build(deps): bump torchmetrics from 0.9.2 to 1.0.2

[dependabot]

Bumps torchmetrics from 0.9.2 to 1.0.2.

Release notes

Sourced from torchmetrics's releases.

Weekly patch release

[1.0.2] - 2022-08-03

Added

• Added warning to PearsonCorrCoeff if input has a very small variance for its given dtype (#1926)

Changed

• Changed all non-task specific classification metrics to be true subtypes of Metric (#1963)

Fixed

• Fixed bug in CalibrationError where calculations for double precision input was performed in float precision (#1919)
• Fixed bug related to the prefix/postfix arguments in MetricCollection and ClasswiseWrapper being duplicated (#1918)
• Fixed missing AUC score when plotting classification metrics that support the score argument (#1948)

Contributors

@​borda, @​SkafteNicki^n

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

Weekly patch release

[1.0.1] - 2022-07-13

Fixed

• Fixes corner case when using MetricCollection together with aggregation metrics (#1896)
• Fixed the use of max_fpr in AUROC metric when only one class is present (#1895)
• Fixed bug related to empty predictions for IntersectionOverUnion metric (#1892)
• Fixed bug related to MeanMetric and broadcasting of weights when Nans are present (#1898)
• Fixed bug related to expected input format of pycoco in MeanAveragePrecision (#1913)

Contributors

@​fansuregrin, @​SkafteNicki

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

Visualize metrics

We are happy to announce that the first major release of Torchmetrics, version v1.0, is publicly available. We have worked hard on a couple of new features for this milestone release, but for v1.0.0, we have also managed to implement over 100 metrics in torchmetrics.

Plotting

The big new feature of v1.0 is a built-in plotting feature. As the old saying goes: "A picture is worth a thousand words". Within machine learning, this is definitely also true for many things. Metrics are one area that, in some cases, is definitely better showcased in a figure than as a list of floats. The only requirement for getting started with the plotting feature is installing matplotlib. Either install with pip install matplotlib or pip install torchmetrics[visual] (the latter option also installs Scienceplots and uses that as the default plotting style).

... (truncated)

Changelog

Sourced from torchmetrics's changelog.

[1.0.2] - 2023-08-02

Added

• Added warning to PearsonCorrCoeff if input has a very small variance for its given dtype (#1926)

Changed

• Changed all non-task specific classification metrics to be true subtypes of Metric (#1963)

Fixed

• Fixed bug in CalibrationError where calculations for double precision input was performed in float precision (#1919)
• Fixed bug related to the prefix/postfix arguments in MetricCollection and ClasswiseWrapper being duplicated (#1918)
• Fixed missing AUC score when plotting classification metrics that support the score argument (#1948)

[1.0.1] - 2023-07-13

Fixed

• Fixes corner case when using MetricCollection together with aggregation metrics (#1896)
• Fixed the use of max_fpr in AUROC metric when only one class is present (#1895)
• Fixed bug related to empty predictions for IntersectionOverUnion metric (#1892)
• Fixed bug related to MeanMetric and broadcasting of weights when Nans are present (#1898)
• Fixed bug related to expected input format of pycoco in MeanAveragePrecision (#1913)

[1.0.0] - 2023-07-04

Added

• Added prefix and postfix arguments to ClasswiseWrapper (#1866)
• Added speech-to-reverberation modulation energy ratio (SRMR) metric (#1792, #1872)
• Added new global arg compute_with_cache to control caching behaviour after compute method (#1754)
• Added ComplexScaleInvariantSignalNoiseRatio for audio package (#1785)
• Added Running wrapper for calculate running statistics (#1752)
• AddedRelativeAverageSpectralError and RootMeanSquaredErrorUsingSlidingWindow to image package (#816)
• Added support for SpecificityAtSensitivity Metric (#1432)
• Added support for plotting of metrics through .plot() method ( #1328, #1481, #1480, #1490, #1581, #1585, #1593, #1600, #1605, #1610, #1609,

... (truncated)

Commits

• 81fe19c releasing 1.0.2
• 0652d66 Convert classification wrapper to metrics (#1963)
• 5494811 docs: revert links in gallery & adjust img/icon path (#1964)
• b82df5e Fix missing AUC score when plotting (#1948)
• 97eb3f6 build(deps): bump pypa/gh-action-pypi-publish from 1.8.7 to 1.8.8 (#1967)
• 84fc622 building docs with py3.9 (#1958)
• a12ad99 revert sphinx to 5.3 to recover icon with anchor links (#1956)
• d601498 docs: remove empty (,,,) from plots docstrings (#1965)
• e4cf2e7 Fix AttributeError: module 'matplotlib' has no attribute 'axes' (#1955)
• aae4a64 Revert "docs: resolving relative path to images (#1930)"
• Additional commits viewable in compare view

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[dependabot]

Superseded by #47.