code: def test_sink_mask(self):
      transform = UltrasoundConfidenceMapTransform(sink_mode="mask")
  
      # This should not raise an exception for torch tensor with mask
      result_torch = transform(
          self.input_img_torch, self.input_mask_torch
      )
      self.assertIsInstance(result_torch, torch.Tensor)
  
      # This should not raise an exception for numpy array with mask
      result_np = transform(self.input_img_np, self.input_mask_np)
      self.assertIsInstance(result_np, np.ndarray)
  
      # This should raise an exception for torch tensor without mask
      with self.assertRaises(ValueError):
          transform(self.input_img_torch)
  
      # This should raise an exception for numpy array without mask
      with self.assertRaises(ValueError):
          transform(self.input_img_np)
  
file_path: MONAI/tests/test_ultrasound_confidence_map_transform.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from monai.transforms import UltrasoundConfidenceMapTransform
  from tests.utils import assert_allclose
label_desc: Use image node_id 10 for calling the TestUltrasoundConfidenceMapTransform obj's underlying member method code with example usage: obj.test_sink_mask() without return types