lightly-ai / lightly-ai/lightly
MMCR benchmark
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feature
- Dominant language
- Python
- Stars
- 3.8k
- Forks
- 367
- Avg merge
- 3d 22h
- Merged PRs (30d)
- 5
Description
MMCR loss and transforms were added in #1446
Now we should add benchmarks for the MMCR model in https://github.com/lightly-ai/lightly/tree/master/benchmarks/imagenet/resnet50
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 reading the existing benchmark files in benchmarks/imagenet/resnet50 and the MMCR loss and transform changes from #1446. Follow the established benchmark structure and add coverage for the MMCR model. Done means the MMCR benchmark is present alongside the existing ResNet-50 ImageNet benchmarks and can be run using their conventions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100