code: def test_blend(self, image, label, alpha):
      blended = blend_images(image, label, alpha)
      self.assertEqual(type(image), type(blended))
      if isinstance(blended, torch.Tensor):
          self.assertEqual(blended.device, image.device)
          blended = blended.cpu().numpy()
      self.assertEqual((3,) + image[0].shape, blended.shape)
  
      blended = moveaxis(blended, 0, -1)  # move RGB component to end
      if blended.ndim > 3:
          blended = blended[blended.shape[0] // 2]
      plt.imshow(blended)
  
file_path: MONAI/tests/test_blend_images.py
imports: from __future__ import annotations
  import unittest
  from unittest.case import skipUnless
  import numpy
  import torch
  from parameterized import parameterized
  from monai.data.synthetic import create_test_image_2d, create_test_image_3d
  from monai.transforms.utils_pytorch_numpy_unification import moveaxis
  from monai.utils.module import optional_import
  from monai.visualize.utils import blend_images
  from tests.utils import TEST_NDARRAYS
label_desc: Use image node_id 1 for calling the TestBlendImages obj's underlying member method code with example usage: obj.test_blend(image, label, alpha) without return types