lightly-ai / lightly-ai/lightly
Finish I-JEPA
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feature
- Dominant language
- Python
- Stars
- 3.8k
- Forks
- 367
- Avg merge
- 3d 22h
- Merged PRs (30d)
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Description
Experimental support for I-JEPA was added in #1273
We should do some refactoring and testing before fully releasing the model.
Todo
- #1367
- Verify that weights are correctly initialized and follow this
- Check if we can refactor
IJEPAMaskCollatorinto a transform, comment. - Move positional embedding functions (
_get_1d_sincos_pos_embed_from_gridetc.) tolightly/models/utilsand add reference to source - Add missing docstrings or bring into correct format, check diff from #1273
- Add unit tests
- Finish pytorch lightning and distributed examples
- Add docs
- Add imagenet benchmark to
lightly/benchmarks/imagenet/vit/ijepa.py - #1712
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 experimental I-JEPA support from #1273 and the remaining checklist, including IJEPAMaskCollator and the positional embedding functions in lightly/models/utils. Inspect lightly/benchmarks/imagenet/vit/ijepa.py along with the referenced examples and diffs; done means the initialization, refactoring, tests, docstrings, examples, documentation, and benchmark items are complete.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, documentation, machine-learning, testing
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100