Pytorch Lightning Versions Save

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

2.1.0

6 months ago

2.1.0.rc1

6 months ago

:rabbit:

2.0.9.post0

7 months ago

2.0.9

7 months ago

App

Fixed

  • Replace LightningClient with import from lightning_cloud (#18544)

Fabric

Fixed

  • Fixed an issue causing the _FabricOptimizer.state to remain outdated after loading with load_state_dict (#18488)

PyTorch

Fixed

  • Fixed an issue that wouldn't prevent the user to set the log_model parameter in WandbLogger via the LightningCLI (#18458)
  • Fixed the display of v_num in the progress bar when running with Trainer(fast_dev_run=True) (#18491)
  • Fixed UnboundLocalError when running with python -O (#18496)
  • Fixed visual glitch with the TQDM progress bar leaving the validation bar incomplete before switching back to the training display (#18503)
  • Fixed false positive warning about logging interval when running with Trainer(fast_dev_run=True) (#18550)

Contributors

@awaelchli, @borda, @justusschock, @SebastianGer

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2.0.8

8 months ago

App

Changed

  • Change top folder (#18212)
  • Remove _handle_is_headless calls in app run loop (#18362)

Fixed

  • refactor path to root preventing circular import (#18357)

Fabric

Changed

  • On XLA, avoid setting the global rank before processes have been launched as this will initialize the PJRT computation client in the main process (#16966)

Fixed

  • Fixed model parameters getting shared between processes when running with strategy="ddp_spawn" and accelerator="cpu"; this has a necessary memory impact, as parameters are replicated for each process now (#18238)
  • Removed false positive warning when using fabric.no_backward_sync with XLA strategies (#17761)
  • Fixed issue where Fabric would not initialize the global rank, world size, and rank-zero-only rank after initialization and before launch (#16966)
  • Fixed FSDP full-precision param_dtype training (16-mixed, bf16-mixed and 32-true configurations) to avoid FSDP assertion errors with PyTorch < 2.0 (#18278)

PyTorch

Changed

  • On XLA, avoid setting the global rank before processes have been launched as this will initialize the PJRT computation client in the main process (#16966)
  • Fix inefficiency in rich progress bar (#18369)

Fixed

  • Fixed FSDP full-precision param_dtype training (16-mixed and bf16-mixed configurations) to avoid FSDP assertion errors with PyTorch < 2.0 (#18278)
  • Fixed an issue that prevented the use of custom logger classes without an experiment property defined (#18093)
  • Fixed setting the tracking uri in MLFlowLogger for logging artifacts to the MLFlow server (#18395)
  • Fixed redundant iter() call to dataloader when checking dataloading configuration (#18415)
  • Fixed model parameters getting shared between processes when running with strategy="ddp_spawn" and accelerator="cpu"; this has a necessary memory impact, as parameters are replicated for each process now (#18238)
  • Properly manage fetcher.done with dataloader_iter (#18376)

Contributors

@awaelchli, @Borda, @carmocca, @quintenroets, @rlizzo, @speediedan, @tchaton

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2.0.7

8 months ago

App

Changed

  • Removed the top-level import lightning.pdb; import lightning.app.pdb instead (#18177)
  • Client retries forever (#18065)

Fixed

  • Fixed an issue that would prevent the user to set the multiprocessing start method after importing lightning (#18177)

Fabric

Changed

  • Disabled the auto-detection of the Kubeflow environment (#18137)

Fixed

  • Fixed issue where DDP subprocesses that used Hydra would set hydra's working directory to current directory (#18145)
  • Fixed an issue that would prevent the user to set the multiprocessing start method after importing lightning (#18177)
  • Fixed an issue with Fabric.all_reduce() not performing an inplace operation for all backends consistently (#18235)

PyTorch

Added

  • Added LightningOptimizer.refresh() to update the __dict__ in case the optimizer it wraps has changed its internal state (#18280)

Changed

  • Disabled the auto-detection of the Kubeflow environment (#18137))

Fixed

  • Fixed a Missing folder exception when using a Google Storage URL as a default_root_dir (#18088)
  • Fixed an issue that would prevent the user to set the multiprocessing start method after importing lightning (#18177)
  • Fixed the gradient unscaling logic if the training step skipped backward (by returning None) (#18267)
  • Ensure that the closure running inside the optimizer step has gradients enabled, even if the optimizer step has it disabled (#18268)
  • Fixed an issue that could cause the LightningOptimizer wrapper returned by LightningModule.optimizers() have different internal state than the optimizer it wraps (#18280)

Contributors

@0x404, @awaelchli, @bilelomrani1, @borda, @ethanwharris, @nisheethlahoti

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2.1.0.rc0

8 months ago

:rabbit:

2.0.6

9 months ago

2.0.6

App

  • Fixed handling a None request in the file orchestration queue (#18111)

Fabric

  • Fixed TensorBoardLogger.log_graph not unwrapping the _FabricModule (#17844)

PyTorch

  • LightningCLI not saving correctly seed_everything when run=True and seed_everything=True (#18056)
  • Fixed validation of non-PyTorch LR schedulers in manual optimization mode (#18092)
  • Fixed an attribute error for _FaultTolerantMode when loading an old checkpoint that pickled the enum (#18094)

Contributors

@awaelchli, @lantiga, @mauvilsa, @shihaoyin

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2.0.5

9 months ago

App

Added

  • plugin: store source app (#17892)
  • added colocation identifier (#16796)
  • Added exponential backoff to HTTPQueue put (#18013)
  • Content for plugins (#17243)

Changed

  • Save a reference to created tasks, to avoid tasks disappearing (#17946)

Fabric

Added

  • Added validation against misconfigured device selection when using the DeepSpeed strategy (#17952)

Changed

  • Avoid info message when loading 0 entry point callbacks (#17990)

Fixed

  • Fixed the emission of a false-positive warning when calling a method on the Fabric-wrapped module that accepts no arguments (#17875)
  • Fixed check for FSDP's flat parameters in all parameter groups (#17914)
  • Fixed automatic step tracking in Fabric's CSVLogger (#17942)
  • Fixed an issue causing the torch.set_float32_matmul_precision info message to show multiple times (#17960)
  • Fixed loading model state when Fabric.load() is called after Fabric.setup() (#17997)

PyTorch

Fixed

  • Fixed delayed creation of experiment metadata and checkpoint/log dir name when using WandbLogger (#17818)
  • Fixed incorrect parsing of arguments when augmenting exception messages in DDP (#17948)
  • Fixed an issue causing the torch.set_float32_matmul_precision info message to show multiple times (#17960)
  • Added missing map_location argument for the LightningDataModule.load_from_checkpoint function (#17950)
  • Fix support for neptune-client (#17939)

Contributors

@anio, @awaelchli, @borda, @ethanwharris, @lantiga, @nicolai86, @rjarun8, @schmidt-ai, @schuhschuh, @wouterzwerink, @yurijmikhalevich

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2.0.4

10 months ago

App

Fixed

  • bumped several dependencies to address security vulnerabilities.

Fabric

Fixed

  • Fixed validation of parameters of plugins.precision.MixedPrecision (#17687)
  • Fixed an issue with HPU imports leading to performance degradation (#17788)

PyTorch

Changed

  • Changes to the NeptuneLogger (#16761):
    • It now supports neptune-client 0.16.16 and neptune >=1.0, and we have replaced the log() method with append() and extend().
    • It now accepts a namespace Handler as an alternative to Run for the run argument. This means that you can call it NeptuneLogger(run=run["some/namespace"]) to log everything to the some/namespace/ location of the run.

Fixed

  • Fixed validation of parameters of plugins.precision.MixedPrecisionPlugin (#17687)
  • Fixed deriving default map location in LightningModule.load_from_checkpoint when there is an extra state (#17812)

Contributors

@akreuzer, @awaelchli, @borda, @jerome-habana, @kshitij12345

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