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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.

[0.3.1] - 2021-04-21

  • Cleaning remaining inconsistency and fix PL develop integration ( #191, #192, #193, #194 )

[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 RetrievalMAP (PL^5032)

    • Added RetrievalMRR (#119)

    • Added RetrievalPrecision (#139)

    • Added RetrievalRecall (#146)

    • Added RetrievalNormalizedDCG (#160)

    • Added RetrievalFallOut (#161)

  • Added other metrics:

    • Added CohenKappa (#69)

    • Added MatthewsCorrcoef (#98)

    • Added PearsonCorrcoef (#157)

    • Added SpearmanCorrcoef (#158)

    • Added Hinge (#120)

  • Added average='micro' as an option in AUROC for multilabel problems (#110)

  • Added multilabel support to ROC metric (#114)

  • Added testing for half precision (#77, #135 )

  • Added AverageMeter for ad-hoc averages of values (#138)

  • Added prefix argument to MetricCollection (#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 and mdmc_average in Accuracy metric (#166)

  • Added postfix arg to MetricCollection (#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 match multilabel_confusion_matrix from sklearn (#134)

  • Updated FBeta arguments (#111)

  • Changed reset method to use detach.clone() instead of deepcopy 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

  • Fixed when _stable_1d_sort to work when n>=N (PL^6177)

  • Fixed _computed attribute not being correctly reset (#147)

  • Fixed to Blau score (#165)

  • Fixed backwards compatibility for logging with older version of pytorch-lightning (#182)

[0.2.0] - 2021-03-12

[0.2.0] - Changed

  • Decoupled PL dependency (#13)

  • Refactored functional - mimic the module-like structure: classification, regression, etc. (#16)

  • Refactored utilities - split to topics/submodules (#14)

  • Refactored MetricCollection (#19)

[0.2.0] - Removed

  • Removed deprecated metrics from PL base (#12, #15)

[0.1.0] - 2021-02-22

  • Added Accuracy metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using the top_k parameter (PL^4838)

  • Added Accuracy metric now enables the computation of subset accuracy for multi-label or multi-dimensional multi-class inputs with the subset_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 and Precision metrics (and their functional counterparts recall and precision) can now be generalized to Recall@K and Precision@K with the use of top_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 to state_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 new Metrics API. (PL^3868, PL^3921)

  • Added EMB similarity (PL^3349)

  • Added SSIM metrics (PL^2671)

  • Added BLEU metrics (PL^2535)