8000 FIX make pipeline pass check_estimator (#26325) · scikit-learn/scikit-learn@8521819 · GitHub
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adrinjalaliadrinjalali
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FIX make pipeline pass check_estimator (#26325)
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+49
-14
lines changed

4 files changed

+49
-14
lines changed

‎doc/whats_new/v1.3.rst

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Original file line numberDiff line numberDiff line change
@@ -467,6 +467,10 @@ Changelog
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`pandas.DataFrame`
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:pr:`25220` by :user:`Ian Thompson <it176131>`.
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- |Fix| :meth:`pipeline.Pipeline.fit_transform` now raises an `AttributeError`
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if the last step of the pipeline does not support `fit_transform`.
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:pr:`26325` by `Adrin Jalali`_.
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:mod:`sklearn.preprocessing`
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............................
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‎sklearn/pipeline.py

Lines changed: 32 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -421,6 +421,14 @@ def fit(self, X, y=None, **fit_params):
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return self
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def _can_fit_transform(self):
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return (
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self._final_estimator == "passthrough"
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or hasattr(self._final_estimator, "transform")
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or hasattr(self._final_estimator, "fit_transform")
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)
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@available_if(_can_fit_transform)
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def fit_transform(self, X, y=None, **fit_params):
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"""Fit the model and transform with the final estimator.
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@@ -744,12 +752,34 @@ def classes_(self):
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return self.steps[-1][1].classes_
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def _more_tags(self):
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tags = {
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"_xfail_checks": {
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"check_dont_overwrite_parameters": (
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"Pipeline changes the `steps` parameter, which it shouldn't."
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"Therefore this test is x-fail until we fix this."
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),
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"check_estimators_overwrite_params": (
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"Pipeline changes the `steps` parameter, which it shouldn't."
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"Therefore this test is x-fail until we fix this."
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),
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}
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}
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try:
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return {"pairwise": _safe_tags(self.steps[0][1], "pairwise")}
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tags["pairwise"] = _safe_tags(self.steps[0][1], "pairwise")
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except (ValueError, AttributeError, TypeError):
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# This happens when the `steps` is not a list of (name, estimator)
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# tuples and `fit` is not called yet to validate the steps.
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return {}
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pass
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try:
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tags["multioutput"] = _safe_tags(self.steps[-1][1], "multioutput")
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except (ValueError, AttributeError, TypeError):
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# This happens when the `steps` is not a list of (name, estimator)
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# tuples and `fit` is not called yet to validate the steps.
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pass
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return tags
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def get_feature_names_out(self, input_features=None):
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"""Get output feature names for transformation.

‎sklearn/tests/test_common.py

Lines changed: 11 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -133,7 +133,17 @@ def _tested_estimators(type_filter=None):
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yield estimator
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@parametrize_with_checks(list(_tested_estimators()))
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def _generate_pipeline():
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for final_estimator in [Ridge(), LogisticRegression()]:
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yield Pipeline(
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steps=[
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("scaler", StandardScaler()),
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("final_estimator", final_estimator),
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]
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)
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@parametrize_with_checks(list(chain(_tested_estimators(), _generate_pipeline())))
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def test_estimators(estimator, check, request):
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# Common tests for estimator instances
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with ignore_warnings(category=(FutureWarning, ConvergenceWarning, UserWarning)):
@@ -283,16 +293,6 @@ def _generate_column_transformer_instances():
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)
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286-
def _generate_pipeline():
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for final_estimator in [Ridge(), LogisticRegression()]:
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yield Pipeline(
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steps=[
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("scaler", StandardScaler()),
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("final_estimator", final_estimator),
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]
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)
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295-
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def _generate_search_cv_instances():
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for SearchCV, (Estimator, param_grid) in product(
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[

‎sklearn/tests/test_pipeline.py

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -670,7 +670,8 @@ def test_set_pipeline_steps():
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with pytest.raises(TypeError, match=msg):
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pipeline.fit([[1]], [1])
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673-
with pytest.raises(TypeError, match=msg):
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msg = "This 'Pipeline' has no attribute 'fit_transform'"
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with pytest.raises(AttributeError, match=msg):
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pipeline.fit_transform([[1]], [1])
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