code: def test_blobs_cluster():
      data, labels = make_blobs(n_samples=500, n_features=10, centers=5)
      embedding = UMAP(n_epochs=100).fit_transform(data)
      assert (
          adjusted_rand_score(labels, KMeans(5).fit_predict(embedding))
          == 1.0
      )
  
imports: from sklearn.datasets import make_blobs
  from sklearn.cluster import KMeans
  from sklearn.metrics import adjusted_rand_score, pairwise_distances
  from sklearn.preprocessing import normalize
  from numpy.testing import assert_array_equal
  from umap import UMAP
  from umap.spectral import component_layout
  import numpy
  import scipy.sparse
  import pytest
  import warnings
  from umap.distances import pairwise_special_metric
  from umap.utils import disconnected_vertices
  from scipy.sparse import csr_matrix
label_desc: Use image node_id 1 for calling a global function with example usage: test_blobs_cluster() without return types