[Refactor] Classification 5/n

docs/source/classification/accuracy.rst

@@ -13,8 +13,44 @@ ________________
 .. autoclass:: torchmetrics.Accuracy
     :noindex:
 
+BinaryAccuracy
+^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.BinaryAccuracy
+    :noindex:
+
+MulticlassAccuracy
+^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MulticlassAccuracy
+    :noindex:
+
+MultilabelAccuracy
+^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MultilabelAccuracy
+    :noindex:
+
 Functional Interface
 ____________________
 
 .. autofunction:: torchmetrics.functional.accuracy
     :noindex:
+
+binary_accuracy
+^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.binary_accuracy
+    :noindex:
+
+multiclass_accuracy
+^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multiclass_accuracy
+    :noindex:
+
+multilabel_accuracy
+^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multilabel_accuracy
+    :noindex:

docs/source/classification/exact_match.rst

@@ -0,0 +1,26 @@
+.. customcarditem::
+   :header: Exact Match
+   :image: https://pl-flash-data.s3.amazonaws.com/assets/thumbnails/tabular_classification.svg
+   :tags: Classification
+
+###########
+Exact Match
+###########
+
+Module Interface
+________________
+
+MultilabelExactMatch
+^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.MultilabelExactMatch
+    :noindex:
+
+Functional Interface
+____________________
+
+multilabel_exact_match
+^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.multilabel_exact_match
+    :noindex:

src/torchmetrics/__init__.py

@@ -26,6 +26,7 @@
     ROC,
     Accuracy,
     AveragePrecision,
+    BinaryAccuracy,
     BinaryCohenKappa,
     BinaryConfusionMatrix,
     BinaryF1Score,
@@ -54,6 +55,7 @@
     LabelRankingAveragePrecision,
     LabelRankingLoss,
     MatthewsCorrCoef,
+    MulticlassAccuracy,
     MulticlassCohenKappa,
     MulticlassConfusionMatrix,
     MulticlassF1Score,
@@ -65,7 +67,9 @@
     MulticlassRecall,
     MulticlassSpecificity,
     MulticlassStatScores,
+    MultilabelAccuracy,
     MultilabelConfusionMatrix,
+    MultilabelExactMatch,
     MultilabelF1Score,
     MultilabelFBetaScore,
     MultilabelHammingDistance,
@@ -143,6 +147,9 @@
 __all__ = [
     "functional",
     "Accuracy",
+    "BinaryAccuracy",
+    "MulticlassAccuracy",
+    "MultilabelAccuracy",
     "AUC",
     "AUROC",
     "AveragePrecision",
@@ -187,6 +194,7 @@
     "BinaryJaccardIndex",
     "MulticlassJaccardIndex",
     "MultilabelJaccardIndex",
+    "MultilabelExactMatch",
     "KLDivergence",
     "LabelRankingAveragePrecision",
     "LabelRankingLoss",

src/torchmetrics/classification/__init__.py

@@ -24,7 +24,12 @@
     StatScores,
 )
 
-from torchmetrics.classification.accuracy import Accuracy  # noqa: F401
+from torchmetrics.classification.accuracy import (  # noqa: F401
+    Accuracy,
+    BinaryAccuracy,
+    MulticlassAccuracy,
+    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
@@ -34,6 +39,7 @@
 from torchmetrics.classification.calibration_error import CalibrationError  # noqa: F401
 from torchmetrics.classification.cohen_kappa import BinaryCohenKappa, CohenKappa, MulticlassCohenKappa  # noqa: F401
 from torchmetrics.classification.dice import Dice  # noqa: F401
+from torchmetrics.classification.exact_match import MultilabelExactMatch  # noqa: F401
 from torchmetrics.classification.f_beta import (  # noqa: F401
     BinaryF1Score,
     BinaryFBetaScore,