-language-modeling

Sigmoid in AttentionLSTM

bkj opened this issue · 0 comments

bkj commented

I noticed that you run the attention through a sigmoid because you were having numerical problems:

https://github.com/codekansas/keras-language-modeling/blob/master/attention_lstm.py#L54

This may work, but I think that should actually be a softmax. In the paper you cite, it only says that the activation should be proportional to

exp(dot(m, U_s))

In another paper [1], they explicitly say it should be

softmax(exp(dot(m, U_s)))

[1] https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf