meta-pytorch / meta-pytorch/data
DataPipes for Error Handling and Retry
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- Dominant language
- Python
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Description
🚀 The feature
Provide a mechanism to catch exception raised by a previous DataPipe and retry. These can be related but separate DataPipes. Non-DataPipes implementation should also be considered.
Motivation, pitch
Currently, there is no standard mechanism to handle exception from a source DataPipe. One example of such issues is raised on the PyTorch forum.
Alternatives
Given how iterators are implemented, it is unclear to me if this is feasible as a DataPipe implementation. We may have to modify the iterator wrapper within _hook_iterator.py (inside PyTorch core) to make this feature possible.
We can also consider modifying specific DataPipes where custom error handling and retries are frequently needed .
Additional context
No response
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 examining the DataPipe iterator behavior and the iterator wrapper in _hook_iterator.py. Determine whether exception catching and retry can be supported as related DataPipes or requires changes in PyTorch core, while considering non-DataPipes implementations. Done requires a defined approach for handling exceptions from a source DataPipe and retrying it.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100