Bump pytorch-lightning from 1.1.8 to 1.2.3

[dependabot]

Bumps pytorch-lightning from 1.1.8 to 1.2.3.

Release notes

Sourced from pytorch-lightning's releases.

Standard weekly patch release

[1.2.3] - 2021-03-09

Added

Changed

Fixed

• Fixed ModelPruning(make_pruning_permanent=True) pruning buffers getting removed when saved during training (#6073)
• Fixed when _stable_1d_sort to work when n >= N (#6177)
• Fixed AttributeError when logger=None on TPU (#6221)
• Fixed PyTorch Profiler with emit_nvtx (#6260)
• Fixed trainer.test from best_path hangs after calling trainer.fit (#6272)
• Fixed SingleTPU calling all_gather (#6296)
• Ensure we check deepspeed/sharded in multinode DDP (#6297)
• Check LightningOptimizer doesn't delete optimizer hooks (#6305)
• Resolve memory leak for evaluation (#6326)
• Ensure that clip gradients is only called if the value is greater than 0 (#6330)
• Fixed Trainer not resetting lightning_optimizers when calling Trainer.fit() multiple times (#6372)

Contributors

@​awaelchli, @​carmocca, @​Chizuchizu, @​frankier, @​SeanNaren, @​tchaton

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

Standard weekly patch release

[1.2.2] - 2021-03-02

Added

• Added checkpoint parameter to callback's on_save_checkpoint hook (#6072)

Changed

• Changed the order of backward, step, zero_grad to zero_grad, backward, step (#6147)
• Changed default for DeepSpeed CPU Offload to False, due to prohibitively slow speeds at smaller scale (#6262)

Fixed

• Fixed epoch level schedulers not being called when val_check_interval < 1.0 (#6075)
• Fixed multiple early stopping callbacks (#6197)
• Fixed incorrect usage of detach(), cpu(), to() (#6216)
• Fixed LBFGS optimizer support which didn't converge in automatic optimization (#6147)
• Prevent WandbLogger from dropping values (#5931)
• Fixed error thrown when using valid distributed mode in multi node (#6297)

Contributors

@​akihironitta, @​borisdayma, @​carmocca, @​dvolgyes, @​SeanNaren, @​SkafteNicki

... (truncated)

Changelog

Sourced from pytorch-lightning's changelog.

[1.2.3] - 2021-03-09

Fixed

• Fixed ModelPruning(make_pruning_permanent=True) pruning buffers getting removed when saved during training (#6073)

• Fixed when _stable_1d_sort to work when n >= N (#6177)

• Fixed AttributeError when logger=None on TPU (#6221)

• Fixed PyTorch Profiler with emit_nvtx (#6260)

• Fixed trainer.test from best_path hangs after calling trainer.fit (#6272)

• Fixed SingleTPU calling all_gather (#6296)

• Ensure we check deepspeed/sharded in multinode DDP (#6297

• Check LightningOptimizer doesn't delete optimizer hooks (#6305

• Resolve memory leak for evaluation (#6326

• Ensure that clip gradients is only called if the value is greater than 0 (#6330

• Fixed Trainer not resetting lightning_optimizers when calling Trainer.fit() multiple times (#6372)

• Fixed DummyLogger.log_hyperparams raising a TypeError when running with fast_dev_run=True (#6398)

[1.2.2] - 2021-03-02

Added

• Added checkpoint parameter to callback's on_save_checkpoint hook (#6072)

Changed

• Changed the order of backward, step, zero_grad to zero_grad, backward, step (#6147)
• Changed default for DeepSpeed CPU Offload to False, due to prohibitively slow speeds at smaller scale (#6262)

Fixed

• Fixed epoch level schedulers not being called when val_check_interval < 1.0 (#6075)

• Fixed multiple early stopping callbacks (#6197)

• Fixed incorrect usage of detach(), cpu(), to() (#6216)

• Fixed LBFGS optimizer support which didn't converge in automatic optimization (#6147)

• Prevent WandbLogger from dropping values (#5931)

• Fixed error thrown when using valid distributed mode in multi node (#6297

• Fixed an issue with Tuner.scale_batch_size not finding the batch size attribute in the datamodule (#5968)

[1.2.1] - 2021-02-23

Fixed

• Fixed incorrect yield logic for the amp autocast context manager (#6080)
• Fixed priority of plugin/accelerator when setting distributed mode (#6089)

... (truncated)

Commits

• e719d60 v1.2.3 & test past ckpts
• b6bd04a update python version (#6399)
• be0351f Fix trainer not resetting lightning_optimizers (#6372)
• 60d0c95 fix importing torchtext batch (#6365)
• 7a39789 require: adjust versions (#6363)
• b542323 CI: fix examples - patch download MNIST (#6357)
• afefe83 [Fix] Call clip gradients if clip val greater than 0 (#6330)
• 4c98322 [bugfix] Resolve memory leak for evaluation (#6326)
• 7a2fad4 hotfix for PT1.6 and torchtext (#6323)
• a39cb52 [bugfix] Check LightningOptimizer doesn't delete optimizer hooks (#6305)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually

[dependabot]

Superseded by #17.