code: def test_shape(
      self,
      init_data,
      call_data,
      map_expected_shape,
      most_prob_expected_shape,
  ):
      occ_sens = OcclusionSensitivity(**init_data)
      m, most_prob = occ_sens(**call_data)
      self.assertTupleEqual(m.shape, map_expected_shape)
      self.assertTupleEqual(most_prob.shape, most_prob_expected_shape)
      # most probable class should be of type int, and should have min>=0, max<num_classes
      self.assertEqual(most_prob.dtype, torch.int64)
      self.assertGreaterEqual(most_prob.min(), 0)
      self.assertLess(most_prob.max(), m.shape[-1])
  
file_path: MONAI/tests/test_occlusion_sensitivity.py
imports: from __future__ import annotations
  import unittest
  from typing import Any
  import torch
  from parameterized import parameterized
  from monai.networks.nets import DenseNet, DenseNet121
  from monai.visualize import OcclusionSensitivity
label_desc: Use image node_id 1 for calling the TestComputeOcclusionSensitivity obj's underlying member method code with example usage: obj.test_shape(init_data, call_data, map_expected_shape, most_prob_expected_shape) without return types