code: def test_gaussian_blur2d_tensor(
      ksize_x, ksize_y, sigma, device, dtype
  ):
      sigma = torch.tensor(sigma, device=device, dtype=dtype)
      bs = sigma.shape[0]
      sample = torch.rand(bs, 3, 16, 16, device=device, dtype=dtype)
      actual = gaussian_blur2d(
          sample,
          (ksize_y, ksize_x),
          sigma,
          "replicate",
          separable=False,
      )
      actual_sep = gaussian_blur2d(
          sample, (ksize_y, ksize_x), sigma, "replicate", separable=True
      )
  
      assert_close(actual, actual_sep)
  
imports: import pytest
  import torch
  from kornia.filters import GaussianBlur2d, gaussian_blur2d, get_gaussian_discrete_kernel1d, get_gaussian_erf_kernel1d, get_gaussian_kernel1d, get_gaussian_kernel2d, get_gaussian_kernel3d
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 12 for calling a global function with example usage: test_gaussian_blur2d_tensor(ksize_x, ksize_y, sigma, device, dtype) without return types