code: def test_logistic_regression(
      strategy,
      use_wrapper,
      nrows,
      num_classes,
      column_info,
      dtype=np.float32,
  ):
      ncols, n_info = column_info
  
      X_train, X_test, y_train, y_test = make_classification_dataset(
          datatype=dtype,
          nrows=nrows,
          ncols=ncols,
          n_info=n_info,
          num_classes=num_classes,
      )
      y_train = y_train.astype(dtype)
      y_test = y_test.astype(dtype)
      culog = cuLog()
  
      if use_wrapper:
          cls = cu_multiclass.MulticlassClassifier(
              culog, strategy=strategy
          )
      else:
          if strategy == "ovo":
              cls = cu_multiclass.OneVsOneClassifier(culog)
          else:
              cls = cu_multiclass.OneVsRestClassifier(culog)
  
      cls.fit(X_train, y_train)
      test_score = cls.score(X_test, y_test)
      assert test_score > 0.7
  
imports: from cuml import LogisticRegression
  from cuml import multiclass
  import sys
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
  from test_linear_model import make_classification_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: test_logistic_regression(strategy, use_wrapper, nrows, num_classes, column_info, dtype) without return types