Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[tune](deps): Bump pytorch-lightning from 1.4.3 to 1.5.4 in /python/requirements/tune #82

Conversation

dependabot[bot]
Copy link

@dependabot dependabot bot commented on behalf of github Dec 4, 2021

Bumps pytorch-lightning from 1.4.3 to 1.5.4.

Release notes

Sourced from pytorch-lightning's releases.

Standard weekly patch release

[1.5.4] - 2021-11-30

Fixed

  • Fixed support for --key.help=class with the LightningCLI (#10767)
  • Fixed _compare_version for python packages (#10762)
  • Fixed TensorBoardLogger SummaryWriter not close before spawning the processes (#10777)
  • Fixed a consolidation error in Lite when attempting to save the state dict of a sharded optimizer (#10746)
  • Fixed the default logging level for batch hooks associated with training from on_step=False, on_epoch=True to on_step=True, on_epoch=False (#10756)

Removed

Contributors

@​awaelchli @​carmocca @​kaushikb11 @​rohitgr7 @​tchaton

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

Standard weekly patch release

[1.5.3] - 2021-11-24

Fixed

  • Fixed ShardedTensor state dict hook registration to check if torch distributed is available (#10621)
  • Fixed an issue with self.log not respecting a tensor's dtype when applying computations (#10076)
  • Fixed LigtningLite _wrap_init popping unexisting keys from DataLoader signature parameters (#10613)
  • Fixed signals being registered within threads (#10610)
  • Fixed an issue that caused Lightning to extract the batch size even though it was set by the user in LightningModule.log (#10408)
  • Fixed Trainer(move_metrics_to_cpu=True) not moving the evaluation logged results to CPU (#10631)
  • Fixed the {validation,test}_step outputs getting moved to CPU with Trainer(move_metrics_to_cpu=True) (#10631)
  • Fixed signals being registered within threads (#10610)
  • Fixed an issue with collecting logged test results with multiple dataloaders (#10522)

Contributors

@​ananthsub @​awaelchli @​carmocca @​jiwidi @​kaushikb11 @​qqueing @​rohitgr7 @​shabie @​tchaton

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

Standard weekly patch release

[1.5.2] - 2021-11-16

Fixed

... (truncated)

Changelog

Sourced from pytorch-lightning's changelog.

[1.5.4] - 2021-11-30

Fixed

  • Fixed support for --key.help=class with the LightningCLI (#10767)
  • Fixed _compare_version for python packages (#10762)
  • Fixed TensorBoardLogger SummaryWriter not close before spawning the processes (#10777)
  • Fixed a consolidation error in Lite when attempting to save the state dict of a sharded optimizer (#10746)
  • Fixed the default logging level for batch hooks associated with training from on_step=False, on_epoch=True to on_step=True, on_epoch=False (#10756)

Removed

[1.5.3] - 2021-11-24

Fixed

  • Fixed ShardedTensor state dict hook registration to check if torch distributed is available (#10621)
  • Fixed an issue with self.log not respecting a tensor's dtype when applying computations (#10076)
  • Fixed LigtningLite _wrap_init popping unexisting keys from DataLoader signature parameters (#10613)
  • Fixed signals being registered within threads (#10610)
  • Fixed an issue that caused Lightning to extract the batch size even though it was set by the user in LightningModule.log (#10408)
  • Fixed Trainer(move_metrics_to_cpu=True) not moving the evaluation logged results to CPU (#10631)
  • Fixed the {validation,test}_step outputs getting moved to CPU with Trainer(move_metrics_to_cpu=True) (#10631)
  • Fixed an issue with collecting logged test results with multiple dataloaders (#10522)

[1.5.2] - 2021-11-16

Fixed

  • Fixed CombinedLoader and max_size_cycle didn't receive a DistributedSampler (#10374)
  • Fixed an issue where class or init-only variables of dataclasses were passed to the dataclass constructor in utilities.apply_to_collection (#9702)
  • Fixed isinstance not working with init_meta_context, materialized model not being moved to the device (#10493)
  • Fixed an issue that prevented the Trainer to shutdown workers when execution is interrupted due to failure(#10463)
  • Squeeze the early stopping monitor to remove empty tensor dimensions (#10461)
  • Fixed sampler replacement logic with overfit_batches to only replace the sample when SequentialSampler is not used (#10486)
  • Fixed scripting causing false positive deprecation warnings (#10470, #10555)
  • Do not fail if batch size could not be inferred for logging when using DeepSpeed (#10438)
  • Fixed propagation of device and dtype information to submodules of LightningLite when they inherit from DeviceDtypeModuleMixin (#10559)

[1.5.1] - 2021-11-09

Fixed

  • Fixed apply_to_collection(defaultdict) (#10316)
  • Fixed failure when DataLoader(batch_size=None) is passed (#10345)

... (truncated)

Commits

Dependabot compatibility score

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 ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

Bumps [pytorch-lightning](https://github.com/PyTorchLightning/pytorch-lightning) from 1.4.3 to 1.5.4.
- [Release notes](https://github.com/PyTorchLightning/pytorch-lightning/releases)
- [Changelog](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/CHANGELOG.md)
- [Commits](Lightning-AI/pytorch-lightning@1.4.3...1.5.4)

---
updated-dependencies:
- dependency-name: pytorch-lightning
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Dec 4, 2021
@dependabot @github
Copy link
Author

dependabot bot commented on behalf of github Dec 11, 2021

Superseded by #83.

@dependabot dependabot bot closed this Dec 11, 2021
@dependabot dependabot bot deleted the dependabot/pip/python/requirements/tune/pytorch-lightning-1.5.4 branch December 11, 2021 08:06
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
dependencies Pull requests that update a dependency file
Projects
None yet
Development

Successfully merging this pull request may close these issues.

0 participants