build(deps): bump torchmetrics from 0.9.1 to 1.6.1 in /tests/e2e

[dependabot]

Bumps torchmetrics from 0.9.1 to 1.6.1.

Release notes

Sourced from torchmetrics's releases.

Minor patch release

[1.6.1] - 2024-12-25

Changed

• Enabled specifying weights path for FID (#2867)
• Delete Device2Host caused by comm with device and host (#2840)

Fixed

• Fixed plotting of multilabel confusion matrix (#2858)
• Fixed issue with shared state in metric collection when using dice score (#2848)
• Fixed top_k for multiclassf1score with one-hot encoding (#2839)
• Fixed slow calculations of classification metrics with MPS (#2876)

---

Key Contributors

@​Isalia20, @​nkaenzig, @​podgorki, @​rittik9, @​yuvalkirstain, @​zhaozheng09

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

---

Full Changelog: Lightning-AI/torchmetrics@v1.6.0...v1.6.1

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

... (truncated)

Changelog

Sourced from torchmetrics's changelog.

[1.6.1] - 2024-12-24

Changed

• Enabled specifying weights path for FID (#2867)
• Delete Device2Host caused by comm with device and host (#2840)

Fixed

• Fixed plotting of multilabel confusion matrix (#2858)
• Fixed issue with shared state in metric collection when using dice score (#2848)
• Fixed top_k for multiclassf1score with one-hot encoding (#2839)
• Fixed slow calculations of classification metrics with MPS (#2876)

[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)

---

[1.5.2] - 2024-11-07

... (truncated)

Commits

• 07224d3 releasing 1.6.1
• 8b47970 Revert "build(deps): update transformers requirement from <4.47.0,>4.4.0 to >...
• 7bda8f7 build(deps): bump mypy from 1.13.0 to 1.14.0 in /requirements (#2880)
• aca022a build(deps): update lightning requirement from <2.5.0,>=1.8.0 to >=1.8.0,<2.6...
• 6ba395d fix slow calculations of classification metrics (#2876)
• 4d9c843 Fix top_k for multiclass-f1score (#2839)
• 8827e64 Bugfix so multilabel confusion matrix can plot for 2 or more labels (#2858)
• a7284e2 enable specifying weights path for fid (#2867)
• 3ff199c Delete Device2Host caused by comm with device and host (#2840)
• b9ab4bc bump: testing with next PyTorch 2.6 (#2836)
• 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)

[openshift-ci]

[APPROVALNOTIFIER] This PR is APPROVED

Approval requirements bypassed by manually added approval.

This pull-request has been approved by:

The full list of commands accepted by this bot can be found here.

The pull request process is described here

Needs approval from an approver in each of these files:

• OWNERS

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

[dependabot]

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version. You can also ignore all major, minor, or patch releases for a dependency by adding an ignore condition with the desired update_types to your config file.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.