meta-pytorch / meta-pytorch/data
pointer to a similar library / feedback
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Description
📚 The doc issue
Hi!
I'm the author of a python library which is called SeqTools. It predates torchdata and provides essentially the same functionality as MapDataPipes.
I just wanted to let you know about it, maybe you can pick some code or ideas out of it. For instance:
- Saving the stack to point a runtime error back to when the transformation node was created
- There is also a multiprocessing/multithreading prefetch function which kinda resembles a Dataloader (actually you can check this example which re-implements Dataloader for map-style datasets).
To be honest I have eventually steered away from using it in my deep learning pipelines. It is good for prototyping and pre-computing data. But in my training scripts I just refactor the transforms into a single big function. That is actually more convenient because all necessary variables (data, parameters, augmentation variables) are available in the same scope. I think this is an issue you might face as well in the future.
Suggest a potential alternative/fix
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 reviewing the linked SeqTools library and the project’s MapDataPipes context, especially the cited stack-saving and prefetch ideas. The issue does not name a file, test, entry point, implementation target, or definition of done, so no concrete completion check is provided.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100