From 9a624fcc73a25f83f41c780de1987d06effef86f Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Mon, 2 Aug 2021 16:05:35 +0200
Subject: [PATCH 01/17] ENH check_is_fitted calls __is_fitted__ if available

---
 sklearn/pipeline.py                           | 17 ++++++++++
 .../preprocessing/_function_transformer.py    |  4 +++
 sklearn/utils/estimator_checks.py             | 33 +++++++++++++++++++
 sklearn/utils/tests/test_validation.py        | 16 ++++++++-
 sklearn/utils/validation.py                   | 12 ++++---
 5 files changed, 77 insertions(+), 5 deletions(-)

diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index 0814632721ba4..d679e2df9694f 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -26,7 +26,9 @@
 from .utils.deprecation import deprecated
 from .utils._tags import _safe_tags
 from .utils.validation import check_memory
+from .utils.validation import check_is_fitted
 from .utils.fixes import delayed
+from .exceptions import NotFittedError
 
 from .utils.metaestimators import _BaseComposition
 
@@ -657,6 +659,21 @@ def n_features_in_(self):
         # delegate to first step (which will call _check_is_fitted)
         return self.steps[0][1].n_features_in_
 
+    def __is_fitted__(self):
+        """Check if pipeline is fitted.
+
+        Returns
+        -------
+        bool
+            True if the last step is fitted, false otherwise.
+        """
+        try:
+            # check if the last step of the pipeline is fitted
+            check_is_fitted(self.steps[-1][1])
+            return True
+        except NotFittedError:
+            return False
+
     def _sk_visual_block_(self):
         _, estimators = zip(*self.steps)
 
diff --git a/sklearn/preprocessing/_function_transformer.py b/sklearn/preprocessing/_function_transformer.py
index 345cc96bb1c2e..ad5e34c38b683 100644
--- a/sklearn/preprocessing/_function_transformer.py
+++ b/sklearn/preprocessing/_function_transformer.py
@@ -176,5 +176,9 @@ def _transform(self, X, func=None, kw_args=None):
 
         return func(X, **(kw_args if kw_args else {}))
 
+    def __is_fitted__(self):
+        """Return True since FunctionTransfomer is stateless."""
+        return True
+
     def _more_tags(self):
         return {"no_validation": not self.validate, "stateless": True}
diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
index ff853be22f663..5fa8e1e5f82cd 100644
--- a/sklearn/utils/estimator_checks.py
+++ b/sklearn/utils/estimator_checks.py
@@ -50,6 +50,7 @@
 from ..model_selection import ShuffleSplit
 from ..model_selection._validation import _safe_split
 from ..metrics.pairwise import rbf_kernel, linear_kernel, pairwise_distances
+from ..utils.validation import check_is_fitted
 
 from . import shuffle
 from ._tags import (
@@ -301,6 +302,7 @@ def _yield_all_checks(estimator):
     yield check_dict_unchanged
     yield check_dont_overwrite_parameters
     yield check_fit_idempotent
+    yield check_fit_check_is_fitted
     if not tags["no_validation"]:
         yield check_n_features_in
         yield check_fit1d
@@ -3314,6 +3316,37 @@ def check_fit_idempotent(name, estimator_orig):
             )
 
 
+def check_fit_check_is_fitted(name, estimator_orig):
+    # Make sure that n_features_in_ attribute doesn't exist until fit is
+    # called, and that its value is correct.
+
+    rng = np.random.RandomState(42)
+
+    estimator = clone(estimator_orig)
+    set_random_state(estimator)
+    if "warm_start" in estimator.get_params():
+        estimator.set_params(warm_start=False)
+
+    n_samples = 100
+    X = rng.normal(loc=100, size=(n_samples, 2))
+    X = _pairwise_estimator_convert_X(X, estimator)
+    if is_regressor(estimator_orig):
+        y = rng.normal(size=n_samples)
+    else:
+        y = rng.randint(low=0, high=2, size=n_samples)
+    y = _enforce_estimator_tags_y(estimator, y)
+
+    if not _safe_tags(estimator).get("stateless", False):
+        # stateless estimators (such as FunctionTransformer) are always "fit"!
+        try:
+            check_is_fitted(estimator)
+            raise (f"{estimator.__name__} passes check_is_fitted before being fit!")
+        except NotFittedError:
+            pass
+    estimator.fit(X, y)
+    check_is_fitted(estimator)
+
+
 def check_n_features_in(name, estimator_orig):
     # Make sure that n_features_in_ attribute doesn't exist until fit is
     # called, and that its value is correct.
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index 1a1449ecc209f..e0d272485db03 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -51,7 +51,7 @@
     FLOAT_DTYPES,
 )
 from sklearn.utils.validation import _check_fit_params
-
+from sklearn.base import BaseEstimator
 import sklearn
 
 from sklearn.exceptions import NotFittedError, PositiveSpectrumWarning
@@ -750,6 +750,20 @@ def test_check_symmetric():
             assert_array_equal(output, arr_sym)
 
 
+def test_check_is_fitted_with_is_fitted():
+    class Estimator(BaseEstimator):
+        def fit(self, **kwargs):
+            self._is_fitted = True
+            return self
+
+        def __is_fitted__(self):
+            return hasattr(self, "_is_fitted") and self._is_fitted
+
+    with pytest.raises(NotFittedError):
+        check_is_fitted(Estimator())
+    check_is_fitted(Estimator().fit())
+
+
 def test_check_is_fitted():
     # Check is TypeError raised when non estimator instance passed
     with pytest.raises(TypeError):
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 98bf6ac8bdb6a..fbfaba9567d80 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1142,8 +1142,9 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
     fitted attributes (ending with a trailing underscore) and otherwise
     raises a NotFittedError with the given message.
 
-    This utility is meant to be used internally by estimators themselves,
-    typically in their own predict / transform methods.
+    If an estimator does not set any attributes with a trailing underscore, it
+    can define a ``__is_fitted__`` method returning a boolean to specify if the
+    estimator is fitted or not.
 
     Parameters
     ----------
@@ -1194,13 +1195,16 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
     if attributes is not None:
         if not isinstance(attributes, (list, tuple)):
             attributes = [attributes]
-        attrs = all_or_any([hasattr(estimator, attr) for attr in attributes])
+        fitted = all_or_any([hasattr(estimator, attr) for attr in attributes])
+    elif hasattr(estimator, "__is_fitted__"):
+        fitted = estimator.__is_fitted__()
     else:
         attrs = [
             v for v in vars(estimator) if v.endswith("_") and not v.startswith("__")
         ]
+        fitted = len(attrs) > 0
 
-    if not attrs:
+    if not fitted:
         raise NotFittedError(msg % {"name": type(estimator).__name__})
 
 

From 54e5efd7f66b25aa9dbde4f049e56230b0f14497 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Mon, 2 Aug 2021 16:10:27 +0200
Subject: [PATCH 02/17] fix description

---
 sklearn/utils/estimator_checks.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
index 5fa8e1e5f82cd..d47e2166f301e 100644
--- a/sklearn/utils/estimator_checks.py
+++ b/sklearn/utils/estimator_checks.py
@@ -3317,8 +3317,8 @@ def check_fit_idempotent(name, estimator_orig):
 
 
 def check_fit_check_is_fitted(name, estimator_orig):
-    # Make sure that n_features_in_ attribute doesn't exist until fit is
-    # called, and that its value is correct.
+    # Make sure that estimator doesn't pass check_is_fitted before calling fit
+    # and that passes check_is_fitted once it's fit.
 
     rng = np.random.RandomState(42)
 

From 5076b691a7e59067370535591e587ddcac6adb99 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Mon, 2 Aug 2021 16:11:32 +0200
Subject: [PATCH 03/17] simplify validation

---
 sklearn/utils/validation.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index fbfaba9567d80..b06604f01303e 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1199,10 +1199,9 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
     elif hasattr(estimator, "__is_fitted__"):
         fitted = estimator.__is_fitted__()
     else:
-        attrs = [
+        fitted = [
             v for v in vars(estimator) if v.endswith("_") and not v.startswith("__")
         ]
-        fitted = len(attrs) > 0
 
     if not fitted:
         raise NotFittedError(msg % {"name": type(estimator).__name__})

From 544ec0f98c53c339c2e6b1c20bed267d4d487638 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Mon, 2 Aug 2021 16:18:56 +0200
Subject: [PATCH 04/17] add whats_new

---
 doc/whats_new/v1.0.rst | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index 7f44c62eb7329..837528ca69486 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -701,6 +701,12 @@ Changelog
   unavailable on the basis of state, in a more readable way.
   :pr:`19948` by `Joel Nothman`_.
 
+_ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
+  ``__is_fitted__``if available, instead of checking for attributes ending with
+  an underscore. This also makes :class:`Pipeline` and
+  :class:`preprocessing.FunctionTransformer` pass `check_is_fitted(estimator)`.
+  :pr:20657 by `Adrin Jalali`_.
+
 - |Fix| Fixed a bug in :func:`utils.sparsefuncs.mean_variance_axis` where the
   precision of the computed variance was very poor when the real variance is
   exactly zero. :pr:`19766` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

From 17853da80923354c2571387ae70b7ae0da96d0b0 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Mon, 2 Aug 2021 16:21:26 +0200
Subject: [PATCH 05/17] fix changelog format

---
 doc/whats_new/v1.0.rst | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index 837528ca69486..5c5ff4a41b062 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -702,10 +702,10 @@ Changelog
   :pr:`19948` by `Joel Nothman`_.
 
 _ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
-  ``__is_fitted__``if available, instead of checking for attributes ending with
+  ``__is_fitted__`` if available, instead of checking for attributes ending with
   an underscore. This also makes :class:`Pipeline` and
-  :class:`preprocessing.FunctionTransformer` pass `check_is_fitted(estimator)`.
-  :pr:20657 by `Adrin Jalali`_.
+  :class:`preprocessing.FunctionTransformer` pass
+  ``check_is_fitted(estimator)``. :pr:`20657` by `Adrin Jalali`_.
 
 - |Fix| Fixed a bug in :func:`utils.sparsefuncs.mean_variance_axis` where the
   precision of the computed variance was very poor when the real variance is

From a93426fbb99feac2045c9da93820508d05558b17 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Mon, 2 Aug 2021 17:32:26 +0200
Subject: [PATCH 06/17] test pipeline and check_estimator

---
 sklearn/tests/test_pipeline.py               | 11 +++++++-
 sklearn/utils/estimator_checks.py            |  5 +++-
 sklearn/utils/tests/test_estimator_checks.py | 27 ++++++++++++++++++++
 3 files changed, 41 insertions(+), 2 deletions(-)

diff --git a/sklearn/tests/test_pipeline.py b/sklearn/tests/test_pipeline.py
index 4176e1a65f4b2..1ee058e0da9a1 100644
--- a/sklearn/tests/test_pipeline.py
+++ b/sklearn/tests/test_pipeline.py
@@ -21,7 +21,8 @@
     MinimalRegressor,
     MinimalTransformer,
 )
-
+from sklearn.exceptions import NotFittedError
+from sklearn.utils.validation import check_is_fitted
 from sklearn.base import clone, is_classifier, BaseEstimator, TransformerMixin
 from sklearn.pipeline import Pipeline, FeatureUnion, make_pipeline, make_union
 from sklearn.svm import SVC
@@ -1361,3 +1362,11 @@ def test_search_cv_using_minimal_compatible_estimator(Predictor):
     else:
         assert_allclose(y_pred, y.mean())
         assert model.score(X, y) == pytest.approx(r2_score(y, y_pred))
+
+
+def test_test_pipeline_check_if_fitted():
+    pipeline = Pipeline([("clf", SVC())])
+    with pytest.raises(NotFittedError):
+        check_is_fitted(pipeline)
+    pipeline.fit(iris.data, iris.target)
+    check_is_fitted(pipeline)
diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
index d47e2166f301e..2a0e7a5bdd349 100644
--- a/sklearn/utils/estimator_checks.py
+++ b/sklearn/utils/estimator_checks.py
@@ -3340,7 +3340,10 @@ def check_fit_check_is_fitted(name, estimator_orig):
         # stateless estimators (such as FunctionTransformer) are always "fit"!
         try:
             check_is_fitted(estimator)
-            raise (f"{estimator.__name__} passes check_is_fitted before being fit!")
+            raise Exception(
+                f"{estimator.__class__.__name__} passes check_is_fitted before being"
+                " fit!"
+            )
         except NotFittedError:
             pass
     estimator.fit(X, y)
diff --git a/sklearn/utils/tests/test_estimator_checks.py b/sklearn/utils/tests/test_estimator_checks.py
index 8ff8d8cf5e782..a24dc40e337e2 100644
--- a/sklearn/utils/tests/test_estimator_checks.py
+++ b/sklearn/utils/tests/test_estimator_checks.py
@@ -20,11 +20,13 @@
     MinimalTransformer,
     SkipTest,
 )
+from sklearn.utils.metaestimators import available_if
 from sklearn.utils.estimator_checks import check_estimator, _NotAnArray
 from sklearn.utils.estimator_checks import check_class_weight_balanced_linear_classifier
 from sklearn.utils.estimator_checks import set_random_state
 from sklearn.utils.estimator_checks import _set_checking_parameters
 from sklearn.utils.estimator_checks import check_estimators_unfitted
+from sklearn.utils.estimator_checks import check_fit_check_is_fitted
 from sklearn.utils.estimator_checks import check_fit_score_takes_y
 from sklearn.utils.estimator_checks import check_no_attributes_set_in_init
 from sklearn.utils.estimator_checks import check_classifier_data_not_an_array
@@ -748,3 +750,28 @@ def test_minimal_class_implementation_checks():
     minimal_estimators = [MinimalTransformer(), MinimalRegressor(), MinimalClassifier()]
     for estimator in minimal_estimators:
         check_estimator(estimator)
+
+
+def test_check_fit_check_is_fitted():
+    class Estimator(BaseEstimator):
+        def __init__(self, behavior="attribute"):
+            self.behavior = behavior
+
+        def fit(self, X, y, **kwargs):
+            if self.behavior == "attribute":
+                self.is_fitted_ = True
+            elif self.behavior == "method":
+                self._is_fitted = True
+            return self
+
+        @available_if(lambda self: self.behavior in {"method", "always-true"})
+        def __is_fitted__(self):
+            if self.behavior == "always-true":
+                return True
+            return hasattr(self, "_is_fitted")
+
+    with raises(Exception, match="passes check_is_fitted before being fit"):
+        check_fit_check_is_fitted("estimator", Estimator(behavior="always-true"))
+
+    check_fit_check_is_fitted("estimator", Estimator(behavior="method"))
+    check_fit_check_is_fitted("estimator", Estimator(behavior="attribute"))

From 64c6a964a0d7568e9c3ba14e01c40494c5646a85 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Tue, 3 Aug 2021 11:59:05 +0200
Subject: [PATCH 07/17] rename to __sk_is_fitted__

---
 doc/whats_new/v1.0.rst                         | 2 +-
 sklearn/pipeline.py                            | 2 +-
 sklearn/preprocessing/_function_transformer.py | 2 +-
 sklearn/utils/tests/test_estimator_checks.py   | 2 +-
 sklearn/utils/tests/test_validation.py         | 2 +-
 sklearn/utils/validation.py                    | 6 +++---
 6 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index 5c5ff4a41b062..bd7fc3511941a 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -702,7 +702,7 @@ Changelog
   :pr:`19948` by `Joel Nothman`_.
 
 _ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
-  ``__is_fitted__`` if available, instead of checking for attributes ending with
+  ``__sk_is_fitted__`` if available, instead of checking for attributes ending with
   an underscore. This also makes :class:`Pipeline` and
   :class:`preprocessing.FunctionTransformer` pass
   ``check_is_fitted(estimator)``. :pr:`20657` by `Adrin Jalali`_.
diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index d679e2df9694f..4a21d1e27fb07 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -659,7 +659,7 @@ def n_features_in_(self):
         # delegate to first step (which will call _check_is_fitted)
         return self.steps[0][1].n_features_in_
 
-    def __is_fitted__(self):
+    def __sk_is_fitted__(self):
         """Check if pipeline is fitted.
 
         Returns
diff --git a/sklearn/preprocessing/_function_transformer.py b/sklearn/preprocessing/_function_transformer.py
index ad5e34c38b683..57fdd0a3684f1 100644
--- a/sklearn/preprocessing/_function_transformer.py
+++ b/sklearn/preprocessing/_function_transformer.py
@@ -176,7 +176,7 @@ def _transform(self, X, func=None, kw_args=None):
 
         return func(X, **(kw_args if kw_args else {}))
 
-    def __is_fitted__(self):
+    def __sk_is_fitted__(self):
         """Return True since FunctionTransfomer is stateless."""
         return True
 
diff --git a/sklearn/utils/tests/test_estimator_checks.py b/sklearn/utils/tests/test_estimator_checks.py
index a24dc40e337e2..22575369aec1d 100644
--- a/sklearn/utils/tests/test_estimator_checks.py
+++ b/sklearn/utils/tests/test_estimator_checks.py
@@ -765,7 +765,7 @@ def fit(self, X, y, **kwargs):
             return self
 
         @available_if(lambda self: self.behavior in {"method", "always-true"})
-        def __is_fitted__(self):
+        def __sk_is_fitted__(self):
             if self.behavior == "always-true":
                 return True
             return hasattr(self, "_is_fitted")
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index e0d272485db03..3d5d3f19b4ffc 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -756,7 +756,7 @@ def fit(self, **kwargs):
             self._is_fitted = True
             return self
 
-        def __is_fitted__(self):
+        def __sk_is_fitted__(self):
             return hasattr(self, "_is_fitted") and self._is_fitted
 
     with pytest.raises(NotFittedError):
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index b06604f01303e..02767663bb803 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1143,7 +1143,7 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
     raises a NotFittedError with the given message.
 
     If an estimator does not set any attributes with a trailing underscore, it
-    can define a ``__is_fitted__`` method returning a boolean to specify if the
+    can define a ``__sk_is_fitted__`` method returning a boolean to specify if the
     estimator is fitted or not.
 
     Parameters
@@ -1196,8 +1196,8 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
         if not isinstance(attributes, (list, tuple)):
             attributes = [attributes]
         fitted = all_or_any([hasattr(estimator, attr) for attr in attributes])
-    elif hasattr(estimator, "__is_fitted__"):
-        fitted = estimator.__is_fitted__()
+    elif hasattr(estimator, "__sk_is_fitted__"):
+        fitted = estimator.__sk_is_fitted__()
     else:
         fitted = [
             v for v in vars(estimator) if v.endswith("_") and not v.startswith("__")

From 552fec16f56df89b594c6cc5adbf373d1670533b Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Tue, 3 Aug 2021 12:01:59 +0200
Subject: [PATCH 08/17] use LogisticRegression in pipeline instead

---
 sklearn/tests/test_pipeline.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn/tests/test_pipeline.py b/sklearn/tests/test_pipeline.py
index 1ee058e0da9a1..3986495b5d13c 100644
--- a/sklearn/tests/test_pipeline.py
+++ b/sklearn/tests/test_pipeline.py
@@ -1364,8 +1364,8 @@ def test_search_cv_using_minimal_compatible_estimator(Predictor):
         assert model.score(X, y) == pytest.approx(r2_score(y, y_pred))
 
 
-def test_test_pipeline_check_if_fitted():
-    pipeline = Pipeline([("clf", SVC())])
+def test_pipeline_check_if_fitted():
+    pipeline = Pipeline([("clf", LogisticRegression())])
     with pytest.raises(NotFittedError):
         check_is_fitted(pipeline)
     pipeline.fit(iris.data, iris.target)

From f59e95e5242bc1f54fa2e7df7370c7e94fb31577 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Wed, 4 Aug 2021 12:49:14 +0200
Subject: [PATCH 09/17] try a fake estimator

---
 sklearn/tests/test_pipeline.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/sklearn/tests/test_pipeline.py b/sklearn/tests/test_pipeline.py
index 3986495b5d13c..4ec5c7f081a15 100644
--- a/sklearn/tests/test_pipeline.py
+++ b/sklearn/tests/test_pipeline.py
@@ -1365,7 +1365,12 @@ def test_search_cv_using_minimal_compatible_estimator(Predictor):
 
 
 def test_pipeline_check_if_fitted():
-    pipeline = Pipeline([("clf", LogisticRegression())])
+    class Estimator(BaseEstimator):
+        def fit(self, X, y):
+            self.fitted_ = True
+            return self
+
+    pipeline = Pipeline([("clf", Estimator())])
     with pytest.raises(NotFittedError):
         check_is_fitted(pipeline)
     pipeline.fit(iris.data, iris.target)

From 282e23b3805213fef22df25c88616da34ca9af47 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Fri, 6 Aug 2021 14:16:53 +0200
Subject: [PATCH 10/17] change from method to property

---
 doc/whats_new/v1.0.rst                        |  4 +--
 sklearn/pipeline.py                           |  1 +
 .../preprocessing/_function_transformer.py    |  1 +
 sklearn/utils/tests/test_estimator_checks.py  | 25 +++++++++++--------
 sklearn/utils/tests/test_validation.py        |  1 +
 sklearn/utils/validation.py                   |  6 ++---
 6 files changed, 22 insertions(+), 16 deletions(-)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index bd7fc3511941a..66f6e8642f941 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -702,8 +702,8 @@ Changelog
   :pr:`19948` by `Joel Nothman`_.
 
 _ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
-  ``__sk_is_fitted__`` if available, instead of checking for attributes ending with
-  an underscore. This also makes :class:`Pipeline` and
+  ``__sk_is_fitted__`` property if available, instead of checking for attributes
+  ending with an underscore. This also makes :class:`Pipeline` and
   :class:`preprocessing.FunctionTransformer` pass
   ``check_is_fitted(estimator)``. :pr:`20657` by `Adrin Jalali`_.
 
diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index 4a21d1e27fb07..bb0d8a07d8eff 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -659,6 +659,7 @@ def n_features_in_(self):
         # delegate to first step (which will call _check_is_fitted)
         return self.steps[0][1].n_features_in_
 
+    @property
     def __sk_is_fitted__(self):
         """Check if pipeline is fitted.
 
diff --git a/sklearn/preprocessing/_function_transformer.py b/sklearn/preprocessing/_function_transformer.py
index 57fdd0a3684f1..a043a01a54948 100644
--- a/sklearn/preprocessing/_function_transformer.py
+++ b/sklearn/preprocessing/_function_transformer.py
@@ -176,6 +176,7 @@ def _transform(self, X, func=None, kw_args=None):
 
         return func(X, **(kw_args if kw_args else {}))
 
+    @property
     def __sk_is_fitted__(self):
         """Return True since FunctionTransfomer is stateless."""
         return True
diff --git a/sklearn/utils/tests/test_estimator_checks.py b/sklearn/utils/tests/test_estimator_checks.py
index 22575369aec1d..5c6d34645a8c6 100644
--- a/sklearn/utils/tests/test_estimator_checks.py
+++ b/sklearn/utils/tests/test_estimator_checks.py
@@ -20,7 +20,6 @@
     MinimalTransformer,
     SkipTest,
 )
-from sklearn.utils.metaestimators import available_if
 from sklearn.utils.estimator_checks import check_estimator, _NotAnArray
 from sklearn.utils.estimator_checks import check_class_weight_balanced_linear_classifier
 from sklearn.utils.estimator_checks import set_random_state
@@ -754,24 +753,28 @@ def test_minimal_class_implementation_checks():
 
 def test_check_fit_check_is_fitted():
     class Estimator(BaseEstimator):
-        def __init__(self, behavior="attribute"):
+        def fit(self, X, y, **kwargs):
+            self.is_fitted_ = True
+            return self
+
+    class EstimatorProperty(BaseEstimator):
+        def __init__(self, behavior="always-true"):
             self.behavior = behavior
 
-        def fit(self, X, y, **kwargs):
-            if self.behavior == "attribute":
-                self.is_fitted_ = True
-            elif self.behavior == "method":
-                self._is_fitted = True
+        def fit(self, X, y):
+            self._is_fitted = True
             return self
 
-        @available_if(lambda self: self.behavior in {"method", "always-true"})
+        @property
         def __sk_is_fitted__(self):
             if self.behavior == "always-true":
                 return True
             return hasattr(self, "_is_fitted")
 
     with raises(Exception, match="passes check_is_fitted before being fit"):
-        check_fit_check_is_fitted("estimator", Estimator(behavior="always-true"))
+        check_fit_check_is_fitted(
+            "estimator", EstimatorProperty(behavior="always-true")
+        )
 
-    check_fit_check_is_fitted("estimator", Estimator(behavior="method"))
-    check_fit_check_is_fitted("estimator", Estimator(behavior="attribute"))
+    check_fit_check_is_fitted("estimator", EstimatorProperty(behavior="method"))
+    check_fit_check_is_fitted("estimator", Estimator())
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index 3d5d3f19b4ffc..243238db4391c 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -756,6 +756,7 @@ def fit(self, **kwargs):
             self._is_fitted = True
             return self
 
+        @property
         def __sk_is_fitted__(self):
             return hasattr(self, "_is_fitted") and self._is_fitted
 
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 02767663bb803..784f053174307 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1143,8 +1143,8 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
     raises a NotFittedError with the given message.
 
     If an estimator does not set any attributes with a trailing underscore, it
-    can define a ``__sk_is_fitted__`` method returning a boolean to specify if the
-    estimator is fitted or not.
+    can define a ``__sk_is_fitted__`` property returning a boolean to specify
+    if the estimator is fitted or not.
 
     Parameters
     ----------
@@ -1197,7 +1197,7 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
             attributes = [attributes]
         fitted = all_or_any([hasattr(estimator, attr) for attr in attributes])
     elif hasattr(estimator, "__sk_is_fitted__"):
-        fitted = estimator.__sk_is_fitted__()
+        fitted = estimator.__sk_is_fitted__
     else:
         fitted = [
             v for v in vars(estimator) if v.endswith("_") and not v.startswith("__")

From bb72f97505792472f873e6087d54662b58bd043c Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Fri, 6 Aug 2021 15:31:16 +0200
Subject: [PATCH 11/17] address Guillaume's comments

---
 sklearn/pipeline.py               | 8 +-------
 sklearn/utils/estimator_checks.py | 7 ++++++-
 2 files changed, 7 insertions(+), 8 deletions(-)

diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index bb0d8a07d8eff..c7cae2e476f81 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -661,13 +661,7 @@ def n_features_in_(self):
 
     @property
     def __sk_is_fitted__(self):
-        """Check if pipeline is fitted.
-
-        Returns
-        -------
-        bool
-            True if the last step is fitted, false otherwise.
-        """
+        """Indicate whether pipeline has been fit."""
         try:
             # check if the last step of the pipeline is fitted
             check_is_fitted(self.steps[-1][1])
diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
index 6f5c24efae88c..f7a4ec0146ea7 100644
--- a/sklearn/utils/estimator_checks.py
+++ b/sklearn/utils/estimator_checks.py
@@ -3526,7 +3526,12 @@ def check_fit_check_is_fitted(name, estimator_orig):
         except NotFittedError:
             pass
     estimator.fit(X, y)
-    check_is_fitted(estimator)
+    try:
+        check_is_fitted(estimator)
+    except NotFittedError as e:
+        raise NotFittedError(
+            "Estimator fails to pass `check_is_fitted` even though it has been fit."
+        ) from e
 
 
 def check_n_features_in(name, estimator_orig):

From 9552776c0953561cc3cda7d12d318f6bd269f531 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Fri, 6 Aug 2021 16:04:31 +0200
Subject: [PATCH 12/17] FunctionTransformer uses a class attribute

---
 sklearn/preprocessing/_function_transformer.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/sklearn/preprocessing/_function_transformer.py b/sklearn/preprocessing/_function_transformer.py
index a043a01a54948..8d48a6af2fa44 100644
--- a/sklearn/preprocessing/_function_transformer.py
+++ b/sklearn/preprocessing/_function_transformer.py
@@ -82,6 +82,10 @@ class FunctionTransformer(TransformerMixin, BaseEstimator):
            [1.0986..., 1.3862...]])
     """
 
+    # This is a stateless transfomer, and always passes
+    # ``check_is_fitted(transformer)``
+    __sk_is_fitted__ = True
+
     def __init__(
         self,
         func=None,
@@ -176,10 +180,5 @@ def _transform(self, X, func=None, kw_args=None):
 
         return func(X, **(kw_args if kw_args else {}))
 
-    @property
-    def __sk_is_fitted__(self):
-        """Return True since FunctionTransfomer is stateless."""
-        return True
-
     def _more_tags(self):
         return {"no_validation": not self.validate, "stateless": True}

From c9384bf28ff6f2585232c8f9e2f44dca50c7e287 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Thu, 12 Aug 2021 15:16:08 +0200
Subject: [PATCH 13/17] Revert "FunctionTransformer uses a class attribute"

This reverts commit 9552776c0953561cc3cda7d12d318f6bd269f531.
---
 sklearn/preprocessing/_function_transformer.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/sklearn/preprocessing/_function_transformer.py b/sklearn/preprocessing/_function_transformer.py
index 8d48a6af2fa44..a043a01a54948 100644
--- a/sklearn/preprocessing/_function_transformer.py
+++ b/sklearn/preprocessing/_function_transformer.py
@@ -82,10 +82,6 @@ class FunctionTransformer(TransformerMixin, BaseEstimator):
            [1.0986..., 1.3862...]])
     """
 
-    # This is a stateless transfomer, and always passes
-    # ``check_is_fitted(transformer)``
-    __sk_is_fitted__ = True
-
     def __init__(
         self,
         func=None,
@@ -180,5 +176,10 @@ def _transform(self, X, func=None, kw_args=None):
 
         return func(X, **(kw_args if kw_args else {}))
 
+    @property
+    def __sk_is_fitted__(self):
+        """Return True since FunctionTransfomer is stateless."""
+        return True
+
     def _more_tags(self):
         return {"no_validation": not self.validate, "stateless": True}

From c0a84dde392c4461efe1de5706dc9c5dc4db875e Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Thu, 12 Aug 2021 15:19:12 +0200
Subject: [PATCH 14/17] Revert "change from method to property"

This reverts commit 282e23b3805213fef22df25c88616da34ca9af47.
---
 doc/whats_new/v1.0.rst                        |  4 +--
 sklearn/pipeline.py                           |  1 -
 .../preprocessing/_function_transformer.py    |  1 -
 sklearn/utils/tests/test_estimator_checks.py  | 25 ++++++++-----------
 sklearn/utils/tests/test_validation.py        |  1 -
 sklearn/utils/validation.py                   |  6 ++---
 6 files changed, 16 insertions(+), 22 deletions(-)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index ab4d9b266fad2..2adac810be246 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -724,8 +724,8 @@ Changelog
   :pr:`19948` by `Joel Nothman`_.
 
 _ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
-  ``__sk_is_fitted__`` property if available, instead of checking for attributes
-  ending with an underscore. This also makes :class:`Pipeline` and
+  ``__sk_is_fitted__`` if available, instead of checking for attributes ending with
+  an underscore. This also makes :class:`Pipeline` and
   :class:`preprocessing.FunctionTransformer` pass
   ``check_is_fitted(estimator)``. :pr:`20657` by `Adrin Jalali`_.
 
diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index c7cae2e476f81..ec4992d321a9c 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -659,7 +659,6 @@ def n_features_in_(self):
         # delegate to first step (which will call _check_is_fitted)
         return self.steps[0][1].n_features_in_
 
-    @property
     def __sk_is_fitted__(self):
         """Indicate whether pipeline has been fit."""
         try:
diff --git a/sklearn/preprocessing/_function_transformer.py b/sklearn/preprocessing/_function_transformer.py
index a043a01a54948..57fdd0a3684f1 100644
--- a/sklearn/preprocessing/_function_transformer.py
+++ b/sklearn/preprocessing/_function_transformer.py
@@ -176,7 +176,6 @@ def _transform(self, X, func=None, kw_args=None):
 
         return func(X, **(kw_args if kw_args else {}))
 
-    @property
     def __sk_is_fitted__(self):
         """Return True since FunctionTransfomer is stateless."""
         return True
diff --git a/sklearn/utils/tests/test_estimator_checks.py b/sklearn/utils/tests/test_estimator_checks.py
index e7f32bdc746ca..a7cd9a3d0498f 100644
--- a/sklearn/utils/tests/test_estimator_checks.py
+++ b/sklearn/utils/tests/test_estimator_checks.py
@@ -34,6 +34,7 @@
 from sklearn.utils.validation import check_array
 from sklearn.utils import all_estimators
 from sklearn.exceptions import SkipTestWarning
+from sklearn.metaestimators import available_if
 
 from sklearn.utils.estimator_checks import (
     _NotAnArray,
@@ -991,28 +992,24 @@ def test_minimal_class_implementation_checks():
 
 def test_check_fit_check_is_fitted():
     class Estimator(BaseEstimator):
-        def fit(self, X, y, **kwargs):
-            self.is_fitted_ = True
-            return self
-
-    class EstimatorProperty(BaseEstimator):
-        def __init__(self, behavior="always-true"):
+        def __init__(self, behavior="attribute"):
             self.behavior = behavior
 
-        def fit(self, X, y):
-            self._is_fitted = True
+        def fit(self, X, y, **kwargs):
+            if self.behavior == "attribute":
+                self.is_fitted_ = True
+            elif self.behavior == "method":
+                self._is_fitted = True
             return self
 
-        @property
+        @available_if(lambda self: self.behavior in {"method", "always-true"})
         def __sk_is_fitted__(self):
             if self.behavior == "always-true":
                 return True
             return hasattr(self, "_is_fitted")
 
     with raises(Exception, match="passes check_is_fitted before being fit"):
-        check_fit_check_is_fitted(
-            "estimator", EstimatorProperty(behavior="always-true")
-        )
+        check_fit_check_is_fitted("estimator", Estimator(behavior="always-true"))
 
-    check_fit_check_is_fitted("estimator", EstimatorProperty(behavior="method"))
-    check_fit_check_is_fitted("estimator", Estimator())
+    check_fit_check_is_fitted("estimator", Estimator(behavior="method"))
+    check_fit_check_is_fitted("estimator", Estimator(behavior="attribute"))
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index 243238db4391c..3d5d3f19b4ffc 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -756,7 +756,6 @@ def fit(self, **kwargs):
             self._is_fitted = True
             return self
 
-        @property
         def __sk_is_fitted__(self):
             return hasattr(self, "_is_fitted") and self._is_fitted
 
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 784f053174307..02767663bb803 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1143,8 +1143,8 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
     raises a NotFittedError with the given message.
 
     If an estimator does not set any attributes with a trailing underscore, it
-    can define a ``__sk_is_fitted__`` property returning a boolean to specify
-    if the estimator is fitted or not.
+    can define a ``__sk_is_fitted__`` method returning a boolean to specify if the
+    estimator is fitted or not.
 
     Parameters
     ----------
@@ -1197,7 +1197,7 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
             attributes = [attributes]
         fitted = all_or_any([hasattr(estimator, attr) for attr in attributes])
     elif hasattr(estimator, "__sk_is_fitted__"):
-        fitted = estimator.__sk_is_fitted__
+        fitted = estimator.__sk_is_fitted__()
     else:
         fitted = [
             v for v in vars(estimator) if v.endswith("_") and not v.startswith("__")

From d30ba5d991fe4dbe30508db6835b13da58bd4377 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Thu, 12 Aug 2021 15:22:56 +0200
Subject: [PATCH 15/17] Olivier's comments

---
 sklearn/pipeline.py               | 3 +++
 sklearn/utils/estimator_checks.py | 2 +-
 2 files changed, 4 insertions(+), 1 deletion(-)

diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index ec4992d321a9c..236ffea43034f 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -663,6 +663,9 @@ def __sk_is_fitted__(self):
         """Indicate whether pipeline has been fit."""
         try:
             # check if the last step of the pipeline is fitted
+            # we only check the last step since if the last step is fit, it
+            # means the previous steps should also be fit. This is faster than
+            # checking if every step of the pipeline is fit.
             check_is_fitted(self.steps[-1][1])
             return True
         except NotFittedError:
diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
index f7a4ec0146ea7..612c61753a1cb 100644
--- a/sklearn/utils/estimator_checks.py
+++ b/sklearn/utils/estimator_checks.py
@@ -3519,7 +3519,7 @@ def check_fit_check_is_fitted(name, estimator_orig):
         # stateless estimators (such as FunctionTransformer) are always "fit"!
         try:
             check_is_fitted(estimator)
-            raise Exception(
+            raise AssertionError(
                 f"{estimator.__class__.__name__} passes check_is_fitted before being"
                 " fit!"
             )

From 89d41cb0cb0b5b634bb607423570215df581a0d7 Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Thu, 12 Aug 2021 15:23:49 +0200
Subject: [PATCH 16/17] rename to __sklearn_is_fitted__

---
 doc/whats_new/v1.0.rst                         | 2 +-
 sklearn/pipeline.py                            | 2 +-
 sklearn/preprocessing/_function_transformer.py | 2 +-
 sklearn/utils/tests/test_estimator_checks.py   | 2 +-
 sklearn/utils/tests/test_validation.py         | 2 +-
 sklearn/utils/validation.py                    | 6 +++---
 6 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index 2adac810be246..5f50465f5aef3 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -724,7 +724,7 @@ Changelog
   :pr:`19948` by `Joel Nothman`_.
 
 _ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
-  ``__sk_is_fitted__`` if available, instead of checking for attributes ending with
+  ``__sklearn_is_fitted__`` if available, instead of checking for attributes ending with
   an underscore. This also makes :class:`Pipeline` and
   :class:`preprocessing.FunctionTransformer` pass
   ``check_is_fitted(estimator)``. :pr:`20657` by `Adrin Jalali`_.
diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index 236ffea43034f..35f0fa3768b45 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -659,7 +659,7 @@ def n_features_in_(self):
         # delegate to first step (which will call _check_is_fitted)
         return self.steps[0][1].n_features_in_
 
-    def __sk_is_fitted__(self):
+    def __sklearn_is_fitted__(self):
         """Indicate whether pipeline has been fit."""
         try:
             # check if the last step of the pipeline is fitted
diff --git a/sklearn/preprocessing/_function_transformer.py b/sklearn/preprocessing/_function_transformer.py
index 57fdd0a3684f1..202b6ec2f6cdd 100644
--- a/sklearn/preprocessing/_function_transformer.py
+++ b/sklearn/preprocessing/_function_transformer.py
@@ -176,7 +176,7 @@ def _transform(self, X, func=None, kw_args=None):
 
         return func(X, **(kw_args if kw_args else {}))
 
-    def __sk_is_fitted__(self):
+    def __sklearn_is_fitted__(self):
         """Return True since FunctionTransfomer is stateless."""
         return True
 
diff --git a/sklearn/utils/tests/test_estimator_checks.py b/sklearn/utils/tests/test_estimator_checks.py
index a7cd9a3d0498f..91219b8b43f08 100644
--- a/sklearn/utils/tests/test_estimator_checks.py
+++ b/sklearn/utils/tests/test_estimator_checks.py
@@ -1003,7 +1003,7 @@ def fit(self, X, y, **kwargs):
             return self
 
         @available_if(lambda self: self.behavior in {"method", "always-true"})
-        def __sk_is_fitted__(self):
+        def __sklearn_is_fitted__(self):
             if self.behavior == "always-true":
                 return True
             return hasattr(self, "_is_fitted")
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index 3d5d3f19b4ffc..35afff12b7ca4 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -756,7 +756,7 @@ def fit(self, **kwargs):
             self._is_fitted = True
             return self
 
-        def __sk_is_fitted__(self):
+        def __sklearn_is_fitted__(self):
             return hasattr(self, "_is_fitted") and self._is_fitted
 
     with pytest.raises(NotFittedError):
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 02767663bb803..aa7a23ffcdf9c 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1143,7 +1143,7 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
     raises a NotFittedError with the given message.
 
     If an estimator does not set any attributes with a trailing underscore, it
-    can define a ``__sk_is_fitted__`` method returning a boolean to specify if the
+    can define a ``__sklearn_is_fitted__`` method returning a boolean to specify if the
     estimator is fitted or not.
 
     Parameters
@@ -1196,8 +1196,8 @@ def check_is_fitted(estimator, attributes=None, *, msg=None, all_or_any=all):
         if not isinstance(attributes, (list, tuple)):
             attributes = [attributes]
         fitted = all_or_any([hasattr(estimator, attr) for attr in attributes])
-    elif hasattr(estimator, "__sk_is_fitted__"):
-        fitted = estimator.__sk_is_fitted__()
+    elif hasattr(estimator, "__sklearn_is_fitted__"):
+        fitted = estimator.__sklearn_is_fitted__()
     else:
         fitted = [
             v for v in vars(estimator) if v.endswith("_") and not v.startswith("__")

From 1b08447f963daa93fcbc89a1b601e2c98215144e Mon Sep 17 00:00:00 2001
From: adrinjalali <adrin.jalali@gmail.com>
Date: Thu, 12 Aug 2021 16:14:35 +0200
Subject: [PATCH 17/17] fix import

---
 sklearn/utils/tests/test_estimator_checks.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/utils/tests/test_estimator_checks.py b/sklearn/utils/tests/test_estimator_checks.py
index 91219b8b43f08..89e2e43651088 100644
--- a/sklearn/utils/tests/test_estimator_checks.py
+++ b/sklearn/utils/tests/test_estimator_checks.py
@@ -34,7 +34,7 @@
 from sklearn.utils.validation import check_array
 from sklearn.utils import all_estimators
 from sklearn.exceptions import SkipTestWarning
-from sklearn.metaestimators import available_if
+from sklearn.utils.metaestimators import available_if
 
 from sklearn.utils.estimator_checks import (
     _NotAnArray,