8000 FIX Removes validation in __init__ for Pipeline by arisayosh · Pull Request #21888 · scikit-learn/scikit-learn · GitHub
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FIX Removes validation in __init__ for Pipeline #21888

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Merged
merged 5 commits into from
Dec 10, 2021
Merged

FIX Removes validation in __init__ for Pipeline #21888

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4f52f45
remove self._validate_steps() from __init__
arisayosh Dec 5, 2021
f0dae7e
modify test_pipeline_init() to test during fit() instead of instantia…
arisayosh Dec 5, 2021
abda71a
Merge remote-tracking branch 'upstream/main' into Issue-21406
arisayosh Dec 8, 2021
034cd32
Rewrite test so error is raised explicitly in fit and adds documentation
arisayosh Dec 8, 2021
dafc7f8
Update doc/whats_new/v1.1.rst
arisayosh Dec 10, 2021
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4 changes: 4 additions & 0 deletions doc/whats_new/v1.1.rst
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Expand Up @@ -258,6 +258,10 @@ Changelog
Setting a transformer to "passthrough" will pass the features unchanged.
:pr:`20860` by :user:`Shubhraneel Pal <shubhraneel>`.

- |Fix| :class: `pipeline.Pipeline` now does not validate hyper-parameters in
`__init__` but in `.fit()`.
:pr:`21888` by :user:`iofall <iofall>` and :user: `Arisa Y. <arisayosh>`.

:mod:`sklearn.preprocessing`
............................

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1 change: 0 additions & 1 deletion sklearn/pipeline.py
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Expand Up @@ -146,7 +146,6 @@ def __init__(self, steps, *, memory=None, verbose=False):
self.steps = steps
self.memory = memory
self.verbose = verbose
self._validate_steps()

def get_params(self, deep=True):
"""Get parameters for this estimator.
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1 change: 0 additions & 1 deletion sklearn/tests/test_common.py
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Expand Up @@ -428,7 +428,6 @@ def test_transformers_get_feature_names_out(transformer):
"FeatureUnion",
"GridSearchCV",
"HalvingGridSearchCV",
"Pipeline",
"SGDOneClassSVM",
"TheilSenRegressor",
"TweedieRegressor",
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20 changes: 12 additions & 8 deletions sklearn/tests/test_pipeline.py
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Expand Up @@ -165,20 +165,23 @@ def predict_log_proba(self, X, got_attribute=False):
return self


def test_pipeline_init():
# Test the various init parameters of the pipeline.
def test_pipeline_invalid_parameters():
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Renamed function since we are not validating parameters during instantiation. We decided not to split the function in two because it caused code repetition.

# Test the various init parameters of the pipeline in fit
# method
pipeline = Pipeline([(1, 1)])
with pytest.raises(TypeError):
Pipeline()
pipeline.fit([[1]], [1])

# Check that we can't instantiate pipelines with objects without fit
# Check that we can't fit pipelines with objects without fit
# method
msg = (
"Last step of Pipeline should implement fit "
"or be the string 'passthrough'"
".*NoFit.*"
)
pipeline = Pipeline([("clf", NoFit())])
with pytest.raises(TypeError, match=msg):
Pipeline([("clf", NoFit())])
pipeline.fit([[1]], [1])

# Smoke test with only an estimator
clf = NoTrans()
Expand All @@ -203,11 +206,12 @@ def test_pipeline_init():
assert pipe.named_steps["anova"] is filter1
assert pipe.named_steps["svc"] is clf

# Check that we can't instantiate with non-transformers on the way
# Check that we can't fit with non-transformers on the way
# Note that NoTrans implements fit, but not transform
msg = "All intermediate steps should be transformers.*\\bNoTrans\\b.*"
pipeline = Pipeline([("t", NoTrans()), ("svc", clf)])
with pytest.raises(TypeError, match=msg):
Pipeline([("t", NoTrans()), ("svc", clf)])
pipeline.fit([[1]], [1])

# Check that params are set
pipe.set_params(svc__C=0.1)
Expand Down Expand Up @@ -1086,7 +1090,7 @@ def test_step_name_validation():
# three ways to make invalid:
# - construction
with pytest.raises(ValueError, match=message):
cls(**{param: bad_steps})
cls(**{param: bad_steps}).fit([[1]], [1])

# - setattr
est = cls(**{param: [("a", Mult(1))]})
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