lightly-ai / lightly-ai/lightly

Finish I-JEPA

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Python
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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 IJEPAMaskCollator into a transform, comment.
  • Move positional embedding functions (_get_1d_sincos_pos_embed_from_grid etc.) to lightly/models/utils and 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

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. 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

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