code: def test_mbsgd_regressor_default(make_dataset):
      nrows, datatype, X_train, X_test, y_train, y_test = make_dataset
  
      cu_mbsgd_regressor = cumlMBSGRegressor(batch_size=nrows / 100)
      cu_mbsgd_regressor.fit(X_train, y_train)
      cu_pred = cu_mbsgd_regressor.predict(X_test)
      cu_r2 = r2_score(
          cp.asnumpy(cu_pred),
          cp.asnumpy(y_test),
          convert_dtype=datatype,
      )
  
      assert cu_r2 > 0.9
  
file_path: cuml/python/cuml/tests/test_mbsgd_regressor.py
imports: from sklearn.model_selection import train_test_split
  from cuml.datasets import make_regression
  from sklearn.linear_model import SGDRegressor
  from cuml.testing.utils import unit_param, quality_param, stress_param
  from cuml.metrics import r2_score
  from cuml.linear_model import MBSGDRegressor
  from cuml.internals.safe_imports import gpu_only_import
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 4 for calling a global function with example usage: test_mbsgd_regressor_default(make_dataset) without return types