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

Bump pytorch-lightning from 2.0.7 to 2.0.8 #155

Merged
merged 1 commit into from
Aug 31, 2023

Conversation

dependabot[bot]
Copy link
Contributor

@dependabot dependabot bot commented on behalf of github Aug 31, 2023

Bumps pytorch-lightning from 2.0.7 to 2.0.8.

Release notes

Sourced from pytorch-lightning's releases.

Weekly patch release

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

... (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 show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @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/Lightning-AI/lightning) from 2.0.7 to 2.0.8.
- [Release notes](https://github.com/Lightning-AI/lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.0.7...2.0.8)

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

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Aug 31, 2023
@codecov
Copy link

codecov bot commented Aug 31, 2023

Codecov Report

Patch and project coverage have no change.

Comparison is base (19e728e) 98.06% compared to head (13f4b3e) 98.06%.

Additional details and impacted files
@@           Coverage Diff           @@
##             main     #155   +/-   ##
=======================================
  Coverage   98.06%   98.06%           
=======================================
  Files          28       28           
  Lines        1807     1807           
=======================================
  Hits         1772     1772           
  Misses         35       35           

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

@shyuep shyuep merged commit f1e2efe into main Aug 31, 2023
@shyuep shyuep deleted the dependabot/pip/pytorch-lightning-2.0.8 branch August 31, 2023 14:26
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 python Pull requests that update Python code
Projects
None yet
Development

Successfully merging this pull request may close these issues.

1 participant