[tune](deps): Bump pytorch-lightning from 1.0.3 to 1.3.2 in /python/requirements

[dependabot]

Bumps pytorch-lightning from 1.0.3 to 1.3.2.

Release notes

Sourced from pytorch-lightning's releases.

Standard weekly patch release

[1.3.2] - 2021-05-18

Changed

• DataModules now avoid duplicate {setup,teardown,prepare_data} calls for the same stage (#7238)

Fixed

• Fixed parsing of multiple training dataloaders (#7433)
• Fixed recursive passing of wrong_type keyword argument in pytorch_lightning.utilities.apply_to_collection (#7433)
• Fixed setting correct DistribType for ddp_cpu (spawn) backend (#7492)
• Fixed incorrect number of calls to LR scheduler when check_val_every_n_epoch > 1 (#7032)

Contributors

@​alanhdu @​carmocca @​justusschock @​tkng

If we forgot someone due to not matching commit email with GitHub account, let us know :]

Standard weekly patch release

[1.3.1] - 2021-05-11

Fixed

• Fixed DeepSpeed with IterableDatasets (#7362)
• Fixed Trainer.current_epoch not getting restored after tuning (#7434)
• Fixed local rank displayed in console log (#7395)

Contributors

@​akihironitta @​awaelchli @​leezu

If we forgot someone due to not matching commit email with GitHub account, let us know :]

Lightning CLI, PyTorch Profiler, Improved Early Stopping

[1.3.0] - 2021-05-06

Added

• Added support for the EarlyStopping callback to run at the end of the training epoch (#6944)
• Added synchronization points before and after setup hooks are run (#7202)
• Added a teardown hook to ClusterEnvironment (#6942)
• Added utils for metrics to scalar conversions (#7180)
• Added utils for NaN/Inf detection for gradients and parameters (#6834)
• Added more explicit exception message when trying to execute trainer.test() or trainer.validate() with fast_dev_run=True (#6667)
• Added LightningCLI class to provide simple reproducibility with minimum boilerplate training CLI (#4492, #6862, #7156, #7299)
• Added gradient_clip_algorithm argument to Trainer for gradient clipping by value (#6123).
• Added a way to print to terminal without breaking up the progress bar (#5470)
• Added support to checkpoint after training steps in ModelCheckpoint callback (#6146)

... (truncated)

Changelog

Sourced from pytorch-lightning's changelog.

[1.3.2] - 2021-05-18

Changed

• DataModules now avoid duplicate {setup,teardown,prepare_data} calls for the same stage (#7238)

Fixed

• Fixed parsing of multiple training dataloaders (#7433)
• Fixed recursive passing of wrong_type keyword argument in pytorch_lightning.utilities.apply_to_collection (#7433)
• Fixed setting correct DistribType for ddp_cpu (spawn) backend (#7492)
• Fixed incorrect number of calls to LR scheduler when check_val_every_n_epoch > 1 (#7032)

[1.3.1] - 2021-05-11

Fixed

• Fixed DeepSpeed with IterableDatasets (#7362)
• Fixed Trainer.current_epoch not getting restored after tuning (#7434)
• Fixed local rank displayed in console log (#7395)

[1.3.0] - 2021-05-06

Added

• Added support for the EarlyStopping callback to run at the end of the training epoch (#6944)
• Added synchronization points before and after setup hooks are run (#7202)
• Added a teardown hook to ClusterEnvironment (#6942)
• Added utils for metrics to scalar conversions (#7180)
• Added utils for NaN/Inf detection for gradients and parameters (#6834)
• Added more explicit exception message when trying to execute trainer.test() or trainer.validate() with fast_dev_run=True (#6667)
• Added LightningCLI class to provide simple reproducibility with minimum boilerplate training CLI ( #4492, #6862, #7156, #7299)
• Added gradient_clip_algorithm argument to Trainer for gradient clipping by value (#6123).
• Added a way to print to terminal without breaking up the progress bar (#5470)
• Added support to checkpoint after training steps in ModelCheckpoint callback (#6146)
• Added TrainerStatus.{INITIALIZING,RUNNING,FINISHED,INTERRUPTED} (#7173)
• Added Trainer.validate() method to perform one evaluation epoch over the validation set (#4948)
• Added LightningEnvironment for Lightning-specific DDP (#5915)
• Added teardown() hook to LightningDataModule (#4673)
• Added auto_insert_metric_name parameter to ModelCheckpoint (#6277)
• Added arg to self.log that enables users to give custom names when dealing with multiple dataloaders (#6274)
• Added teardown method to BaseProfiler to enable subclasses defining post-profiling steps outside of __del__ (#6370)
• Added setup method to BaseProfiler to enable subclasses defining pre-profiling steps for every process (#6633)
• Added no return warning to predict (#6139)

... (truncated)

Commits

• 6b81cd8 v1.3.2
• 40bc8c1 Bugfix/Multiple dataloaders (#7433)
• ea243ee Fix the condition for calling update_learning_rates (#7032)
• da1e36c Fix DistribType for ddp_cpu (spawn) (#7492)
• 2e226d9 Automatically check DataModule.has_{setup,teardown,prepare_data} [2/2] (#7238)
• b9b3ec5 v1.3.1
• 86e827e Pin Sphinx<4.0 (#7456)
• f933d7a fix display bug (#7395)
• 85b71c8 fix 1.9 test (#7441)
• fcd6be1 Restore trainer.current_epoch after tuning (#7434)
• Additional commits viewable in compare view

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