code: def test_torch_to_tensor_v2_on_gray_scale_images():
      aug = ToTensorV2()
      grayscale_image = np.random.randint(
          low=0, high=256, size=(100, 100), dtype=np.uint8
      )
      data = aug(image=grayscale_image)
      assert isinstance(data["image"], torch.Tensor)
      assert len(data["image"].shape) == 3
      assert data["image"].shape[1:] == grayscale_image.shape
      assert data["image"].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 5 for calling a global function with example usage: test_torch_to_tensor_v2_on_gray_scale_images() without return types