HOTFIX: remove dependence to typing_extensions

Author: Valentin-Laurent

mapie/classification.py

@@ -2,7 +2,6 @@
 
 import warnings
 from typing import Any, Iterable, Optional, Tuple, Union, cast
-from typing_extensions import Self
 
 import numpy as np
 from sklearn import clone
@@ -155,7 +154,7 @@ def fit(
         X_train: ArrayLike,
         y_train: ArrayLike,
         fit_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> SplitConformalClassifier:
         """
         Fits the base classifier to the training data.
 
@@ -191,7 +190,7 @@ def conformalize(
         X_conformalize: ArrayLike,
         y_conformalize: ArrayLike,
         predict_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> SplitConformalClassifier:
         """
         Estimates the uncertainty of the base classifier by computing
         conformity scores on the conformalization set.
@@ -422,7 +421,7 @@ def fit_conformalize(
         groups: Optional[ArrayLike] = None,
         fit_params: Optional[dict] = None,
         predict_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> CrossConformalClassifier:
         """
         Estimates the uncertainty of the base classifier in a cross-validation style:
         fits the base classifier on different folds of the dataset

mapie/regression/quantile_regression.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 from typing import Iterable, List, Optional, Tuple, Union, cast, Any
-from typing_extensions import Self
 
 import numpy as np
 from sklearn.base import RegressorMixin, clone
@@ -128,7 +127,7 @@ def fit(
         X_train: ArrayLike,
         y_train: ArrayLike,
         fit_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> ConformalizedQuantileRegressor:
         """
         Fits three models using the regressor provided at initialisation:
 
@@ -174,7 +173,7 @@ def conformalize(
         X_conformalize: ArrayLike,
         y_conformalize: ArrayLike,
         predict_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> ConformalizedQuantileRegressor:
         """
         Estimates the uncertainty of the quantile regressors by computing
         conformity scores on the conformalization set.

mapie/regression/regression.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 from typing import Any, Iterable, Optional, Tuple, Union, cast
-from typing_extensions import Self
 
 import numpy as np
 from sklearn.base import BaseEstimator, RegressorMixin, clone
@@ -151,7 +150,7 @@ def fit(
         X_train: ArrayLike,
         y_train: ArrayLike,
         fit_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> SplitConformalRegressor:
         """
         Fits the base regressor to the training data.
 
@@ -187,7 +186,7 @@ def conformalize(
         X_conformalize: ArrayLike,
         y_conformalize: ArrayLike,
         predict_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> SplitConformalRegressor:
         """
         Estimates the uncertainty of the base regressor by computing
         conformity scores on the conformalization set.
@@ -438,7 +437,7 @@ def fit_conformalize(
         groups: Optional[ArrayLike] = None,
         fit_params: Optional[dict] = None,
         predict_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> CrossConformalRegressor:
         """
         Estimates the uncertainty of the base regressor in a cross-validation style:
         fits the base regressor on different folds of the dataset
@@ -751,7 +750,7 @@ def fit_conformalize(
         y: ArrayLike,
         fit_params: Optional[dict] = None,
         predict_params: Optional[dict] = None,
-    ) -> Self:
+    ) -> JackknifeAfterBootstrapRegressor:
         """
         Estimates the uncertainty of the base regressor using bootstrap sampling:
         fits the base regressor on (potentially overlapping) samples of the dataset,