code: def test_transform(setup):
      centers = np.array(
          [
              [0.0, 5.0, 0.0, 0.0, 0.0],
              [1.0, 1.0, 4.0, 0.0, 0.0],
              [1.0, 0.0, 0.0, 5.0, 1.0],
          ]
      )
      n_samples = 100
      n_clusters, n_features = centers.shape
      X = make_blobs(
          n_samples=n_samples,
          centers=centers,
          cluster_std=1.0,
          random_state=42,
      )[0]
  
      km = KMeans(
          n_clusters=n_clusters, init="k-means++", algorithm="elkan"
      )
      km.fit(X)
      X_new = km.transform(km.cluster_centers_).fetch()
  
      for c in range(n_clusters):
          assert X_new[c, c] == 0
          for c2 in range(n_clusters):
              if c != c2:
                  assert X_new[c, c2] > 0
  
imports: import sys
  from io import StringIO
  import numpy
  import pytest
  import scipy.sparse
  from ....None import tensor
  from ....core import TileableGraphBuilder, TileableGraph, ChunkGraphBuilder
  from ....config import options
  from ..None import KMeans, k_means
  from .._kmeans import _init_centroids
label_desc: Use image node_id 13 for calling a global function with example usage: test_transform(setup) without return types