code: def test_check_estimator(solver):
      # sklearn fits on unnormalized data for which there are convergence issues
      # fix with increased tolerance:
      clf = LogisticRegression(C=1, solver=solver, tol=0.1)
      check_estimator(clf)
  
file_path: celer/celer/tests/test_logreg.py
imports: import pytest
  import numpy
  from numpy.linalg import norm
  from numpy.testing import assert_allclose, assert_array_less
  from sklearn.linear_model._logistic import _logistic_regression_path
  from sklearn.utils.estimator_checks import check_estimator
  from sklearn.linear_model import LogisticRegression
  from celer import celer_path
  from celer.dropin_sklearn import LogisticRegression
  from celer.utils.testing import build_dataset
label_desc: Use image node_id 4 for calling a global function with example usage: test_check_estimator(solver) without return types