code: def supervised_iris_model(iris):
      return UMAP(
          n_neighbors=10, min_dist=0.01, n_epochs=200, random_state=42
      ).fit(iris.data, iris.target)
  
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 22 for calling a global function with example usage: supervised_iris_model(iris) and returns: UMAP