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 torchmetrics from 1.3.1 to 1.4.0 in /requirements #144

Closed

Conversation

dependabot[bot]
Copy link

@dependabot dependabot bot commented on behalf of github May 6, 2024

Bumps torchmetrics from 1.3.1 to 1.4.0.

Release notes

Sourced from torchmetrics's releases.

Metrics for segmentation

In Torchmetrics v1.4, we are happy to introduce a new domain of metrics to the library: segmentation metrics. Segmentation metrics are used to evaluate how well segmentation algorithms are performing, e.g., algorithms that take in an image and pixel-by-pixel decide what kind of object it is. These kind of algorithms are necessary in applications such as self driven cars. Segmentations are closely related to classification metrics, but for now, in Torchmetrics, expect the input to be formatted differently; see the documentation for more info. For now, MeanIoU and GeneralizedDiceScore have been added to the subpackage, with many more to follow in upcoming releases of Torchmetrics. We are happy to receive any feedback on metrics to add in the future or the user interface for the new segmentation metrics.

Torchmetrics v1.3 adds new metrics to the classification and image subpackage and has multiple bug fixes and other quality-of-life improvements. We refer to the changelog for the complete list of changes.

[1.4.0] - 2024-05-03

Added

  • Added SensitivityAtSpecificity metric to classification subpackage (#2217)
  • Added QualityWithNoReference metric to image subpackage (#2288)
  • Added a new segmentation metric:
  • Added support for calculating segmentation quality and recognition quality in PanopticQuality metric (#2381)
  • Added pretty-errors for improving error prints (#2431)
  • Added support for torch.float weighted networks for FID and KID calculations (#2483)
  • Added zero_division argument to selected classification metrics (#2198)

Changed

  • Made __getattr__ and __setattr__ of ClasswiseWrapper more general (#2424)

Fixed

  • Fix getitem for metric collection when prefix/postfix is set (#2430)
  • Fixed axis names with Precision-Recall curve (#2462)
  • Fixed list synchronization with partly empty lists (#2468)
  • Fixed memory leak in metrics using list states (#2492)
  • Fixed bug in computation of ERGAS metric (#2498)
  • Fixed BootStrapper wrapper not working with kwargs provided argument (#2503)
  • Fixed warnings being suppressed in MeanAveragePrecision when requested (#2501)
  • Fixed corner-case in binary_average_precision when only negative samples are provided (#2507)

Key Contributors

@​baskrahmer, @​Borda, @​ChristophReich1996, @​daniel-code, @​furkan-celik, @​i-aki-y, @​jlcsilva, @​NielsRogge, @​oguz-hanoglu, @​SkafteNicki, @​ywchan2005

New Contributors

... (truncated)

Changelog

Sourced from torchmetrics's changelog.

[1.4.0] - 2024-05-03

Added

  • Added SensitivityAtSpecificity metric to classification subpackage (#2217)
  • Added QualityWithNoReference metric to image subpackage (#2288)
  • Added a new segmentation metric:
  • Added support for calculating segmentation quality and recognition quality in PanopticQuality metric (#2381)
  • Added pretty-errors for improving error prints (#2431)
  • Added support for torch.float weighted networks for FID and KID calculations (#2483)
  • Added zero_division argument to selected classification metrics (#2198)

Changed

  • Made __getattr__ and __setattr__ of ClasswiseWrapper more general (#2424)

Fixed

  • Fix getitem for metric collection when prefix/postfix is set (#2430)
  • Fixed axis names with Precision-Recall curve (#2462)
  • Fixed list synchronization with partly empty lists (#2468)
  • Fixed memory leak in metrics using list states (#2492)
  • Fixed bug in computation of ERGAS metric (#2498)
  • Fixed BootStrapper wrapper not working with kwargs provided argument (#2503)
  • Fixed warnings being suppressed in MeanAveragePrecision when requested (#2501)
  • Fixed corner-case in binary_average_precision when only negative samples are provided (#2507)

[1.3.2] - 2024-03-18

Fixed

  • Fixed negative variance estimates in certain image metrics (#2378)
  • Fixed dtype being changed by deepspeed for certain regression metrics (#2379)
  • Fixed plotting of metric collection when prefix/postfix is set (#2429)
  • Fixed bug when top_k>1 and average="macro" for classification metrics (#2423)
  • Fixed case where label prediction tensors in classification metrics were not validated correctly (#2427)
  • Fixed how auc scores are calculated in PrecisionRecallCurve.plot methods (#2437)
Commits
  • f6d1f44 releasing 1.4.0
  • 335ebe6 Add zero_division option to the precision, recall, f1, fbeta. (#2198)
  • d9add3d build(deps): bump torch from 2.2.2 to 2.3.0 & torchvision from <0.18.0 ...
  • 6258fad build(deps): bump coverage from 7.4.4 to 7.5.0 in /requirements (#2521)
  • f303fda CI: debugging setup Linux (#2515)
  • 01f2c4b Description on how to run tests & build docs (#2500)
  • 3d52192 Add optional color map parameter for confusion matrix (#2512)
  • af32fd0 [Segmentation] Add mean IoU (#1236)
  • ec2c246 build(deps): update transformers requirement from <4.40.0,>=4.10.0 to >=4.10....
  • 745c471 [Segmentation] Added generalized dice score metric (#1090)
  • 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 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 [torchmetrics](https://github.com/Lightning-AI/torchmetrics) from 1.3.1 to 1.4.0.
- [Release notes](https://github.com/Lightning-AI/torchmetrics/releases)
- [Changelog](https://github.com/Lightning-AI/torchmetrics/blob/master/CHANGELOG.md)
- [Commits](Lightning-AI/torchmetrics@v1.3.1...v1.4.0)

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

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels May 6, 2024
Copy link
Author

dependabot bot commented on behalf of github May 15, 2024

Superseded by #146.

@dependabot dependabot bot closed this May 15, 2024
@dependabot dependabot bot deleted the dependabot/pip/requirements/torchmetrics-1.4.0 branch May 15, 2024 15:39
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.

0 participants