VFormer
A PyTorch library for Vision Transformers
Getting Started
Read the contributing guidelines in CONTRIBUTING.rst
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Read the contributing guidelines in CONTRIBUTING.rst
to learn how to start contributing.
viz
module.We can replace _Projection class with a one-liner if-else statement.
Should we replace it with if-else or should we keep the current implementation?
cc: @NeelayS @aditya-agrawal-30502 @alvanli
During the last PR (#45), I had to revert back because of compatibility issues
In this PR I have added some docstrings and Minor changes like changing variable names
this PR is the same as - #48 with edited title :)
@NeelayS
AbsolutePositionEmbedding class was structured specifically for the PVT, but we can use it in other models too if we re-structure it properly, it should also support sinusoidal position embedding or a separate class for Sinusoidal embedding also works.
enhancementThis paper describes how promoting smoothness with a recently proposed sharpness-aware optimizer substantially improves the performance of ViTs.
It would be good to have an implementation of this optimizer in our library. It would fit in the functional
module.
I have added some fixes for page breaks in #86.
Still, we need to enhance the docs for visualization methods.
We can include the license/copyright disclaimer for visualization methods in our license or have a separate file.
Additionally, we can add the sample outputs from these methods into the doc.
CC : @NeelayS @aditya-agrawal-30502 @alvanli
documentation enhancement good first issuepaper - https://arxiv.org/abs/2202.09741 code- https://github.com/Visual-Attention-Network/VAN-Classification https://github.com/Visual-Attention-Network/VAN-Segmentation
Paper implementationFirst release of VFormer
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