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@sorenmacbeth sorenmacbeth commented Dec 2, 2024

  • Support Multi-GPU training
  • Address some FutureWarning and PerformanceWarning
  • Change type of precision to string to match PL
  • Allow setting of pickle_protocol in DataConfig to save very large DataModules
  • Preserve original index in TabularDataset

I've tested this using the DDP strategy but I believe it will work with other PL strategies as well.


📚 Documentation preview 📚: https://pytorch-tabular--517.org.readthedocs.build/en/517/

it down to `torch.save()` when caching datasets to disk
so that it can be restored when accessing `TabularDataset.data`
`validation_step()` and `test_step()` to distributed training
remove integer choices. Add a pointer to docs with
possible options
@dosubot dosubot bot added size:L This PR changes 100-499 lines, ignoring generated files. enhancement New feature or request labels Dec 2, 2024
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@manujosephv wish i knew a release was coming or i would have push this up sooner, sorry about that

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@manujosephv I see some python 3.8 fails because the option context im using isn't available. let me know how you'd like me to address those

@sorenmacbeth sorenmacbeth force-pushed the main branch 4 times, most recently from 61a68d4 to a3f8242 Compare December 3, 2024 08:22
@dosubot dosubot bot added size:M This PR changes 30-99 lines, ignoring generated files. and removed size:L This PR changes 100-499 lines, ignoring generated files. labels Dec 3, 2024
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@manujosephv I removed the commits that tried to address the FutureWarning regarding silent downcasting and fillna to maintain support back to pandas 2.0.3 and python 3.8.

All checks are passing now

@sorenmacbeth sorenmacbeth changed the title Support Multi-GPU Training Enable Support for Multi-GPU Training Dec 3, 2024
@manujosephv manujosephv merged commit f04a05c into pytorch-tabular:main Dec 10, 2024
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@sorenmacbeth Sorry for the delay. got caught up with some other things last week! Thanks for this PR.. Merging it :)

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