code: def test_umap_distance_metrics_fit_transform_trust(metric, supported):
      data, labels = make_blobs(
          n_samples=1000, n_features=64, centers=5, random_state=42
      )
  
      if metric == "jaccard":
          data = data >= 0
  
      umap_model = umap.UMAP(
          n_neighbors=10, min_dist=0.01, metric=metric, init="random"
      )
      cuml_model = cuUMAP(
          n_neighbors=10, min_dist=0.01, metric=metric, init="random"
      )
      if not supported:
          with pytest.raises(NotImplementedError):
              cuml_model.fit_transform(data)
          return
  
      umap_embedding = umap_model.fit_transform(data)
  
      cuml_embedding = cuml_model.fit_transform(data)
  
      umap_trust = trustworthiness(
          data, umap_embedding, n_neighbors=10, metric=metric
      )
      cuml_trust = trustworthiness(
          data, cuml_embedding, n_neighbors=10, metric=metric
      )
  
      assert array_equal(umap_trust, cuml_trust, 0.05, with_sign=True)
  
imports: import platform
  import pytest
  import copy
  import joblib
  from sklearn.metrics import adjusted_rand_score
  from sklearn.manifold import trustworthiness
  from sklearn.datasets import make_blobs
  from sklearn.cluster import KMeans
  from sklearn.neighbors import NearestNeighbors
  from sklearn import datasets
  from cuml.internals import logger
  from cuml.metrics import pairwise_distances
  from cuml.testing.utils import array_equal, unit_param, quality_param, stress_param
  from cuml.manifold.umap import UMAP
  from cuml.internals.safe_imports import cpu_only_import
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 22 for calling a global function with example usage: test_umap_distance_metrics_fit_transform_trust(metric, supported) without return types