Add examples in algorithm_efficiency
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- Dominant language
- Python
- Stars
- 1k
- Forks
- 346
- PR merge metrics
- No merged PRs in 30d
Description
Related post: https://discuss.pytorch.org/t/struggling-to-get-pytorch-fast-enough-to-use-in-public-competition/186015
Example link:
- FastMRI: https://github.com/mlcommons/algorithmic-efficiency/tree/main/algorithmic_efficiency/workloads/fastmri
- Criteo DLRMsmall: https://github.com/mlcommons/algorithmic-efficiency/tree/main/algorithmic_efficiency/workloads/criteo1tb
- WMT Transformer: https://github.com/mlcommons/algorithmic-efficiency/tree/main/algorithmic_efficiency/workloads/wmt
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
Review the algorithmic-efficiency workload examples linked in the issue: FastMRI, Criteo DLRMsmall, and WMT Transformer. Compare them with the existing examples in the repository to determine the expected structure and entry points. Done means the requested examples are added consistently and can be used from algorithm_efficiency.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100