code: def test_draw_segmentation_masks_dtypes():
      num_masks, h, w = 2, 100, 100
  
      masks = torch.randint(0, 2, (num_masks, h, w), dtype=torch.bool)
  
      img_uint8 = torch.randint(
          0, 256, size=(3, h, w), dtype=torch.uint8
      )
      out_uint8 = utils.draw_segmentation_masks(img_uint8, masks)
  
      assert img_uint8 is not out_uint8
      assert out_uint8.dtype == torch.uint8
  
      img_float = to_dtype(img_uint8, torch.float, scale=True)
      out_float = utils.draw_segmentation_masks(img_float, masks)
  
      assert img_float is not out_float
      assert out_float.is_floating_point()
  
      torch.testing.assert_close(
          out_uint8,
          to_dtype(out_float, torch.uint8, scale=True),
          rtol=0,
          atol=1,
      )
  
imports: import os
  import re
  import sys
  import tempfile
  from io import BytesIO
  import numpy
  import pytest
  import torch
  import torchvision.transforms.functional
  import torchvision.utils
  from common_utils import assert_equal, cpu_and_cuda
  from PIL import __version__, Image, ImageColor
  from torchvision.transforms.v2.functional import to_dtype
label_desc: Use image node_id 15 for calling a global function with example usage: test_draw_segmentation_masks_dtypes() without return types