code: def test_logistic_regression_weights():
      """[Utils] LogisticRegression: check weights."""
      w = np.array(
          [
              [-0.81643357, 0.76923077],
              [-0.52156177, 0.51282051],
              [0.33799534, -0.28205128],
          ]
      )
  
      lr = LogisticRegression()
      lr.fit(X, z)
  
      np.testing.assert_array_almost_equal(lr.coef_, w)
  
imports: import numpy
  import os
  from mlens.ensemble.base import Layer, Sequential
  from mlens.utils.dummy import OLS, LogisticRegression, Scale
  from mlens.testing.dummy import ESTIMATORS, PREPROCESSING, ESTIMATORS_PROBA, ECM, ECM_PROBA, InitMixin
  from mlens.testing.dummy import Data, EstimatorContainer
  from mlens.utils import assert_correct_format
  from mlens.utils.formatting import _assert_format, _format_instances
  from mlens.utils.exceptions import NotFittedError
  from mlens.externals.sklearn.base import BaseEstimator
label_desc: Use image node_id 7 for calling a global function with example usage: test_logistic_regression_weights() without return types