Code cleaning after classification refactor 1/n

CHANGELOG.md

@@ -26,7 +26,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Removed
 
--
+- Removed deprecated classification code ([#1251](https://github.com/Lightning-AI/metrics/pull/1251))
 
 
 ### Fixed

docs/source/classification/coverage_error.rst

@@ -10,17 +10,11 @@ Coverage Error
 Module Interface
 ________________
 
-.. autoclass:: torchmetrics.CoverageError
- :noindex:
-
 .. autoclass:: torchmetrics.classification.MultilabelCoverageError
  :noindex:
 
 Functional Interface
 ____________________
 
-.. autofunction:: torchmetrics.functional.coverage_error
- :noindex:
-
 .. autofunction:: torchmetrics.functional.classification.multilabel_coverage_error
  :noindex:

docs/source/classification/label_ranking_average_precision.rst

@@ -10,18 +10,12 @@ Label Ranking Average Precision
 Module Interface
 ________________
 
-.. autoclass:: torchmetrics.LabelRankingAveragePrecision
- :noindex:
-
 .. autoclass:: torchmetrics.classification.MultilabelRankingAveragePrecision
  :noindex:
 
 
 Functional Interface
 ____________________
 
-.. autofunction:: torchmetrics.functional.label_ranking_average_precision
- :noindex:
-
 .. autofunction:: torchmetrics.functional.classification.multilabel_ranking_average_precision
  :noindex:

docs/source/classification/label_ranking_loss.rst

@@ -10,18 +10,11 @@ Label Ranking Loss
 Module Interface
 ________________
 
-.. autoclass:: torchmetrics.LabelRankingLoss
- :noindex:
-
-
 .. autoclass:: torchmetrics.classification.MultilabelRankingLoss
  :noindex:
 
 Functional Interface
 ____________________
 
-.. autofunction:: torchmetrics.functional.label_ranking_loss
- :noindex:
-
 .. autofunction:: torchmetrics.functional.classification.multilabel_ranking_loss
  :noindex:

src/torchmetrics/__init__.py

@@ -21,26 +21,19 @@
  SignalNoiseRatio,
 )
 from torchmetrics.classification import ( # noqa: E402
- AUC,
  AUROC,
  ROC,
  Accuracy,
  AveragePrecision,
- BinnedAveragePrecision,
- BinnedPrecisionRecallCurve,
- BinnedRecallAtFixedPrecision,
  CalibrationError,
  CohenKappa,
  ConfusionMatrix,
- CoverageError,
  Dice,
  F1Score,
  FBetaScore,
  HammingDistance,
  HingeLoss,
  JaccardIndex,
- LabelRankingAveragePrecision,
- LabelRankingLoss,
  MatthewsCorrCoef,
  Precision,
  PrecisionRecallCurve,
@@ -113,12 +106,8 @@
 __all__ = [
  "functional",
  "Accuracy",
- "AUC",
  "AUROC",
  "AveragePrecision",
- "BinnedAveragePrecision",
- "BinnedPrecisionRecallCurve",
- "BinnedRecallAtFixedPrecision",
  "BLEUScore",
  "BootStrapper",
  "CalibrationError",
@@ -130,7 +119,6 @@
  "CohenKappa",
  "ConfusionMatrix",
  "CosineSimilarity",
- "CoverageError",
  "Dice",
  "TweedieDevianceScore",
  "ErrorRelativeGlobalDimensionlessSynthesis",
@@ -142,8 +130,6 @@
  "HingeLoss",
  "JaccardIndex",
  "KLDivergence",
- "LabelRankingAveragePrecision",
- "LabelRankingLoss",
  "MatchErrorRate",
  "MatthewsCorrCoef",
  "MaxMetric",

src/torchmetrics/classification/__init__.py

@@ -29,21 +29,14 @@
  MultilabelStatScores,
  StatScores,
 )
-
 from torchmetrics.classification.accuracy import Accuracy, BinaryAccuracy, MulticlassAccuracy, MultilabelAccuracy
-from torchmetrics.classification.auc import AUC
 from torchmetrics.classification.auroc import AUROC, BinaryAUROC, MulticlassAUROC, MultilabelAUROC
 from torchmetrics.classification.average_precision import (
  AveragePrecision,
  BinaryAveragePrecision,
  MulticlassAveragePrecision,
  MultilabelAveragePrecision,
 )
-from torchmetrics.classification.binned_precision_recall import (
- BinnedAveragePrecision,
- BinnedPrecisionRecallCurve,
- BinnedRecallAtFixedPrecision,
-)
 from torchmetrics.classification.calibration_error import (
  BinaryCalibrationError,
  CalibrationError,
@@ -92,9 +85,6 @@
  Recall,
 )
 from torchmetrics.classification.ranking import (
- CoverageError,
- LabelRankingAveragePrecision,
- LabelRankingLoss,
  MultilabelCoverageError,
  MultilabelRankingAveragePrecision,
  MultilabelRankingLoss,