code: def test_multi_label_two_classes_has_two_columns():
      analyser = output_analysers.ClassificationAnalyser(
          name="a", multi_label=True
      )
      dataset = tf.data.Dataset.from_tensor_slices(
          np.random.rand(10, 2)
      ).batch(32)
  
      for data in dataset:
          analyser.update(data)
      analyser.finalize()
  
      assert analyser.encoded
  
file_path: autokeras/autokeras/analysers/output_analysers_test.py
imports: import numpy
  import pytest
  import tensorflow
  from autokeras import test_utils
  from autokeras.analysers import output_analysers
label_desc: Use image node_id 9 for calling a global function with example usage: test_multi_label_two_classes_has_two_columns() without return types