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https://issues.apache.org/jira/browse/SPARK-41776?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Rithwik Ediga Lakhamsani updated SPARK-41776:
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Description: This requires us to just call train() on each spark task
separately without much preprocessing or postprocessing because PyTorch
Lightning handles that by itself. (was: This requires us to just call train()
on each spark task separately without much preprocessing or postprocessing
because PyTorch Lightning handles that by itself.
Update: This was resolved by using `torch.distributed.run`)
> Implement support for PyTorch Lightning
> ---------------------------------------
>
> Key: SPARK-41776
> URL: https://issues.apache.org/jira/browse/SPARK-41776
> Project: Spark
> Issue Type: Sub-task
> Components: ML, PySpark
> Affects Versions: 3.4.0
> Reporter: Rithwik Ediga Lakhamsani
> Priority: Major
>
> This requires us to just call train() on each spark task separately without
> much preprocessing or postprocessing because PyTorch Lightning handles that
> by itself.
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