code: def make_blob_dataset():
      X, y = make_blobs(
          n_samples=2000, n_features=20, centers=20, random_state=0
      )
      X_train, X_test = X[:1800], X[1800:]
      y_train, _ = y[:1800], y[1800:]
      return (
          X_train.astype(np.float32),
          y_train.astype(np.float32),
          X_test.astype(np.float32),
      )
  
imports: import platform
  from cuml.testing.test_preproc_utils import to_output_type
  from cuml.testing.utils import array_equal
  from cuml.cluster.hdbscan import HDBSCAN
  from cuml.neighbors import NearestNeighbors
  from cuml.metrics import trustworthiness
  from cuml.metrics import adjusted_rand_score
  from cuml.manifold import UMAP
  from cuml.linear_model import ElasticNet, Lasso, LinearRegression, LogisticRegression, Ridge
  from cuml.internals.memory_utils import using_memory_type
  from cuml.internals.mem_type import MemoryType
  from cuml.decomposition import PCA, TruncatedSVD
  from cuml.common.device_selection import DeviceType, using_device_type
  from hdbscan import HDBSCAN
  from sklearn.neighbors import NearestNeighbors
  from sklearn.linear_model import Ridge
  from sklearn.linear_model import ElasticNet
  from sklearn.linear_model import Lasso
  from sklearn.linear_model import LogisticRegression
  from sklearn.linear_model import LinearRegression
  from sklearn.decomposition import PCA
  from sklearn.decomposition import TruncatedSVD
  from sklearn.datasets import make_regression, make_blobs
  from pytest_cases import fixture_union, fixture_plus
  from importlib import import_module
  import inspect
  import pickle
  from cuml.internals.safe_imports import gpu_only_import
  import itertools
  import pytest
  import cuml
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 7 for calling a global function with example usage: make_blob_dataset() and returns: X_train,  y_train,  X_test