Resolve ANN102

pyproject.toml

@@ -117,7 +117,6 @@ ignore = [
     "D104",   # todo: Missing docstring in public package
     "D107",   # Missing docstring in `__init__`
     "ANN101", # Missing type annotation for `self` in method
-    "ANN102", # Missing type annotation for `cls` in classmethod
     "S301",   # todo: `pickle` and modules that wrap it can be unsafe when used to deserialize untrusted data, possible security issue  # todo
     "S310",   # todo: Audit URL open for permitted schemes. Allowing use of `file:` or custom schemes is often unexpected.  # todo
     "B905",   # todo: `zip()` without an explicit `strict=` parameter

src/torchmetrics/classification/accuracy.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -483,8 +483,8 @@ class Accuracy(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["Accuracy"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/auroc.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -501,8 +501,8 @@ class AUROC(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["AUROC"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/average_precision.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -511,8 +511,8 @@ class AveragePrecision(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["AveragePrecision"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/calibration_error.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -367,8 +367,8 @@ class CalibrationError(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["CalibrationError"],
         task: Literal["binary", "multiclass"],
         n_bins: int = 15,
         norm: Literal["l1", "l2", "max"] = "l1",

src/torchmetrics/classification/cohen_kappa.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -311,8 +311,8 @@ class labels.
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["CohenKappa"],
         task: Literal["binary", "multiclass"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/confusion_matrix.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional
+from typing import Any, List, Optional, Type
 
 import torch
 from torch import Tensor
@@ -504,8 +504,8 @@ class ConfusionMatrix(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["ConfusionMatrix"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/exact_match.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 import torch
 from torch import Tensor
@@ -393,7 +393,7 @@ class ExactMatch(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["ExactMatch"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/f_beta.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -1053,7 +1053,7 @@ class FBetaScore(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["FBetaScore"],
         task: Literal["binary", "multiclass", "multilabel"],
         beta: float = 1.0,
         threshold: float = 0.5,
@@ -1115,7 +1115,7 @@ class F1Score(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["F1Score"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/hamming.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -492,8 +492,8 @@ class HammingDistance(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["HammingDistance"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/hinge.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 import torch
 from torch import Tensor
@@ -350,8 +350,8 @@ class HingeLoss(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["HingeLoss"],
         task: Literal["binary", "multiclass"],
         num_classes: Optional[int] = None,
         squared: bool = False,

src/torchmetrics/classification/jaccard.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -441,8 +441,8 @@ class JaccardIndex(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["JaccardIndex"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/matthews_corrcoef.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -389,8 +389,8 @@ class MatthewsCorrCoef(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["MatthewsCorrCoef"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/precision_fixed_recall.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Tuple, Union
+from typing import Any, List, Optional, Sequence, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -481,8 +481,8 @@ class PrecisionAtFixedRecall(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["PrecisionAtFixedRecall"],
         task: Literal["binary", "multiclass", "multilabel"],
         min_recall: float,
         thresholds: Optional[Union[int, List[float], Tensor]] = None,

src/torchmetrics/classification/precision_recall.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -925,7 +925,7 @@ class Precision(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["Precision"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
@@ -988,7 +988,7 @@ class Recall(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["Recall"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/precision_recall_curve.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Type, Union
 
 import torch
 from torch import Tensor
@@ -649,8 +649,8 @@ class PrecisionRecallCurve(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["PrecisionRecallCurve"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/recall_fixed_precision.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Tuple, Union
+from typing import Any, List, Optional, Sequence, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -480,8 +480,8 @@ class RecallAtFixedPrecision(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["RecallAtFixedPrecision"],
         task: Literal["binary", "multiclass", "multilabel"],
         min_precision: float,
         thresholds: Optional[Union[int, List[float], Tensor]] = None,

src/torchmetrics/classification/roc.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -559,7 +559,7 @@ class ROC(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["ROC"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/specificity.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -473,8 +473,8 @@ class Specificity(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["Specificity"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,

src/torchmetrics/classification/specificity_sensitivity.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -342,8 +342,8 @@ class SpecificityAtSensitivity(_ClassificationTaskWrapper):
 
     """
 
-    def __new__(  # type: ignore[misc]
-        cls,
+    def __new__(
+        cls: Type["SpecificityAtSensitivity"],
         task: Literal["binary", "multiclass", "multilabel"],
         min_sensitivity: float,
         thresholds: Optional[Union[int, List[float], Tensor]] = None,