[tune](deps): Bump pytorch-lightning from 1.0.3 to 1.4.2 in /python/requirements/tune

[dependabot]

Bumps pytorch-lightning from 1.0.3 to 1.4.2.

Release notes

Sourced from pytorch-lightning's releases.

Standard weekly patch release

[1.4.2] - 2021-08-10

• Fixed recursive call for apply_to_collection(include_none=False) (#8719)
• Fixed truncated backprop through time enablement when set as a property on the LightningModule and not the Trainer (#8804)
• Fixed comments and exception message for metrics_to_scalars (#8782)
• Fixed typo error in LightningLoggerBase.after_save_checkpoint docstring (#8737)

Contributors

@​Aiden-Jeon @​ananthsub @​awaelchli @​edward-io If we forgot someone due to not matching commit email with GitHub account, let us know :]

Standard weekly patch release

[1.4.1] - 2021-08-03

• Fixed trainer.fit_loop.split_idx always returning None (#8601)
• Fixed references for ResultCollection.extra (#8622)
• Fixed reference issues during epoch end result collection (#8621)
• Fixed horovod auto-detection when horovod is not installed and the launcher is mpirun (#8610)
• Fixed an issue with training_step outputs not getting collected correctly for training_epoch_end (#8613)
• Fixed distributed types support for CPUs (#8667)
• Fixed a deadlock issue with DDP and torchelastic (#8655)
• Fixed accelerator=ddp choice for CPU (#8645)

Contributors

@​awaelchli, @​borda, @​carmocca, @​kaushikb11, @​tchaton

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

TPU Pod Training, IPU Accelerator, DeepSpeed Infinity, Fully Sharded Data Parallel

Today we are excited to announce Lightning 1.4, introducing support for TPU pods, XLA profiling, IPUs, and new plugins to reach 10+ billion parameters, including Deep Speed Infinity, Fully Sharded Data-Parallel and more!

https://devblog.pytorchlightning.ai/announcing-lightning-1-4-8cd20482aee9

[1.4.0] - 2021-07-27

Added

• Added extract_batch_size utility and corresponding tests to extract batch dimension from multiple batch types (#8357)
• Added support for named parameter groups in LearningRateMonitor (#7987)
• Added dataclass support for pytorch_lightning.utilities.apply_to_collection (#7935)
• Added support to LightningModule.to_torchscript for saving to custom filesystems with fsspec (#7617)
• Added KubeflowEnvironment for use with the PyTorchJob operator in Kubeflow
• Added LightningCLI support for config files on object stores (#7521)
• Added ModelPruning(prune_on_train_epoch_end=True|False) to choose when to apply pruning (#7704)
• Added support for checkpointing based on a provided time interval during training (#7515)

... (truncated)

Changelog

Sourced from pytorch-lightning's changelog.

[1.4.2] - 2021-08-10

• Fixed recursive call for apply_to_collection(include_none=False) (#8719)
• Fixed truncated backprop through time enablement when set as a property on the LightningModule and not the Trainer (#8804)
• Fixed comments and exception message for metrics_to_scalars (#8782)
• Fixed typo error in LightningLoggerBase.after_save_checkpoint docstring (#8737)

[1.4.1] - 2021-08-03

• Fixed trainer.fit_loop.split_idx always returning None (#8601)
• Fixed references for ResultCollection.extra (#8622)
• Fixed reference issues during epoch end result collection (#8621)
• Fixed horovod auto-detection when horovod is not installed and the launcher is mpirun (#8610)
• Fixed an issue with training_step outputs not getting collected correctly for training_epoch_end (#8613)
• Fixed distributed types support for CPUs (#8667)
• Fixed a deadlock issue with DDP and torchelastic (#8655)
• Fixed accelerator=ddp choice for CPU (#8645)

[1.4.0] - 2021-07-27

Added

• Added extract_batch_size utility and corresponding tests to extract batch dimension from multiple batch types. (#8357)
• Added support for named parameter groups in LearningRateMonitor (#7987)
• Added dataclass support for pytorch_lightning.utilities.apply_to_collection (#7935)
• Added support to LightningModule.to_torchscript for saving to custom filesystems with fsspec (#7617)
• Added KubeflowEnvironment for use with the PyTorchJob operator in Kubeflow
• Added LightningCLI support for config files on object stores (#7521)
• Added ModelPruning(prune_on_train_epoch_end=True|False) to choose when to apply pruning (#7704)
• Added support for checkpointing based on a provided time interval during training (#7515)
• Progress tracking
  • Added dataclasses for progress tracking (#6603, #7574, #8140, #8362)
  • Add {,load_}state_dict to the progress tracking dataclasses (#8140)
  • Connect the progress tracking dataclasses to the loops (#8244, #8362)
  • Do not reset the progress tracking dataclasses total counters (#8475)
• Added support for passing a LightningDataModule positionally as the second argument to trainer.{validate,test,predict} (#7431)
• Added argument trainer.predict(ckpt_path) (#7430)
• Added clip_grad_by_value support for TPUs (#7025)
• Added support for passing any class to is_overridden (#7918)
• Added sub_dir parameter to TensorBoardLogger (#6195)
• Added correct dataloader_idx to batch transfer hooks (#6241)
• Added include_none=bool argument to apply_to_collection (#7769)
• Added apply_to_collections to apply a function to two zipped collections (#7769)
• Added ddp_fully_sharded support (#7487)

... (truncated)

Commits

• b845c44 Add requirement to handle deepspeed version
• 7aa862a Fix import
• db3b467 Fix pre-commit blacken-docs failures (#8624)
• 41ac9e2 fix TM import MAPE
• a0d29ed Increment version, upate CHANGELOG.md
• dff47e7 Tests: fix deprecated TM mape (#8830)
• a4283c2 Fix import
• 7cc4cc5 Legacy: simple classif training (#8535)
• d5acc0c Fix truncated backprop through time when set on LightningModule and not Train...
• 9e44c65 Fix tests for new tensorboard >= 2.6 (#8789)
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[dependabot]

Superseded by #54.