ml-explore / ml-explore/mlx-data
Feature Request: `stream.checkpoint(path)`
Open
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- Dominant language
- C++
- Stars
- 483
- Forks
- 62
- PR merge metrics
- No merged PRs in 30d
Description
- Checkpointing data workloads is critical when training on larger corpora of data.
- Checkpointing enables recovery or continuing training at a later date.
- Checkpointing is necessary to restore state and prevent sample repeats.
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 locating the stream API and the implementation behind stream.checkpoint(path). Define the checkpointed state, restore behavior, and sample-repeat guarantees before identifying tests that can verify checkpoint creation and resumption.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- data-engineering
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100