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This repository was archived by the owner on Apr 11, 2021. It is now read-only.
This repository was archived by the owner on Apr 11, 2021. It is now read-only.

Sigmoid in AttentionLSTM #30

@bkj

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@bkj

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

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