[Refactor] Classification 6/n (#1163)

* some idea

* implementation stuff

* error message

* somethings working

* working

* working multilabel precision recall

* docstrings

* working average precision

* working roc

* working auroc

* working precision at recall

* docs

* init files

* beginning doctest

* more docs

* more docs

* more docs

* more docs

* more docs

* more docs

* correction to math

* fix mypy

* add suggestions

* change default from 100 to None

* fix

* fix

* some fixes

* suggestions for stancld

* try fixing

* try fix

* try again

* more fixing

* another fix

* skip half + cpu test for old versions

* fix link

* another fix

* nan safety

* another fix

* skip non working cpu half tests

* skip non working cpu + half tests

docs/source/classification/auroc.rst

@@ -15,8 +15,44 @@ ________________
 .. autoclass:: torchmetrics.AUROC
     :noindex:
 
+BinaryAUROC
+^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.BinaryAUROC
+    :noindex:
+
+MulticlassAUROC
+^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MulticlassAUROC
+    :noindex:
+
+MultilabelAUROC
+^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MultilabelAUROC
+    :noindex:
+
 Functional Interface
 ____________________
 
 .. autofunction:: torchmetrics.functional.auroc
     :noindex:
+
+binary_auroc
+^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.binary_auroc
+    :noindex:
+
+multiclass_auroc
+^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multiclass_auroc
+    :noindex:
+
+multilabel_auroc
+^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multilabel_auroc
+    :noindex:

docs/source/classification/average_precision.rst

@@ -13,8 +13,44 @@ ________________
 .. autoclass:: torchmetrics.AveragePrecision
     :noindex:
 
+BinaryAveragePrecision
+^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.BinaryAveragePrecision
+    :noindex:
+
+MulticlassAveragePrecision
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MulticlassAveragePrecision
+    :noindex:
+
+MultilabelAveragePrecision
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MultilabelAveragePrecision
+    :noindex:
+
 Functional Interface
 ____________________
 
 .. autofunction:: torchmetrics.functional.average_precision
     :noindex:
+
+binary_average_precision
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.binary_average_precision
+    :noindex:
+
+multiclass_average_precision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multiclass_average_precision
+    :noindex:
+
+multilabel_average_precision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multilabel_average_precision
+    :noindex:

docs/source/classification/precision_recall_curve.rst

@@ -13,8 +13,44 @@ ________________
 .. autoclass:: torchmetrics.PrecisionRecallCurve
     :noindex:
 
+BinaryPrecisionRecallCurve
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.BinaryPrecisionRecallCurve
+    :noindex:
+
+MulticlassPrecisionRecallCurve
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MulticlassPrecisionRecallCurve
+    :noindex:
+
+MultilabelPrecisionRecallCurve
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MultilabelPrecisionRecallCurve
+    :noindex:
+
 Functional Interface
 ____________________
 
 .. autofunction:: torchmetrics.functional.precision_recall_curve
     :noindex:
+
+binary_precision_recall_curve
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.binary_precision_recall_curve
+    :noindex:
+
+multiclass_precision_recall_curve
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multiclass_precision_recall_curve
+    :noindex:
+
+multilabel_precision_recall_curve
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multilabel_precision_recall_curve
+    :noindex:

docs/source/classification/recall_at_fixed_precision.rst

@@ -0,0 +1,50 @@
+.. customcarditem::
+   :header: Recall At Fixed Precision
+   :image: https://pl-flash-data.s3.amazonaws.com/assets/thumbnails/tabular_classification.svg
+   :tags: Classification
+
+#########################
+Recall At Fixed Precision
+#########################
+
+Module Interface
+________________
+
+BinaryRecallAtFixedPrecision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.BinaryRecallAtFixedPrecision
+    :noindex:
+
+MulticlassRecallAtFixedPrecision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MulticlassRecallAtFixedPrecision
+    :noindex:
+
+MultilabelRecallAtFixedPrecision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MultilabelRecallAtFixedPrecision
+    :noindex:
+
+Functional Interface
+____________________
+
+binary_recall_at_fixed_precision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.binary_recall_at_fixed_precision
+    :noindex:
+
+multiclass_recall_at_fixed_precision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multiclass_recall_at_fixed_precision
+    :noindex:
+
+multilabel_recall_at_fixed_precision
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multilabel_recall_at_fixed_precision
+    :noindex:

docs/source/classification/roc.rst

@@ -13,8 +13,44 @@ ________________
 .. autoclass:: torchmetrics.ROC
     :noindex:
 
+BinaryROC
+^^^^^^^^^
+
+.. autoclass:: torchmetrics.BinaryROC
+    :noindex:
+
+MulticlassROC
+^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MulticlassROC
+    :noindex:
+
+MultilabelROC
+^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MultilabelROC
+    :noindex:
+
 Functional Interface
 ____________________
 
 .. autofunction:: torchmetrics.functional.roc
     :noindex:
+
+binary_roc
+^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.binary_roc
+    :noindex:
+
+multiclass_roc
+^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multiclass_roc
+    :noindex:
+
+multilabel_roc
+^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multilabel_roc
+    :noindex:

src/torchmetrics/__init__.py

@@ -27,6 +27,8 @@
     Accuracy,
     AveragePrecision,
     BinaryAccuracy,
+    BinaryAUROC,
+    BinaryAveragePrecision,
     BinaryCohenKappa,
     BinaryConfusionMatrix,
     BinaryF1Score,
@@ -35,7 +37,10 @@
     BinaryJaccardIndex,
     BinaryMatthewsCorrCoef,
     BinaryPrecision,
+    BinaryPrecisionRecallCurve,
     BinaryRecall,
+    BinaryRecallAtFixedPrecision,
+    BinaryROC,
     BinarySpecificity,
     BinaryStatScores,
     BinnedAveragePrecision,
@@ -56,6 +61,8 @@
     LabelRankingLoss,
     MatthewsCorrCoef,
     MulticlassAccuracy,
+    MulticlassAUROC,
+    MulticlassAveragePrecision,
     MulticlassCohenKappa,
     MulticlassConfusionMatrix,
     MulticlassF1Score,
@@ -64,10 +71,15 @@
     MulticlassJaccardIndex,
     MulticlassMatthewsCorrCoef,
     MulticlassPrecision,
+    MulticlassPrecisionRecallCurve,
     MulticlassRecall,
+    MulticlassRecallAtFixedPrecision,
+    MulticlassROC,
     MulticlassSpecificity,
     MulticlassStatScores,
     MultilabelAccuracy,
+    MultilabelAUROC,
+    MultilabelAveragePrecision,
     MultilabelConfusionMatrix,
     MultilabelCoverageError,
     MultilabelExactMatch,
@@ -77,9 +89,12 @@
     MultilabelJaccardIndex,
     MultilabelMatthewsCorrCoef,
     MultilabelPrecision,
+    MultilabelPrecisionRecallCurve,
     MultilabelRankingAveragePrecision,
     MultilabelRankingLoss,
     MultilabelRecall,
+    MultilabelRecallAtFixedPrecision,
+    MultilabelROC,
     MultilabelSpecificity,
     MultilabelStatScores,
     Precision,
@@ -155,6 +170,21 @@
     "MultilabelAccuracy",
     "AUC",
     "AUROC",
+    "BinaryAUROC",
+    "BinaryAveragePrecision",
+    "BinaryPrecisionRecallCurve",
+    "BinaryRecallAtFixedPrecision",
+    "BinaryROC",
+    "MultilabelROC",
+    "MulticlassAUROC",
+    "MulticlassAveragePrecision",
+    "MulticlassPrecisionRecallCurve",
+    "MulticlassRecallAtFixedPrecision",
+    "MulticlassROC",
+    "MultilabelAUROC",
+    "MultilabelAveragePrecision",
+    "MultilabelPrecisionRecallCurve",
+    "MultilabelRecallAtFixedPrecision",
     "AveragePrecision",
     "BinnedAveragePrecision",
     "BinnedPrecisionRecallCurve",

src/torchmetrics/classification/__init__.py

@@ -17,6 +17,12 @@
     MulticlassConfusionMatrix,
     MultilabelConfusionMatrix,
 )
+from torchmetrics.classification.precision_recall_curve import (  # noqa: F401 isort:skip
+    PrecisionRecallCurve,
+    BinaryPrecisionRecallCurve,
+    MulticlassPrecisionRecallCurve,
+    MultilabelPrecisionRecallCurve,
+)
 from torchmetrics.classification.stat_scores import (  # noqa: F401 isort:skip
     BinaryStatScores,
     MulticlassStatScores,
@@ -31,8 +37,13 @@
     MultilabelAccuracy,
 )
 from torchmetrics.classification.auc import AUC  # noqa: F401
-from torchmetrics.classification.auroc import AUROC  # noqa: F401
-from torchmetrics.classification.avg_precision import AveragePrecision  # noqa: F401
+from torchmetrics.classification.auroc import AUROC, BinaryAUROC, MulticlassAUROC, MultilabelAUROC  # noqa: F401
+from torchmetrics.classification.average_precision import (  # noqa: F401
+    AveragePrecision,
+    BinaryAveragePrecision,
+    MulticlassAveragePrecision,
+    MultilabelAveragePrecision,
+)
 from torchmetrics.classification.binned_precision_recall import BinnedAveragePrecision  # noqa: F401
 from torchmetrics.classification.binned_precision_recall import BinnedPrecisionRecallCurve  # noqa: F401
 from torchmetrics.classification.binned_precision_recall import BinnedRecallAtFixedPrecision  # noqa: F401
@@ -80,7 +91,6 @@
     Precision,
     Recall,
 )
-from torchmetrics.classification.precision_recall_curve import PrecisionRecallCurve  # noqa: F401
 from torchmetrics.classification.ranking import (  # noqa: F401
     CoverageError,
     LabelRankingAveragePrecision,
@@ -89,7 +99,12 @@
     MultilabelRankingAveragePrecision,
     MultilabelRankingLoss,
 )
-from torchmetrics.classification.roc import ROC  # noqa: F401
+from torchmetrics.classification.recall_at_fixed_precision import (  # noqa: F401
+    BinaryRecallAtFixedPrecision,
+    MulticlassRecallAtFixedPrecision,
+    MultilabelRecallAtFixedPrecision,
+)
+from torchmetrics.classification.roc import ROC, BinaryROC, MulticlassROC, MultilabelROC  # noqa: F401
 from torchmetrics.classification.specificity import (  # noqa: F401
     BinarySpecificity,
     MulticlassSpecificity,