code: def test_make_blobs(setup):
      cluster_stds = np.array([0.05, 0.2, 0.4])
      cluster_centers = np.array([[0.0, 0.0], [1.0, 1.0], [0.0, 1.0]])
      X, y = make_blobs(
          random_state=0,
          n_samples=50,
          n_features=2,
          centers=cluster_centers,
          cluster_std=cluster_stds,
      )
      X, y = mt.ExecutableTuple((X, y)).execute().fetch()
      assert X.shape == (50, 2)
      assert y.shape == (50,)
      assert np.unique(y).shape == (3,)
      for i, (ctr, std) in enumerate(
          zip(cluster_centers, cluster_stds)
      ):
          assert_almost_equal(
              (X[y == i] - ctr).std(), std, 1, "Unexpected std"
          )
  
file_path: mars/mars/learn/datasets/tests/test_samples_generator.py
imports: from functools import partial
  from collections import defaultdict
  import numpy
  from sklearn.utils._testing import assert_array_almost_equal, assert_raises, assert_almost_equal, assert_raise_message
  from ....None import tensor
  from ....tensor.linalg import svd
  from ..samples_generator import make_low_rank_matrix, make_classification, make_regression, make_blobs
label_desc: Use image node_id 5 for calling a global function with example usage: test_make_blobs(setup) without return types