code: def test_mbsgd_regressor(lrate, penalty, make_dataset):
      nrows, datatype, X_train, X_test, y_train, y_test = make_dataset
  
      cu_mbsgd_regressor = cumlMBSGRegressor(
          learning_rate=lrate,
          eta0=0.005,
          epochs=100,
          fit_intercept=True,
          batch_size=nrows / 100,
          tol=0.0,
          penalty=penalty,
      )
  
      cu_mbsgd_regressor.fit(X_train, y_train)
      cu_pred = cu_mbsgd_regressor.predict(X_test)
      cu_r2 = r2_score(cu_pred, y_test, convert_dtype=datatype)
  
      assert cu_r2 >= 0.88
  
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 3 for calling a global function with example usage: test_mbsgd_regressor(lrate, penalty, make_dataset) without return types