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Posted to issues@spark.apache.org by "Rithwik Ediga Lakhamsani (Jira)" <ji...@apache.org> on 2023/01/20 18:38:00 UTC

[jira] [Resolved] (SPARK-41776) Implement support for PyTorch Lightning

     [ https://issues.apache.org/jira/browse/SPARK-41776?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Rithwik Ediga Lakhamsani resolved SPARK-41776.
----------------------------------------------
    Resolution: Fixed

Not needed, since we are now 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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