code: def test_get_gaussian_kernel2d_float(
      ksize_x, ksize_y, sigma, device, dtype
  ):
      actual = get_gaussian_kernel2d(
          (ksize_y, ksize_x), sigma, device=device, dtype=dtype
      )
      expected = torch.ones(1, device=device, dtype=dtype)
  
      assert actual.shape == (1, ksize_y, ksize_x)
      assert_close(actual.sum(), expected.sum())
  
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 3 for calling a global function with example usage: test_get_gaussian_kernel2d_float(ksize_x, ksize_y, sigma, device, dtype) without return types