[jira] [Updated] (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 updated SPARK-41776: - 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. Update: This was resolved by using `torch.distributed.run` 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. > 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. > > Update: This was resolved by using `torch.distributed.run` -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (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 updated SPARK-41776: - 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. -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
