code: def test_umap_transform_on_iris(target_metric):
      iris = datasets.load_iris()
  
      iris_selection = np.random.RandomState(42).choice(
          [True, False], 150, replace=True, p=[0.75, 0.25]
      )
      data = iris.data[iris_selection]
  
      fitter = cuUMAP(
          n_neighbors=10,
          init="random",
          n_epochs=800,
          min_dist=0.01,
          random_state=42,
          target_metric=target_metric,
      )
      fitter.fit(data, convert_dtype=True)
      new_data = iris.data[~iris_selection]
      embedding = fitter.transform(new_data, convert_dtype=True)
  
      assert not np.isnan(embedding).any()
  
      trust = trustworthiness(new_data, embedding, n_neighbors=10)
      assert trust >= 0.85
  
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 6 for calling a global function with example usage: test_umap_transform_on_iris(target_metric) without return types