code: def test_duplicate_distances(connectivity):
      X = cp.array([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [2.0, 2.0, 2.0]])
  
      cuml_agg = AgglomerativeClustering(
          n_clusters=2,
          affinity="euclidean",
          linkage="single",
          n_neighbors=3,
          connectivity=connectivity,
      )
  
      sk_agg = cluster.AgglomerativeClustering(
          n_clusters=2, affinity="euclidean", linkage="single"
      )
  
      cuml_agg.fit(X)
      sk_agg.fit(X.get())
  
      assert (
          adjusted_rand_score(cuml_agg.labels_, sk_agg.labels_) == 1.0
      )
  
file_path: cuml/python/cuml/tests/test_agglomerative.py
imports: import pytest
  from cuml.cluster import AgglomerativeClustering
  from cuml.datasets import make_blobs
  from cuml.metrics import adjusted_rand_score
  from sklearn import cluster
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 1 for calling a global function with example usage: test_duplicate_distances(connectivity) without return types