code: def test_clf_with_nan(self, input_data, expected_value):
      params = input_data.copy()
      vals = {}
      vals["y_pred"] = params.pop("y_pred")
      vals["y"] = params.pop("y")
      metric = ConfusionMatrixMetric(**params)
      result = metric(**vals)
      assert_allclose(result, expected_value, atol=1e-4, rtol=1e-4)
      result, _ = metric.aggregate(reduction="mean_channel")[0]
      expected_value, _ = do_metric_reduction(
          expected_value, "mean_channel"
      )
      expected_value = compute_confusion_matrix_metric(
          "tpr", expected_value
      )
      assert_allclose(result, expected_value, atol=1e-4, rtol=1e-4)
  
file_path: MONAI/tests/test_compute_confusion_matrix.py
imports: from __future__ import annotations
  import unittest
  from typing import Any
  import numpy
  import torch
  from parameterized import parameterized
  from monai.metrics import ConfusionMatrixMetric, compute_confusion_matrix_metric, do_metric_reduction, get_confusion_matrix
  from tests.utils import assert_allclose
label_desc: Use image node_id 5 for calling the TestConfusionMatrix obj's underlying member method code with example usage: obj.test_clf_with_nan(input_data, expected_value) without return types