code: def test_multiclass(dtype):
      actuals = tf.constant(
          [
              [1, 0, 0, 0],
              [0, 0, 1, 0],
              [0, 0, 0, 1],
              [0, 1, 0, 0],
              [0, 1, 0, 0],
              [1, 0, 0, 0],
              [0, 0, 1, 0],
              [1, 0, 0, 0],
              [0, 0, 1, 0],
              [0, 0, 0, 1],
          ],
          dtype=dtype,
      )
      preds = tf.constant(
          [
              [1, 0, 0, 0],
              [0, 0, 1, 0],
              [0, 0, 0, 1],
              [1, 0, 0, 0],
              [1, 0, 0, 0],
              [1, 0, 0, 0],
              [0, 0, 1, 0],
              [1, 0, 0, 0],
              [0, 1, 0, 0],
              [0, 0, 0, 1],
          ],
          dtype=dtype,
      )
  
      # Initialize
      mcm_obj = MultiLabelConfusionMatrix(num_classes=4, dtype=dtype)
      mcm_obj.update_state(actuals, preds)
      # Check results
      check_results(
          mcm_obj,
          [
              [[5, 2], [0, 3]],
              [[7, 1], [2, 0]],
              [[7, 0], [1, 2]],
              [[8, 0], [0, 2]],
          ],
      )
  
file_path: addons/tensorflow_addons/metrics/tests/multilabel_confusion_matrix_test.py
imports: import numpy
  import pytest
  import tensorflow
  from tensorflow_addons.metrics import MultiLabelConfusionMatrix
label_desc: Use image node_id 5 for calling a global function with example usage: test_multiclass(dtype) without return types