Cadene / Cadene/vqa.pytorch

model specifications not coherent with the MLB paper

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#18 3 comments 0 reactions 0 assignees View on GitHub
Dominant language
Python
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Forks
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Description

The model configuration is not the same as described in the paper. There is a softmax layer missing at the end of the model. The paper concatenates the attention * vision features for all the glimpses and then pass it through a single linear layer. You use non-linearity both times before and after fusion.

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Research direction

No file or test is named; start by locating the model implementation and comparing its configuration and forward path with the MLB paper. Done means the model includes the paper's final softmax, concatenates attention-weighted vision features across glimpses before one linear layer, and matches the paper's nonlinearity placement.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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