code: def test_umap_distance_metrics_fit_transform_trust_on_sparse_input(
      metric, supported, umap_learn_supported
  ):
      data, labels = make_blobs(
          n_samples=1000, n_features=64, centers=5, random_state=42
      )
  
      data_selection = np.random.RandomState(42).choice(
          [True, False], 1000, replace=True, p=[0.75, 0.25]
      )
  
      if metric == "jaccard":
          data = data >= 0
  
      new_data = scipy_sparse.csr_matrix(data[~data_selection])
  
      if umap_learn_supported:
          umap_model = umap.UMAP(
              n_neighbors=10,
              min_dist=0.01,
              metric=metric,
              init="random",
          )
          umap_embedding = umap_model.fit_transform(new_data)
          umap_trust = trustworthiness(
              data[~data_selection],
              umap_embedding,
              n_neighbors=10,
              metric=metric,
          )
  
      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(new_data)
          return
  
      cuml_embedding = cuml_model.fit_transform(new_data)
      cuml_trust = trustworthiness(
          data[~data_selection],
          cuml_embedding,
          n_neighbors=10,
          metric=metric,
      )
  
      if umap_learn_supported:
          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 23 for calling a global function with example usage: test_umap_distance_metrics_fit_transform_trust_on_sparse_input(metric, supported, umap_learn_supported) without return types