Add other swin architectures.
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- Dominant language
- Python
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Description
🚀 The feature
The original paper describes a few more configurations based on swin Transformer.
- Swin Large: Simply a large model of swin transformer, needs a few config tweaks and we can port weights probably?
- SwinMLP: MLP Mixer Based SwinTransformer. Described in the original paper.
- SwinMoe: Mixture of experts for Swin https://arxiv.org/pdf/2204.09636.pdf
Motivation, pitch
I think that Swin Large and SwinMLP could be good candidates as they need few edits for implementation.
I'm not sure if we can port weights, or train from scratch. As adding weights and implementation would also add a CI job and maintaining it.
Alternatives
No response
Additional context
No response
cc @datumbox
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the existing Swin Transformer implementation and the configurations described in the original paper, including Swin Large and SwinMLP; the linked SwinMoe paper defines another possible scope. First establish which architecture should be supported, whether pretrained weights are required, and whether CI coverage is expected. Done means an agreed implementation scope with corresponding weights and CI requirements addressed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100