code: def test_non_encoded_labels():
      dataset = datasets.load_iris()
      X = dataset.data
      labels = dataset.target
      assert silhouette_score(X, labels * 2 + 10) == silhouette_score(
          X, labels
      )
      assert_array_equal(
          silhouette_samples(X, labels * 2 + 10),
          silhouette_samples(X, labels),
      )
  
imports: import warnings
  import numpy
  import pytest
  from numpy.testing import assert_allclose
  from scipy.sparse import issparse
  from sklearn import datasets
  from sklearn.metrics import pairwise_distances
  from sklearn.metrics.cluster import calinski_harabasz_score, davies_bouldin_score, silhouette_samples, silhouette_score
  from sklearn.metrics.cluster._unsupervised import _silhouette_reduce
  from sklearn.utils._testing import assert_array_equal
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
label_desc: Use image node_id 5 for calling a global function with example usage: test_non_encoded_labels() without return types