build(deps-dev): bump torchmetrics from 1.5.2 to 1.6.0 in /runtimes/mlflow

[dependabot]

Bumps torchmetrics from 1.5.2 to 1.6.0.

Release notes

Sourced from torchmetrics's releases.

More metrics

The latest release of TorchMetrics introduces several significant enhancements and new features that will greatly benefit users across various domains. This update includes the addition of new metrics and methods that enhance the library's functionality and usability.

One of the key additions is the NISQA audio metric, which provides advanced capabilities for evaluating audio quality. In the classification domain, the new LogAUC and NegativePredictiveValue metrics offer improved tools for assessing model performance, particularly in imbalanced datasets. For regression tasks, the NormalizedRootMeanSquaredError metric has been introduced, providing a normalized measure of prediction accuracy that is less sensitive to outliers.

In the field of image segmentation, the new Dice metric enhances the evaluation of segmentation models by providing a robust measure of overlap between predicted and ground truth masks. Additionally, the merge_state method has been added to the Metric class, allowing for more efficient state management and aggregation across multiple devices or processes.

Furthermore, this release includes support for the propagation of the autograd graph in Distributed Data-Parallel (DDP) settings, enabling more efficient and scalable training of models across multiple GPUs. These enhancements collectively make TorchMetrics a more powerful and versatile tool for machine learning practitioners, enabling more accurate and efficient model evaluation across a wide range of applications.

[1.6.0] - 2024-11-12

Added

• Added audio metric NISQA (#2792)
• Added classification metric LogAUC (#2377)
• Added classification metric NegativePredictiveValue (#2433)
• Added regression metric NormalizedRootMeanSquaredError (#2442)
• Added segmentation metric Dice (#2725)
• Added method merge_state to Metric (#2786)
• Added support for propagation of the autograd graph in DDP setting (#2754)

Changed

• Changed naming and input order arguments in KLDivergence (#2800)

Deprecated

• Deprecated Dice from classification metrics (#2725)

Removed

• Changed minimum supported Pytorch version to 2.0 (#2671)
• Dropped support for Python 3.8 (#2827)
• Removed num_outputs in R2Score (#2800)

Fixed

• Fixed segmentation Dice + GeneralizedDice for 2d index tensors (#2832)
• Fixed mixed results of rouge_score with accumulate='best' (#2830)

---

Key Contributors

@​Borda, @​cw-tan, @​philgzl, @​rittik9, @​SkafteNicki

New Contributors since 1.5.0

• @​bfolie made their first contribution in Lightning-AI/torchmetrics#2793
• @​StalkerShurik made their first contribution in Lightning-AI/torchmetrics#2811
• @​philgzl made their first contribution in Lightning-AI/torchmetrics#2792
• @​cw-tan made their first contribution in Lightning-AI/torchmetrics#2754

... (truncated)

Changelog

Sourced from torchmetrics's changelog.

[1.6.0] - 2024-11-12

Added

• Added audio metric NISQA (#2792)
• Added classification metric LogAUC (#2377)
• Added classification metric NegativePredictiveValue (#2433)
• Added regression metric NormalizedRootMeanSquaredError (#2442)
• Added segmentation metric Dice (#2725)
• Added method merge_state to Metric (#2786)
• Added support for propagation of the autograd graph in ddp setting (#2754)

Changed

• Changed naming and input order arguments in KLDivergence (#2800)

Deprecated

• Deprecated Dice from classification metrics (#2725)

Removed

• Changed minimum supported Pytorch version to 2.0 (#2671)
• Dropped support for Python 3.8 (#2827)
• Removed num_outputs in R2Score (#2800)

Fixed

• Fixed segmentation Dice + GeneralizedDice for 2d index tensors (#2832)
• Fixed mixed results of rouge_score with accumulate='best' (#2830)

---

Commits

• 58147e0 releasing 1.6.0
• d73e6c1 New metric: LogAUC (#2377)
• 8f6936d Fix segmentation Dice + GeneralizedDice for 2d index tensors (#2832)
• e2543c8 build(deps): update tqdm requirement from <4.67.0 to <4.68.0 in /requirements...
• 47bd4b8 build(deps): update pygithub requirement from <2.5.0,>2.0.0 to >2.0.0,<2.6.0 ...
• bb1af09 build(deps): update regex requirement from <=2024.9.11,>=2021.9.24 to >=2021....
• 0d009de build(deps): bump pytest-cov from 5.0.0 to 6.0.0 in /requirements (#2825)
• 7147275 Fix mixed results of rouge_score with accumulate='best' (#2830)
• ea29c89 bump: drop support for python 3.8 (#2827)
• bf030e0 docs: update chlog after 1.5.2
• Additional commits viewable in compare view

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)