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@Borda Borda released this 05 Jul 08:54
· 943 commits to master since this release
v1.0.0
ef1af35

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).

The basic interface is the same for any metric. Just call the new .plot method:

metric = AnyMetricYouLike()
for _ in range(num_updates):
    metric.update(preds[i], target[i])
fig, ax = metric.plot()

The plot method by default does not require any arguments and will automatically call metric.compute internally on
whatever metric states have been accumulated.

[1.0.0] - 2022-07-04

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, #1621, #1624, #1623, #1638, #1631, #1650, #1639, #1660, #1682, #1786)
  • Added support for plotting of audio metrics through .plot() method (#1434)
  • Added classes to output from MAP metric (#1419)
  • Added Binary group fairness metrics to classification package (#1404)
  • Added MinkowskiDistance to regression package (#1362)
  • Added pairwise_minkowski_distance to pairwise package (#1362)
  • Added new detection metric PanopticQuality (#929, #1527)
  • Added PSNRB metric (#1421)
  • Added ClassificationTask Enum and use in metrics (#1479)
  • Added ignore_index option to exact_match metric (#1540)
  • Add parameter top_k to RetrievalMAP (#1501)
  • Added support for deterministic evaluation on GPU for metrics that uses torch.cumsum operator (#1499)
  • Added support for plotting of aggregation metrics through .plot() method (#1485)
  • Added support for python 3.11 (#1612)
  • Added support for auto clamping of input for metrics that uses the data_range (#1606)
  • Added ModifiedPanopticQuality metric to detection package (#1627)
  • Added PrecisionAtFixedRecall metric to classification package (#1683)
  • Added multiple metrics to detection package (#1284)
    • IntersectionOverUnion
    • GeneralizedIntersectionOverUnion
    • CompleteIntersectionOverUnion
    • DistanceIntersectionOverUnion
  • Added MultitaskWrapper to wrapper package (#1762)
  • Added RelativeSquaredError metric to regression package (#1765)
  • Added MemorizationInformedFrechetInceptionDistance metric to image package (#1580)

Changed

  • Changed permutation_invariant_training to allow using a 'permutation-wise' metric function (#1794)
  • Changed update_count and update_called from private to public methods (#1370)
  • Raise exception for invalid kwargs in Metric base class (#1427)
  • Extend EnumStr raising ValueError for invalid value (#1479)
  • Improve speed and memory consumption of binned PrecisionRecallCurve with large number of samples (#1493)
  • Changed __iter__ method from raising NotImplementedError to TypeError by setting to None (#1538)
  • FID metric will now raise an error if too few samples are provided (#1655)
  • Allowed FID with torch.float64 (#1628)
  • Changed LPIPS implementation to no more rely on third-party package (#1575)
  • Changed FID matrix square root calculation from scipy to torch (#1708)
  • Changed calculation in PearsonCorrCoeff to be more robust in certain cases (#1729)
  • Changed MeanAveragePrecision to pycocotools backend (#1832)

Deprecated

Removed

  • Support for python 3.7 (#1640)

Fixed

  • Fixed support in MetricTracker for MultioutputWrapper and nested structures (#1608)
  • Fixed restrictive check in PearsonCorrCoef (#1649)
  • Fixed integration with jsonargparse and LightningCLI (#1651)
  • Fixed corner case in calibration error for zero confidence input (#1648)
  • Fix precision-recall curve based computations for float target (#1642)
  • Fixed missing kwarg squeeze in MultiOutputWrapper (#1675)
  • Fixed padding removal for 3d input in MSSSIM (#1674)
  • Fixed max_det_threshold in MAP detection (#1712)
  • Fixed states being saved in metrics that use register_buffer (#1728)
  • Fixed states not being correctly synced and device transfered in MeanAveragePrecision for iou_type="segm" (#1763)
  • Fixed use of prefix and postfix in nested MetricCollection (#1773)
  • Fixed ax plotting logging in `MetricCollection (#1783)
  • Fixed lookup for punkt sources being downloaded in RougeScore (#1789)
  • Fixed integration with lightning for CompositionalMetric (#1761)
  • Fixed several bugs in SpectralDistortionIndex metric (#1808)
  • Fixed bug for corner cases in MatthewsCorrCoef (#1812, #1863)
  • Fixed support for half precision in PearsonCorrCoef (#1819)
  • Fixed number of bugs related to average="macro" in classification metrics (#1821)
  • Fixed off-by-one issue when ignore_index = num_classes + 1 in Multiclass-jaccard (#1860)

New Contributors

Contributors

@alexkrz, @AndresAlgaba, @basveeling, @Bomme, @Borda, @Callidior, @clueless-skywatcher, @Dibz15, @EPronovost, @fkroeber, @ItamarChinn, @marcocaccin, @martinmeinke, @niberger, @Piyush-97, @quancs, @relativityhd, @shenoynikhil, @shhs29, @SkafteNicki, @soma2000-lang, @srishti-git1110, @stancld, @twsl, @ValerianRey, @venomouscyanide, @wbeardall

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

Contributors

basveeling, goldenfire6, and 48 other contributors
Assets 4
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