Visualizing Attention for Sequence Data in the Frequency domain

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I have trouble finding out how i can map my attention weights onto my input data.
My input data is in a 512*1 Cell, it represents a vibration in the frequency-domain, after going through different layers (mainly 2 CNN and 2 Bi-GRU), i have a high level representation of it(480*1), that enters a self attention layer.
I am able to extract the attention weights (256*1), but I am unsure on how to map them to my input sequence, am i able to just upscale the attention vector and overlay it onto my input?
I've added a screenshots of the model structure, to help you understand the problem.
The whole problem is further illustrated in this research paper.
I would be grateful for anyone, who can help me understand how I need to proceed.

Answers (1)

Kaustab Pal
Kaustab Pal on 11 Jul 2024
Hi @Luca,
To upscale your attention weights from a 256x1 dimension to 512x1, you can utilize the "imresize" function.
You can refer to the imresizefunction documentation available here: https://www.mathworks.com/help/matlab/ref/imresize.html
Below is an example demonstrating how to achieve this:
A = randn(256,1); % dummy data of size 256x1
B = imresize(A,[512,1]); % resize to required size
size(B) % return an image B of size 512x1
ans = 1x2
512 1
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I hope this solves your issue.

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