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 1.0.3 to 1.2.2 in /python/requirements #8

Conversation

dependabot[bot]
Copy link

@dependabot dependabot bot commented on behalf of github Mar 6, 2021

Bumps pytorch-lightning from 1.0.3 to 1.2.2.

Release notes

Sourced from pytorch-lightning's releases.

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

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

Standard weekly patch release

[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)
  • Fixed error message for AMP + CPU incompatibility (#6107)

Contributors

@​awaelchli, @​SeanNaren, @​carmocca

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

Pruning & Quantization & SWA

[1.2.0] - 2021-02-18

Added

  • Added DataType, AverageMethod and MDMCAverageMethod enum in metrics (#5657)
  • Added support for summarized model total params size in megabytes (#5590)
  • Added support for multiple train loaders (#1959)
  • Added Accuracy metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using the top_k parameter (#4838)

... (truncated)

Changelog

Sourced from pytorch-lightning's changelog.

[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

[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)
  • Fixed error message for AMP + CPU incompatibility (#6107)

[1.2.0] - 2021-02-18

Added

  • Added DataType, AverageMethod and MDMCAverageMethod enum in metrics (#5657)
  • Added support for summarized model total params size in megabytes (#5590)
  • Added support for multiple train loaders (#1959)
  • Added Accuracy metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using the top_k parameter (#4838)
  • Added Accuracy metric now enables the computation of subset accuracy for multi-label or multi-dimensional multi-class inputs with the subset_accuracy parameter (#4838)
  • Added HammingDistance metric to compute the hamming distance (loss) (#4838)
  • Added max_fpr parameter to auroc metric for computing partial auroc metric (#3790)
  • Added StatScores metric to compute the number of true positives, false positives, true negatives and false negatives (#4839)
  • Added R2Score metric (#5241)
  • Added LambdaCallback (#5347)
  • Added BackboneLambdaFinetuningCallback (#5377)
  • Accelerator all_gather supports collection (#5221)
  • Added image_gradients functional metric to compute the image gradients of a given input image. (#5056)
  • Added MetricCollection (#4318)
  • Added .clone() method to metrics (#4318)
  • Added IoU class interface (#4704)

... (truncated)

Commits
  • b3b8f95 hotfix for PT1.6 and torchtext (#6323)
  • 9f3ef1b update lightning version to v1.2.2
  • c5e9d67 [fix] Ensure we check deepspeed/sharded in multinode DDP (#6297)
  • fc95f00 Disable CPU Offload as default for DeepSpeed (#6262)
  • ad61624 Fix for incorrect usage of detach(), cpu(), to() (#6216)
  • 09b287a Remove opt from manual_backward in docs (#6267)
  • 3c498ce Call optimizer.zero_grad() before backward inside closure in AutoOpt (#6147)
  • 5abfd2c fix(wandb): prevent WandbLogger from dropping values (#5931)
  • 9329f58 Add checkpoint parameter to on_save_checkpoint (#6072)
  • 4b71a83 Fix for multiple callbacks (#6197)
  • Additional commits viewable in compare view

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)

@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Mar 6, 2021
@dependabot @github
Copy link
Author

dependabot bot commented on behalf of github Mar 13, 2021

Superseded by #10.

@dependabot dependabot bot closed this Mar 13, 2021
@dependabot dependabot bot deleted the dependabot/pip/python/requirements/pytorch-lightning-1.2.2 branch March 13, 2021 08:02
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