code: def test_gridsearchCV():
      iris = load_iris()
      parameters = {"kernel": ("linear", "rbf"), "C": [1, 10]}
      clf = GridSearchCV(SVC(), parameters)
      clf.fit(iris.data, iris.target)
      assert clf.best_params_["kernel"] == "rbf"
      assert clf.best_params_["C"] == 10
  
file_path: cuml/python/cuml/tests/test_meta_estimators.py
imports: from cuml.svm import SVC
  from cuml.preprocessing import StandardScaler
  from sklearn.datasets import load_iris
  from cuml.model_selection import train_test_split
  from cuml.datasets import make_regression, make_classification
  from cuml.testing.utils import ClassEnumerator
  from cuml.model_selection import GridSearchCV
  from cuml.pipeline import Pipeline, make_pipeline
  import pytest
  import cuml
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 2 for calling a global function with example usage: test_gridsearchCV() without return types