code: def _run_test(model, methods, dataset):
      datasets = []
      if dataset in ["blobs", "classifier", "sparse"]:
          X1, y1 = load_iris(return_X_y=True)
          if dataset == "sparse":
              X1 = sparse.csr_matrix(X1)
          datasets.append((X1, y1))
          X2, y2 = load_breast_cancer(return_X_y=True)
          if dataset == "sparse":
              X2 = sparse.csr_matrix(X2)
          datasets.append((X2, y2))
      elif dataset == "regression":
          X1, y1 = make_regression(
              n_samples=500, n_features=10, noise=64.0, random_state=42
          )
          datasets.append((X1, y1))
          X2, y2 = load_diabetes(return_X_y=True)
          datasets.append((X2, y2))
      else:
          raise ValueError("Unknown dataset type")
  
      for X, y in datasets:
          baseline, name = func(X, y, model, methods)
          for i in range(10):
              res, _ = func(X, y, model, methods)
  
              for a, b, n in zip(res, baseline, name):
                  np.testing.assert_allclose(
                      a,
                      b,
                      rtol=0.0,
                      atol=0.0,
                      err_msg=str(n + " is incorrect"),
                  )
  
imports: import random
  import numpy
  import pytest
  import daal4py
  from sklearnex import patch_sklearn
  from scipy import sparse
  from sklearn.cluster import DBSCAN, KMeans
  from sklearn.datasets import load_breast_cancer, load_diabetes, load_iris, make_classification, make_regression
  from sklearn.decomposition import PCA
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
  from sklearn.linear_model import ElasticNet, Lasso, LinearRegression, LogisticRegression, LogisticRegressionCV, Ridge
  from sklearn.manifold import TSNE
  from sklearn.metrics import pairwise_distances, roc_auc_score
  from sklearn.model_selection import train_test_split
  from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor, LocalOutlierFactor, NearestNeighbors
  from sklearn.svm import SVC, SVR, NuSVC, NuSVR
  from daal4py.sklearn._utils import daal_check_version
label_desc: Use image node_id 4 for calling a global function with example usage: _run_test(model, methods, dataset) without return types