Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

About Attention for Memory Addressig #12

Open
simaiden opened this issue Jun 15, 2020 · 1 comment
Open

About Attention for Memory Addressig #12

simaiden opened this issue Jun 15, 2020 · 1 comment

Comments

@simaiden
Copy link

In the paper at section 3.3.2, in eq 4 shows that in MemAE each weight is computed using softmax operation and cosine similarity, but I can't find this in the code, so where this operation actually is used?

Thanks

@Wolfybox
Copy link

Cosine Similarity is not implemented in the code. Instead, the weight computing process was replaced as applying Softmax on the inner product of z and m. I tried modified it to the way as written in the paper, however I found using cosine similarity only got me to an attention weight with all elements down to zero. So I guess the cosine distance measure was not applicable as it was said in the paper, which explained why they replaced it with inner product similarity in the actual implementation.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants