VFormer
A PyTorch library for Vision Transformers
Getting Started
Read the contributing guidelines in CONTRIBUTING.rst
to learn how to start contributing.
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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