code: def test_balanced_random_forest_grid_search(imbalanced_dataset):
      brf = BalancedRandomForestClassifier(
          sampling_strategy="all", replacement=True, bootstrap=False
      )
      grid = GridSearchCV(
          brf, {"n_estimators": (1, 2), "max_depth": (1, 2)}, cv=3
      )
      grid.fit(*imbalanced_dataset)
  
imports: import numpy
  import pytest
  import sklearn
  from sklearn.datasets import load_iris, make_classification
  from sklearn.model_selection import GridSearchCV, train_test_split
  from sklearn.utils._testing import assert_allclose, assert_array_equal
  from sklearn.utils.fixes import parse_version
  from imblearn.ensemble import BalancedRandomForestClassifier
label_desc: Use image node_id 7 for calling a global function with example usage: test_balanced_random_forest_grid_search(imbalanced_dataset) without return types