code: def test_non_consecutive_indexed_semi_supervised_classificaton_classes():
      iris = datasets.load_iris()
      x = iris.data
      y = iris.target
  
      # Make labels non-consecutive indexed
      y[y == max(y)] = max(y) + 1
  
      # Mark points as unlabeled
      mask = np.random.choice(
          range(len(y)), size=len(y) // 2, replace=False
      )
      y[mask] = -1
  
      supervision_metric = "sparse_categorical_crossentropy"
      ivis_iris = Ivis(
          k=15,
          batch_size=16,
          epochs=5,
          supervision_metric=supervision_metric,
      )
  
      with pytest.raises(ValueError):
          embeddings = ivis_iris.fit_transform(x, y)
  
file_path: ivis/tests/integration/test_semi-supervised_iris.py
imports: import pytest
  from sklearn import datasets
  import numpy
  from ivis import Ivis
label_desc: Use image node_id 4 for calling a global function with example usage: test_non_consecutive_indexed_semi_supervised_classificaton_classes() without return types