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SeldonIO / MLServer

An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
https://mlserver.readthedocs.io/en/latest/
Apache License 2.0
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build(deps-dev): bump torchmetrics from 1.3.2 to 1.4.0 in /runtimes/mlflow #1756

Closed dependabot[bot] closed 3 months ago

dependabot[bot] commented 3 months ago

Bumps torchmetrics from 1.3.2 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)
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


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dependabot[bot] commented 3 months ago

Superseded by #1770.