code: def test_logistic_regression_preds_labels():
      """[Utils] LogisticRegression: check label predictions."""
      g = np.array(
          [1.0, 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 3.0, 3.0]
      )
  
      p = LogisticRegression().fit(X, z).predict(X)
  
      np.testing.assert_array_equal(p, g)
  
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 8 for calling a global function with example usage: test_logistic_regression_preds_labels() without return types