code: def test_sklearn_compliance():
      """Test LinearModel compliance with sklearn."""
      pytest.importorskip("sklearn")
      from sklearn.linear_model import LogisticRegression
      from sklearn.utils.estimator_checks import check_estimator
  
      est = SlidingEstimator(LogisticRegression(), allow_2d=True)
  
      ignores = (
          "check_estimator_sparse_data",  # we densify
          "check_classifiers_one_label_sample_weights",  # don't handle singleton
          "check_classifiers_classes",  # dim mismatch
          "check_classifiers_train",
          "check_decision_proba_consistency",
          "check_parameters_default_constructible",
      )
      for est, check in check_estimator(est, generate_only=True):
          if any(ignore in str(check) for ignore in ignores):
              continue
          check(est)
  
file_path: mne-python/mne/decoding/tests/test_search_light.py
imports: import platform
  from inspect import signature
  import numpy
  import pytest
  from numpy.testing import assert_array_equal, assert_equal
  from mne.decoding.search_light import GeneralizingEstimator, SlidingEstimator
  from mne.decoding.transformer import Vectorizer
  from mne.utils import _record_warnings, check_version, use_log_level
label_desc: Use image node_id 6 for calling a global function with example usage: test_sklearn_compliance() without return types