code: def test_gaussian_blur(device, channels, meth_kwargs):
      if all(
          [
              device == "cuda",
              channels == 1,
              meth_kwargs["kernel_size"] in [23, [23]],
              torch.version.cuda == "11.3",
              sys.platform in ("win32", "cygwin"),
          ]
      ):
          pytest.skip(
              "Fails on Windows, see https://github.com/pytorch/vision/issues/5464"
          )
  
      tol = 1.0 + 1e-10
      torch.manual_seed(12)
      _test_class_op(
          T.GaussianBlur,
          meth_kwargs=meth_kwargs,
          channels=channels,
          test_exact_match=False,
          device=device,
          agg_method="max",
          tol=tol,
      )
  
imports: import os
  import sys
  import numpy
  import PIL.Image
  import pytest
  import torch
  from common_utils import _assert_approx_equal_tensor_to_pil, _assert_equal_tensor_to_pil, _create_data, _create_data_batch, assert_equal, cpu_and_cuda, float_dtypes, get_tmp_dir, int_dtypes
  from torchvision import transforms
  from torchvision.transforms import functional, InterpolationMode
  from torchvision.transforms.autoaugment import _apply_op
label_desc: Use image node_id 43 for calling a global function with example usage: test_gaussian_blur(device, channels, meth_kwargs) without return types