code: def test_gs():
      X = np.array([[1, 1, 1], [0, 0, 0], [-1, -1, -1]] * 100)
      y = np.array([0, 0, 1] * 100)
      gs = DistGridSearchCV(
          LogisticRegression(solver="liblinear"),
          {"C": [0.1, 1.0]},
          cv=3,
      )
      gs.fit(X, y)
      preds = gs.predict(X[:3])
      assert np.allclose(preds, np.array([0, 0, 1]))
  
file_path: sk-dist/skdist/distribute/tests/test_search.py
imports: import sys
  import pytest
  import numpy
  from scipy.stats.distributions import expon
  from sklearn.linear_model import LogisticRegression
  from sklearn.naive_bayes import GaussianNB
  from sklearn.ensemble import RandomForestClassifier
label_desc: Use image node_id 2 for calling a global function with example usage: test_gs() without return types