Scikit-learn: ट्रांसफार्मर चरण के लिए कोई नहीं के साथ पाइपलाइन पर ग्रिड खोज के दौरान उठाई गई त्रुटि

बग का वर्णन करें

ट्रांसफॉर्मर चरण के लिए None पाइपलाइन पर ग्रिड खोज करते समय, एक AttributeError उठाया जाता है। नीचे दिया गया यह स्निपेट पहले scikit-learn==0.23.2 साथ सफलतापूर्वक चला लेकिन अब 0.24.dev0 काम नहीं करता है।

चरण/कोड पुन: उत्पन्न करने के लिए

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)

अपेक्षित परिणाम

GridSearchCV.fit कॉल सफलतापूर्वक पूर्ण करने में सक्षम है

वास्तविक परिणाम

निम्नलिखित त्रुटि उठाई गई है (मैंने पूर्ण ट्रेसबैक को और नीचे शामिल किया है):

  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'

ऐसा प्रतीत होता है कि _is_pairwise चेक एक चरण ट्रांसफॉर्मर के लिए None के साथ पाइपलाइन पर लागू होने पर अपेक्षित रूप से काम नहीं करता है।

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'

संस्करणों

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