Changelog¶
All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
Note: we move fast, but still we preserve 0.1 version (one feature release) back compatibility.
[1.0.2] - 2023-08-02¶
[1.0.2] - Added¶
Added warning to
PearsonCorrCoeff
if input has a very small variance for its given dtype (#1926)
[1.0.2] - Changed¶
Changed all non-task specific classification metrics to be true subtypes of
Metric
(#1963)
[1.0.2] - 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 inMetricCollection
andClasswiseWrapper
being duplicated (#1918)Fixed missing AUC score when plotting classification metrics that support the
score
argument (#1948)
[1.0.1] - 2023-07-13¶
[1.0.1] - Fixed¶
Fixes corner case when using
MetricCollection
together with aggregation metrics (#1896)Fixed the use of
max_fpr
inAUROC
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¶
[1.0.0] - Added¶
Added
prefix
andpostfix
arguments toClasswiseWrapper
(#1866)Added speech-to-reverberation modulation energy ratio (SRMR) metric (#1792, #1872)
Added new global arg
compute_with_cache
to control caching behaviour aftercompute
method (#1754)Added
ComplexScaleInvariantSignalNoiseRatio
for audio package (#1785)Added
Running
wrapper for calculate running statistics (#1752)Added
RelativeAverageSpectralError
andRootMeanSquaredErrorUsingSlidingWindow
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 fromMAP
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
PSNRB
metric (#1421)Added
ClassificationTask
Enum and use in metrics (#1479)Added
ignore_index
option toexact_match
metric (#1540)Add parameter
top_k
toRetrievalMAP
(#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](argument https://github.com/Lightning-AI/metrics/pull/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)
[1.0.0] - Changed¶
Changed
permutation_invariant_training
to allow using a'permutation-wise'
metric function (#1794)Changed
update_count
andupdate_called
from private to public methods (#1370)Raise exception for invalid kwargs in Metric base class (#1427)
Extend
EnumStr
raisingValueError
for invalid value (#1479)Improve speed and memory consumption of binned
PrecisionRecallCurve
with large number of samples (#1493)Changed
__iter__
method from raisingNotImplementedError
toTypeError
by setting toNone
(#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
totorch
(#1708)Changed calculation in
PearsonCorrCoeff
to be more robust in certain cases (#1729)Changed
MeanAveragePrecision
topycocotools
backend (#1832)
[1.0.0] - Deprecated¶
[1.0.0] - Removed¶
Support for python 3.7 (#1640)
[1.0.0] - Fixed¶
Fixed support in
MetricTracker
forMultioutputWrapper
and nested structures (#1608)Fixed restrictive check in
PearsonCorrCoef
(#1649)Fixed integration with
jsonargparse
andLightningCLI
(#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
foriou_type="segm"
(#1763)Fixed use of
prefix
andpostfix
in nestedMetricCollection
(#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)
[0.11.4] - 2023-03-10¶
[0.11.4] - Fixed¶
Fixed evaluation of
R2Score
with near constant target (#1576)Fixed dtype conversion when metric is submodule (#1583)
Fixed bug related to
top_k>1
andignore_index!=None
inStatScores
based metrics (#1589)Fixed corner case for
PearsonCorrCoef
when running in ddp mode but only on single device (#1587)Fixed overflow error for specific cases in
MAP
when big areas are calculated (#1607)
[0.11.3] - 2023-02-28¶
[0.11.3] - Fixed¶
[0.11.2] - 2023-02-21¶
[0.11.2] - Fixed¶
[0.11.1] - 2023-01-30¶
[0.11.1] - Fixed¶
Fixed type checking on the
maximize
parameter at the initialization ofMetricTracker
(#1428)Fixed mixed precision autocast for
SSIM
metric (#1454)Fixed checking for
nltk.punkt
inRougeScore
if a machine is not online (#1456)Fixed wrongly reset method in
MultioutputWrapper
(#1460)Fixed dtype checking in
PrecisionRecallCurve
fortarget
tensor (#1457)
[0.11.0] - 2022-11-30¶
[0.11.0] - Added¶
Added
MulticlassExactMatch
to classification metrics (#1343)Added
TotalVariation
to image package (#978)Added
CLIPScore
to new multimodal package (#1314)Added regression metrics:
Added new nominal metrics:
Added option to pass
distributed_available_fn
to metrics to allow checks for custom communication backend for makingdist_sync_fn
actually useful (#1301)Added
normalize
argument toInception
,FID
,KID
metrics (#1246)
[0.11.0] - Changed¶
[0.11.0] - Removed¶
[0.11.0] - Fixed¶
Fixed precision bug in
pairwise_euclidean_distance
(#1352)
[0.10.3] - 2022-11-16¶
[0.10.3] - Fixed¶
[0.10.2] - 2022-10-31¶
[0.10.2] - Changed¶
Changed in-place operation to out-of-place operation in
pairwise_cosine_similarity
(#1288)
[0.10.2] - Fixed¶
Fixed high memory usage for certain classification metrics when
average='micro'
(#1286)Fixed precision problems when
structural_similarity_index_measure
was used with autocast (#1291)Fixed slow performance for confusion matrix based metrics (#1302)
Fixed restrictive dtype checking in
spearman_corrcoef
when used with autocast (#1303)
[0.10.1] - 2022-10-21¶
[0.10.1] - Fixed¶
[0.10.0] - 2022-10-04¶
[0.10.0] - Added¶
Added a new NLP metric
InfoLM
(#915)Added
Perplexity
metric (#922)Added
ConcordanceCorrCoef
metric to regression package (#1201)Added argument
normalize
toLPIPS
metric (#1216)Added support for multiprocessing of batches in
PESQ
metric (#1227)Added support for multioutput in
PearsonCorrCoef
andSpearmanCorrCoef
(#1200)
[0.10.0] - Changed¶
Classification refactor ( #1054, #1143, #1145, #1151, #1159, #1163, #1167, #1175, #1189, #1197, #1215, #1195 )
Changed update in
FID
metric to be done in online fashion to save memory (#1199)Improved performance of retrieval metrics (#1242)
Changed
SSIM
andMSSSIM
update to be online to reduce memory usage (#1231)
[0.10.0] - Deprecated¶
Deprecated
BinnedAveragePrecision
,BinnedPrecisionRecallCurve
,BinnedRecallAtFixedPrecision
(#1163)BinnedAveragePrecision
-> useAveragePrecision
withthresholds
argBinnedPrecisionRecallCurve
-> useAveragePrecisionRecallCurve
withthresholds
argBinnedRecallAtFixedPrecision
-> useRecallAtFixedPrecision
withthresholds
arg
Renamed and refactored
LabelRankingAveragePrecision
,LabelRankingLoss
andCoverageError
(#1167)LabelRankingAveragePrecision
->MultilabelRankingAveragePrecision
LabelRankingLoss
->MultilabelRankingLoss
CoverageError
->MultilabelCoverageError
Deprecated
KLDivergence
andAUC
from classification package (#1189)KLDivergence
moved toregression
packageInstead of
AUC
usetorchmetrics.utils.compute.auc
[0.10.0] - Fixed¶
[0.9.3] - 2022-08-22¶
[0.9.3] - Added¶
Added global option
sync_on_compute
to disable automatic synchronization whencompute
is called (#1107)
[0.9.3] - Fixed¶
[0.9.2] - 2022-06-29¶
[0.9.2] - Fixed¶
Fixed mAP calculation for areas with 0 predictions (#1080)
Fixed bug where avg precision state and auroc state was not merge when using MetricCollections (#1086)
Skip box conversion if no boxes are present in
MeanAveragePrecision
(#1097)Fixed inconsistency in docs and code when setting
average="none"
inAvaragePrecision
metric (#1116)
[0.9.1] - 2022-06-08¶
[0.9.1] - Added¶
[0.9.1] - Fixed¶
[0.9.0] - 2022-05-30¶
[0.9.0] - Added¶
Added
RetrievalPrecisionRecallCurve
andRetrievalRecallAtFixedPrecision
to retrieval package (#951)Added class property
full_state_update
that determinesforward
should callupdate
once or twice ( #984, #1033)Added support for nested metric collections (#1003)
Added
Dice
to classification package (#1021)Added support to segmentation type
segm
as IOU for mean average precision (#822)
[0.9.0] - Changed¶
Renamed
reduction
argument toaverage
in Jaccard score and added additional options (#874)
[0.9.0] - Removed¶
[0.9.0] - Fixed¶
Fixed non-empty state dict for a few metrics (#1012)
Fixed bug when comparing states while finding compute groups (#1022)
Fixed
torch.double
support in stat score metrics (#1023)Fixed
FID
calculation for non-equal size real and fake input (#1028)Fixed case where
KLDivergence
could outputNan
(#1030)Fixed deterministic for PyTorch<1.8 (#1035)
Fixed default value for
mdmc_average
inAccuracy
(#1036)Fixed missing copy of property when using compute groups in
MetricCollection
(#1052)
[0.8.2] - 2022-05-06¶
[0.8.2] - Fixed¶
[0.8.1] - 2022-04-27¶
[0.8.1] - Changed¶
Reimplemented the
signal_distortion_ratio
metric, which removed the absolute requirement offast-bss-eval
(#964)
[0.8.1] - Fixed¶
[0.8.0] - 2022-04-14¶
[0.8.0] - Added¶
Added
WeightedMeanAbsolutePercentageError
to regression package (#948)Added new classification metrics:
Added new image metric:
Added support for
MetricCollection
inMetricTracker
(#718)Added support for 3D image and uniform kernel in
StructuralSimilarityIndexMeasure
(#818)Added smart update of
MetricCollection
(#709)Added
ClasswiseWrapper
for better logging of classification metrics with multiple output values (#832)Added
**kwargs
argument for passing additional arguments to base class (#833)Added negative
ignore_index
for the Accuracy metric (#362)Added
adaptive_k
for theRetrievalPrecision
metric (#910)Added
reset_real_features
argument image quality assessment metrics (#722)Added new keyword argument
compute_on_cpu
to all metrics (#867)
[0.8.0] - Changed¶
Made
num_classes
injaccard_index
a required argument (#853, #914)Added normalizer, tokenizer to ROUGE metric (#838)
Improved shape checking of
permutation_invariant_training
(#864)Allowed reduction
None
(#891)MetricTracker.best_metric
will now give a warning when computing on metric that do not have a best (#913)
[0.8.0] - Deprecated¶
[0.8.0] - Removed¶
Removed support for versions of Pytorch-Lightning lower than v1.5 (#788)
Removed deprecated functions, and warnings in Text (#773)
WER
andfunctional.wer
Removed deprecated functions and warnings in Image (#796)
SSIM
andfunctional.ssim
PSNR
andfunctional.psnr
Removed deprecated functions, and warnings in classification and regression (#806)
FBeta
andfunctional.fbeta
F1
andfunctional.f1
Hinge
andfunctional.hinge
IoU
andfunctional.iou
MatthewsCorrcoef
PearsonCorrcoef
SpearmanCorrcoef
Removed deprecated functions, and warnings in detection and pairwise (#804)
MAP
andfunctional.pairwise.manhatten
Removed deprecated functions, and warnings in Audio (#805)
PESQ
andfunctional.audio.pesq
PIT
andfunctional.audio.pit
SDR
andfunctional.audio.sdr
andfunctional.audio.si_sdr
SNR
andfunctional.audio.snr
andfunctional.audio.si_snr
STOI
andfunctional.audio.stoi
Removed unused
get_num_classes
fromtorchmetrics.utilities.data
(#914)
[0.8.0] - Fixed¶
[0.7.3] - 2022-03-23¶
[0.7.3] - Fixed¶
Fixed unsafe log operation in
TweedieDeviace
for power=1 (#847)Fixed bug in MAP metric related to either no ground truth or no predictions (#884)
Fixed
ConfusionMatrix
,AUROC
andAveragePrecision
on GPU when running in deterministic mode (#900)Fixed NaN or Inf results returned by
signal_distortion_ratio
(#899)Fixed memory leak when using
update
method with tensor whererequires_grad=True
(#902)
[0.7.2] - 2022-02-10¶
[0.7.2] - Fixed¶
Minor patches in JOSS paper.
[0.7.1] - 2022-02-03¶
[0.7.1] - Changed¶
[0.7.1] - Fixed¶
[0.7.0] - 2022-01-17¶
[0.7.0] - Added¶
Added NLP metrics:
Added
MultiScaleSSIM
into image metrics (#679)Added Signal to Distortion Ratio (
SDR
) to audio package (#565)Added
MinMaxMetric
to wrappers (#556)Added
ignore_index
to retrieval metrics (#676)Added support for multi references in
ROUGEScore
(#680)Added a default VSCode devcontainer configuration (#621)
[0.7.0] - Changed¶
Scalar metrics will now consistently have additional dimensions squeezed (#622)
Metrics having third party dependencies removed from global import (#463)
Untokenized for
BLEUScore
input stay consistent with all the other text metrics (#640)Arguments reordered for
TER
,BLEUScore
,SacreBLEUScore
,CHRFScore
now expect input order as predictions first and target second (#696)Changed dtype of metric state from
torch.float
totorch.long
inConfusionMatrix
to accommodate larger values (#715)Unify
preds
,target
input argument’s naming across all text metrics (#723, #727)bert
,bleu
,chrf
,sacre_bleu
,wip
,wil
,cer
,ter
,wer
,mer
,rouge
,squad
[0.7.0] - Deprecated¶
Renamed IoU -> Jaccard Index (#662)
Renamed text WER metric (#714)
functional.wer
->functional.word_error_rate
WER
->WordErrorRate
Renamed correlation coefficient classes: (#710)
MatthewsCorrcoef
->MatthewsCorrCoef
PearsonCorrcoef
->PearsonCorrCoef
SpearmanCorrcoef
->SpearmanCorrCoef
Renamed audio STOI metric: (#753, #758)
audio.STOI
toaudio.ShortTimeObjectiveIntelligibility
functional.audio.stoi
tofunctional.audio.short_time_objective_intelligibility
Renamed audio PESQ metrics: (#751)
functional.audio.pesq
->functional.audio.perceptual_evaluation_speech_quality
audio.PESQ
->audio.PerceptualEvaluationSpeechQuality
Renamed audio SDR metrics: (#711)
functional.sdr
->functional.signal_distortion_ratio
functional.si_sdr
->functional.scale_invariant_signal_distortion_ratio
SDR
->SignalDistortionRatio
SI_SDR
->ScaleInvariantSignalDistortionRatio
Renamed audio SNR metrics: (#712)
functional.snr
->functional.signal_distortion_ratio
functional.si_snr
->functional.scale_invariant_signal_noise_ratio
SNR
->SignalNoiseRatio
SI_SNR
->ScaleInvariantSignalNoiseRatio
Renamed F-score metrics: (#731, #740)
functional.f1
->functional.f1_score
F1
->F1Score
functional.fbeta
->functional.fbeta_score
FBeta
->FBetaScore
Renamed Hinge metric: (#734)
functional.hinge
->functional.hinge_loss
Hinge
->HingeLoss
Renamed image PSNR metrics (#732)
functional.psnr
->functional.peak_signal_noise_ratio
PSNR
->PeakSignalNoiseRatio
Renamed image PIT metric: (#737)
functional.pit
->functional.permutation_invariant_training
PIT
->PermutationInvariantTraining
Renamed image SSIM metric: (#747)
functional.ssim
->functional.scale_invariant_signal_noise_ratio
SSIM
->StructuralSimilarityIndexMeasure
Renamed detection
MAP
toMeanAveragePrecision
metric (#754)Renamed Fidelity & LPIPS image metric: (#752)
image.FID
->image.FrechetInceptionDistance
image.KID
->image.KernelInceptionDistance
image.LPIPS
->image.LearnedPerceptualImagePatchSimilarity
[0.7.0] - Removed¶
[0.7.0] - Fixed¶
Fixed MetricCollection kwargs filtering when no
kwargs
are present in update signature (#707)
[0.6.2] - 2021-12-15¶
[0.6.2] - Fixed¶
[0.6.1] - 2021-12-06¶
[0.6.1] - Changed¶
[0.6.1] - Fixed¶
[0.6.0] - 2021-10-28¶
[0.6.0] - Added¶
Added audio metrics:
Added Information retrieval metrics:
Added NLP metrics:
Added other metrics:
Added
MAP
(mean average precision) metric to new detection package (#467)Added support for float targets in
nDCG
metric (#437)Added
average
argument toAveragePrecision
metric for reducing multi-label and multi-class problems (#477)Added
MultioutputWrapper
(#510)Added metric sweeping:
Added simple aggregation metrics:
SumMetric
,MeanMetric
,CatMetric
,MinMetric
,MaxMetric
(#506)Added pairwise submodule with metrics (#553)
pairwise_cosine_similarity
pairwise_euclidean_distance
pairwise_linear_similarity
pairwise_manhatten_distance
[0.6.0] - Changed¶
AveragePrecision
will now as default output themacro
average for multilabel and multiclass problems (#477)half
,double
,float
will no longer change the dtype of the metric states. Usemetric.set_dtype
instead (#493)Renamed
AverageMeter
toMeanMetric
(#506)Changed
is_differentiable
from property to a constant attribute (#551)ROC
andAUROC
will no longer throw an error when either the positive or negative class is missing. Instead return 0 score and give a warning
[0.6.0] - Deprecated¶
Deprecated
functional.self_supervised.embedding_similarity
in favour of new pairwise submodule
[0.6.0] - Removed¶
Removed
dtype
property (#493)
[0.6.0] - Fixed¶
Fixed bug in
F1
withaverage='macro'
andignore_index!=None
(#495)Fixed bug in
pit
by using the returned first result to initialize device and type (#533)Fixed
SSIM
metric using too much memory (#539)Fixed bug where
device
property was not properly update when metric was a child of a module (#542)
[0.5.1] - 2021-08-30¶
[0.5.1] - Added¶
[0.5.1] - Changed¶
Added support for float targets in
nDCG
metric (#437)
[0.5.1] - Removed¶
[0.5.1] - Fixed¶
Fixed ranking of samples in
SpearmanCorrCoef
metric (#448)Fixed bug where compositional metrics where unable to sync because of type mismatch (#454)
Fixed metric hashing (#478)
Fixed
BootStrapper
metrics not working on GPU (#462)Fixed the semantic ordering of kernel height and width in
SSIM
metric (#474)
[0.5.0] - 2021-08-09¶
[0.5.0] - Added¶
Added Text-related (NLP) metrics:
Added
MetricTracker
wrapper metric for keeping track of the same metric over multiple epochs (#238)Added other metrics:
Added support in
nDCG
metric for target with values larger than 1 (#349)Added support for negative targets in
nDCG
metric (#378)Added
None
as reduction option inCosineSimilarity
metric (#400)Allowed passing labels in (n_samples, n_classes) to
AveragePrecision
(#386)
[0.5.0] - Changed¶
Moved
psnr
andssim
fromfunctional.regression.*
tofunctional.image.*
(#382)Moved
image_gradient
fromfunctional.image_gradients
tofunctional.image.gradients
(#381)Moved
R2Score
fromregression.r2score
toregression.r2
(#371)Pearson metric now only store 6 statistics instead of all predictions and targets (#380)
Use
torch.argmax
instead oftorch.topk
whenk=1
for better performance (#419)Moved check for number of samples in R2 score to support single sample updating (#426)
[0.5.0] - Deprecated¶
[0.5.0] - Removed¶
Removed restriction that
threshold
has to be in (0,1) range to support logit input ( #351 #401)Removed restriction that
preds
could not be bigger thannum_classes
to support logit input (#357)Removed module
regression.psnr
andregression.ssim
(#382):Removed (#379):
function
functional.mean_relative_error
num_thresholds
argument inBinnedPrecisionRecallCurve
[0.5.0] - Fixed¶
Fixed bug where classification metrics with
average='macro'
would lead to wrong result if a class was missing (#303)Fixed
weighted
,multi-class
AUROC computation to allow for 0 observations of some class, as contribution to final AUROC is 0 (#376)Fixed that
_forward_cache
and_computed
attributes are also moved to the correct device if metric is moved (#413)Fixed calculation in
IoU
metric when usingignore_index
argument (#328)
[0.4.1] - 2021-07-05¶
[0.4.1] - Changed¶
[0.4.1] - Fixed¶
Fixed DDP by
is_sync
logic toMetric
(#339)
[0.4.0] - 2021-06-29¶
[0.4.0] - Added¶
Added Image-related metrics:
Added Audio metrics: SNR, SI_SDR, SI_SNR (#292)
Added other metrics:
Added
add_metrics
method toMetricCollection
for adding additional metrics after initialization (#221)Added pre-gather reduction in the case of
dist_reduce_fx="cat"
to reduce communication cost (#217)Added better error message for
AUROC
whennum_classes
is not provided for multiclass input (#244)Added support for unnormalized scores (e.g. logits) in
Accuracy
,Precision
,Recall
,FBeta
,F1
,StatScore
,Hamming
,ConfusionMatrix
metrics (#200)Added
squared
argument toMeanSquaredError
for computingRMSE
(#249)Added
is_differentiable
property toConfusionMatrix
,F1
,FBeta
,Hamming
,Hinge
,IOU
,MatthewsCorrcoef
,Precision
,Recall
,PrecisionRecallCurve
,ROC
,StatScores
(#253)Added
sync
andsync_context
methods for manually controlling when metric states are synced (#302)
[0.4.0] - Changed¶
Forward cache is reset when
reset
method is called (#260)Improved per-class metric handling for imbalanced datasets for
precision
,recall
,precision_recall
,fbeta
,f1
,accuracy
, andspecificity
(#204)Decorated
torch.jit.unused
toMetricCollection
forward (#307)Renamed
thresholds
argument to binned metrics for manually controlling the thresholds (#322)
[0.4.0] - Deprecated¶
[0.4.0] - Removed¶
Removed argument
is_multiclass
(#319)
[0.4.0] - Fixed¶
[0.3.2] - 2021-05-10¶
[0.3.2] - Added¶
[0.3.2] - Changed¶
[0.3.2] - Removed¶
Removed
numpy
as direct dependency (#212)
[0.3.2] - Fixed¶
Fixed auc calculation and add tests (#197)
Fixed loading persisted metric states using
load_state_dict()
(#202)Fixed
PSNR
not working withDDP
(#214)Fixed metric calculation with unequal batch sizes (#220)
Fixed metric concatenation for list states for zero-dim input (#229)
Fixed numerical instability in
AUROC
metric for large input (#230)
[0.3.1] - 2021-04-21¶
[0.3.0] - 2021-04-20¶
[0.3.0] - Added¶
Added
BootStrapper
to easily calculate confidence intervals for metrics (#101)Added Binned metrics (#128)
Added metrics for Information Retrieval ((PL^5032)):
Added other metrics:
Added
average='micro'
as an option in AUROC for multilabel problems (#110)Added multilabel support to
ROC
metric (#114)Added
AverageMeter
for ad-hoc averages of values (#138)Added
prefix
argument toMetricCollection
(#70)Added
__getitem__
as metric arithmetic operation (#142)Added property
is_differentiable
to metrics and test for differentiability (#154)Added support for
average
,ignore_index
andmdmc_average
inAccuracy
metric (#166)Added
postfix
arg toMetricCollection
(#188)
[0.3.0] - Changed¶
Changed
ExplainedVariance
from storing all preds/targets to tracking 5 statistics (#68)Changed behaviour of
confusionmatrix
for multilabel data to better matchmultilabel_confusion_matrix
from sklearn (#134)Updated FBeta arguments (#111)
Changed
reset
method to usedetach.clone()
instead ofdeepcopy
when resetting to default (#163)Metrics passed as dict to
MetricCollection
will now always be in deterministic order (#173)Allowed
MetricCollection
pass metrics as arguments (#176)
[0.3.0] - Deprecated¶
Rename argument
is_multiclass
->multiclass
(#162)
[0.3.0] - Removed¶
Prune remaining deprecated (#92)
[0.3.0] - Fixed¶
[0.2.0] - 2021-03-12¶
[0.2.0] - Changed¶
[0.2.0] - Removed¶
[0.1.0] - 2021-02-22¶
Added
Accuracy
metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using thetop_k
parameter (PL^4838)Added
Accuracy
metric now enables the computation of subset accuracy for multi-label or multi-dimensional multi-class inputs with thesubset_accuracy
parameter (PL^4838)Added
HammingDistance
metric to compute the hamming distance (loss) (PL^4838)Added
StatScores
metric to compute the number of true positives, false positives, true negatives and false negatives (PL^4839)Added
R2Score
metric (PL^5241)Added
MetricCollection
(PL^4318)Added
.clone()
method to metrics (PL^4318)Added
IoU
class interface (PL^4704)The
Recall
andPrecision
metrics (and their functional counterpartsrecall
andprecision
) can now be generalized to Recall@K and Precision@K with the use oftop_k
parameter (PL^4842)Added compositional metrics (PL^5464)
Added AUC/AUROC class interface (PL^5479)
Added
QuantizationAwareTraining
callback (PL^5706)Added
ConfusionMatrix
class interface (PL^4348)Added multiclass AUROC metric (PL^4236)
Added
PrecisionRecallCurve, ROC, AveragePrecision
class metric (PL^4549)Classification metrics overhaul (PL^4837)
Added
F1
class metric (PL^4656)Added metrics aggregation in Horovod and fixed early stopping (PL^3775)
Added
persistent(mode)
method to metrics, to enable and disable metric states being added tostate_dict
(PL^4482)Added unification of regression metrics (PL^4166)
Added persistent flag to
Metric.add_state
(PL^4195)Added classification metrics (PL^4043)
Added EMB similarity (PL^3349)
Added SSIM metrics (PL^2671)
Added BLEU metrics (PL^2535)