code: def iris_subset_model_large(iris, iris_selection):
      return UMAP(
          n_neighbors=10,
          min_dist=0.01,
          random_state=42,
          force_approximation_algorithm=True,
      ).fit(iris.data[iris_selection])
  
imports: import pytest
  import numpy
  from scipy import sparse
  from sklearn.datasets import load_iris
  from umap import UMAP, AlignedUMAP
label_desc: Use image node_id 21 for calling a global function with example usage: iris_subset_model_large(iris, iris_selection) and returns: UMAP