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@dependabot dependabot bot commented on behalf of github Aug 5, 2024

Bumps torchmetrics from 0.11.0 to 1.4.1.

Release notes

Sourced from torchmetrics's releases.

Minor patch release

[1.4.1] - 2024-08-02

Changed

  • Calculate the text color of ConfusionMatrix plot based on luminance (#2590)
  • Updated _safe_divide to allow Accuracy to run on the GPU (#2640)
  • Improved better error messages for intersection detection metrics for wrong user input (#2577)

Removed

  • Dropped Chrf implementation due to licensing issues with the upstream package (#2668)

Fixed

  • Fixed bug in MetricCollection when using compute groups and compute is called more than once (#2571)
  • Fixed class order of panoptic_quality(..., return_per_class=True) output (#2548)
  • Fixed BootstrapWrapper not being reset correctly (#2574)
  • Fixed integration between ClasswiseWrapper and MetricCollection with custom _filter_kwargs method (#2575)
  • Fixed BertScore calculation: pred target misalignment (#2347)
  • Fixed _cumsum helper function in multi-gpu (#2636)
  • Fixed bug in MeanAveragePrecision.coco_to_tm (#2588)
  • Fixed missed f-strings in exceptions/warnings (#2667)

Key Contributors

@​Borda, @​gxy-gxy, @​i-aki-y, @​ndrwrbgs, @​relativityhd, @​SkafteNicki

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


Full Changelog: Lightning-AI/torchmetrics@v1.4.0...v1.4.1

Minor dependency correction

Full Changelog: Lightning-AI/torchmetrics@v1.4.0...v1.4.0.post0

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)

... (truncated)

Changelog

Sourced from torchmetrics's changelog.

[1.4.1] - 2024-08-02

Changed

  • Calculate text color of ConfusionMatrix plot based on luminance (#2590)
  • Updated _safe_divide to allow Accuracy to run on the GPU (#2640)
  • Improved error messages for intersection detection metrics for wrong user input (#2577)

Removed

  • Dropped Chrf implementation due to licensing issues with the upstream package (#2668)

Fixed

  • Fixed bug in MetricCollection when using compute groups and compute is called more than once (#2571)
  • Fixed class order of panoptic_quality(..., return_per_class=True) output (#2548)
  • Fixed BootstrapWrapper not being reset correctly (#2574)
  • Fixed integration between ClasswiseWrapper and MetricCollection with custom _filter_kwargs method (#2575)
  • Fixed BertScore calculation: pred target misalignment (#2347)
  • Fixed _cumsum helper function in multi-gpu (#2636)
  • Fixed bug in MeanAveragePrecision.coco_to_tm (#2588)
  • Fixed missed f-strings in exceptions/warnings (#2667)

[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)

... (truncated)

Commits
  • 59d67ef releasing 1.4.1
  • 1309b07 test: update after ChrF removed
  • d95c772 build(deps): update huggingface-hub requirement from <0.24 to <0.25 in /requi...
  • 683b620 text: temp drop Chrf implementation (#2668)
  • 83ff38d build(deps): update scipy requirement from <1.14.0,>1.0.0 to >1.0.0,<1.15.0 i...
  • 72e8304 build(deps): bump Lightning-AI/utilities from 0.11.3.post0 to 0.11.6 (#2666)
  • 7a66579 fix missed f-strings (#2667)
  • 98c5456 docs: fix broken link
  • 32279a6 Update _safe_divide to allow Accuracy to run on the GPU (#2640)
  • d214dbe build(deps): bump lightning-utilities from 0.11.3.post0 to 0.11.5 in /require...
  • Additional commits viewable in compare view

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Bumps [torchmetrics](https://github.com/Lightning-AI/torchmetrics) from 0.11.0 to 1.4.1.
- [Release notes](https://github.com/Lightning-AI/torchmetrics/releases)
- [Changelog](https://github.com/Lightning-AI/torchmetrics/blob/v1.4.1/CHANGELOG.md)
- [Commits](Lightning-AI/torchmetrics@v0.11.0...v1.4.1)

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

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Aug 5, 2024
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