Scikit-learn: Erreur générée lors de la recherche de grille sur le pipeline avec Aucun pour l'étape du transformateur

Décrivez le bogue

Lors de l'exécution d'une recherche de grille sur un pipeline qui a None pour une étape de transformation, un AttributeError est généré. Cet extrait ci-dessous fonctionnait auparavant avec succès avec scikit-learn==0.23.2 mais ne fonctionne plus avec 0.24.dev0 .

Étapes/Code à reproduire

from sklearn.datasets import load_iris
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import GridSearchCV
from sklearn.svm import SVC

iris = load_iris()
X, y = iris.data, iris.target

pipe = Pipeline([("setup", None), ("svc", SVC(kernel="linear", random_state=0))])

param_grid = [
    {"svc__C": [0.1, 0.1]},
    {"setup": [StandardScaler()]},
]

gs = GridSearchCV(pipe, param_grid=param_grid, return_train_score=True, cv=3)
gs.fit(X, y)

Résultats attendus

L'appel GridSearchCV.fit peut se terminer avec succès

Résultats actuels

L'erreur suivante est générée (j'ai inclus le retraçage complet plus bas):

  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/base.py", line 863, in _is_pairwise
    pairwise_tag = estimator._get_tags().get('pairwise', False)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/base.py", line 348, in _get_tags
    more_tags = base_class._more_tags(self)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/pipeline.py", line 626, in _more_tags
    estimator_tags = self.steps[0][1]._get_tags()
AttributeError: 'NoneType' object has no attribute '_get_tags'

Il semble que la vérification _is_pairwise ne fonctionne pas comme prévu lorsqu'elle est appliquée à un pipeline avec None pour un transformateur pas à pas.

Traceback (most recent call last):
  File "test-pipeline.py", line 18, in <module>
    gs.fit(X, y)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/utils/validation.py", line 60, in inner_f
    return f(*args, **kwargs)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/model_selection/_search.py", line 841, in fit
    self._run_search(evaluate_candidates)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/model_selection/_search.py", line 1288, in _run_search
    evaluate_candidates(ParameterGrid(self.param_grid))
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/model_selection/_search.py", line 795, in evaluate_candidates
    out = parallel(delayed(_fit_and_score)(clone(base_estimator),
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/joblib/parallel.py", line 1048, in __call__
    if self.dispatch_one_batch(iterator):
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/joblib/parallel.py", line 866, in dispatch_one_batch
    self._dispatch(tasks)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/joblib/parallel.py", line 784, in _dispatch
    job = self._backend.apply_async(batch, callback=cb)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/joblib/_parallel_backends.py", line 208, in apply_async
    result = ImmediateResult(func)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/joblib/_parallel_backends.py", line 572, in __init__
    self.results = batch()
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/joblib/parallel.py", line 262, in __call__
    return [func(*args, **kwargs)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/joblib/parallel.py", line 262, in <listcomp>
    return [func(*args, **kwargs)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/utils/fixes.py", line 222, in __call__
    return self.function(*args, **kwargs)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/model_selection/_validation.py", line 585, in _fit_and_score
    X_train, y_train = _safe_split(estimator, X, y, train)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/utils/metaestimators.py", line 198, in _safe_split
    if _is_pairwise(estimator):
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/base.py", line 863, in _is_pairwise
    pairwise_tag = estimator._get_tags().get('pairwise', False)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/base.py", line 348, in _get_tags
    more_tags = base_class._more_tags(self)
  File "/Users/james/miniforge3/envs/dask-ml/lib/python3.8/site-packages/sklearn/pipeline.py", line 626, in _more_tags
    estimator_tags = self.steps[0][1]._get_tags()
AttributeError: 'NoneType' object has no attribute '_get_tags'

Versions

System:
    python: 3.8.6 | packaged by conda-forge | (default, Oct  7 2020, 18:42:56)  [Clang 10.0.1 ]
executable: /Users/james/miniforge3/envs/dask-ml/bin/python3.8
   machine: macOS-10.15.5-x86_64-i386-64bit

Python dependencies:
          pip: 20.2.4
   setuptools: 49.6.0.post20201009
      sklearn: 0.24.dev0
        numpy: 1.19.4
        scipy: 1.5.3
       Cython: None
       pandas: 1.1.4
   matplotlib: None
       joblib: 0.17.0
threadpoolctl: 2.1.0

Built with OpenMP: True