code: def test_with_replaycompose():
      aug = A.ReplayCompose([ToTensorV2()])
      kwargs = {
          "image": np.random.randint(
              low=0, high=256, size=(100, 100, 3), dtype=np.uint8
          ),
          "mask": np.random.randint(
              low=0, high=256, size=(100, 100, 3), dtype=np.uint8
          ),
      }
      res = aug(**kwargs)
      res2 = A.ReplayCompose.replay(res["replay"], **kwargs)
      assert np.array_equal(res["image"], res2["image"])
      assert np.array_equal(res["mask"], res2["mask"])
      assert res["image"].dtype == torch.uint8
      assert res["mask"].dtype == torch.uint8
      assert res2["image"].dtype == torch.uint8
      assert res2["mask"].dtype == torch.uint8
  
file_path: albumentations/tests/test_pytorch.py
imports: import pytest
  import numpy
  import torch
  from PIL import Image
  from torchvision.transforms import ColorJitter
  import albumentations
  from albumentations.pytorch.transforms import ToTensor, ToTensorV2
label_desc: Use image node_id 7 for calling a global function with example usage: test_with_replaycompose() without return types