code: def test_mbsgd_classifier_vs_skl(lrate, penalty, loss, make_dataset):
      nrows, X_train, X_test, y_train, y_test = make_dataset
  
      if nrows < 500000:
          cu_mbsgd_classifier = cumlMBSGClassifier(
              learning_rate=lrate,
              eta0=0.005,
              epochs=100,
              fit_intercept=True,
              batch_size=2,
              tol=0.0,
              penalty=penalty,
          )
  
          cu_mbsgd_classifier.fit(X_train, y_train)
          cu_pred = cu_mbsgd_classifier.predict(X_test)
          cu_acc = accuracy_score(
              cp.asnumpy(cu_pred), cp.asnumpy(y_test)
          )
  
          skl_sgd_classifier = SGDClassifier(
              learning_rate=lrate,
              eta0=0.005,
              max_iter=100,
              fit_intercept=True,
              tol=0.0,
              penalty=penalty,
              random_state=0,
          )
  
          skl_sgd_classifier.fit(
              cp.asnumpy(X_train), cp.asnumpy(y_train)
          )
          skl_pred = skl_sgd_classifier.predict(cp.asnumpy(X_test))
          skl_acc = accuracy_score(skl_pred, cp.asnumpy(y_test))
          assert cu_acc >= skl_acc - 0.08
  
file_path: cuml/python/cuml/tests/test_mbsgd_classifier.py
imports: from sklearn.model_selection import train_test_split
  from sklearn.metrics import accuracy_score
  from cuml.datasets import make_classification
  from sklearn.linear_model import SGDClassifier
  from cuml.testing.utils import unit_param, quality_param, stress_param
  from cuml.linear_model import MBSGDClassifier
  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 2 for calling a global function with example usage: test_mbsgd_classifier_vs_skl(lrate, penalty, loss, make_dataset) without return types