code: def dog_response_single(
      input: Tensor, sigma1: float = 1.0, sigma2: float = 1.6
  ) -> Tensor:
      r"""Compute the Difference-of-Gaussian response.
  
      .. image:: _static/img/dog_response_single.png
  
      Args:
          input: a given the gaussian 4d tensor :math:`(B, C, H, W)`.
          sigma1: lower gaussian sigma
          sigma2: bigger gaussian sigma
  
      Return:
          the response map per channel with shape :math:`(B, C, H, W)`.
      """
      KORNIA_CHECK_SHAPE(input, ["B", "C", "H", "W"])
      ks1 = _get_kernel_size(sigma1)
      ks2 = _get_kernel_size(sigma1)
      g1 = gaussian_blur2d(input, (ks1, ks1), (sigma1, sigma1))
      g2 = gaussian_blur2d(input, (ks2, ks2), (sigma2, sigma2))
      return g2 - g1
  
imports: from typing import Optional, Union
  import torch
  from kornia.core import Module, Tensor, tensor
  from kornia.core.check import KORNIA_CHECK_SHAPE
  from kornia.filters import gaussian_blur2d, spatial_gradient
label_desc: Use image node_id 6 for calling a global function with example usage: dog_response_single(input, sigma1, sigma2) and returns: unknown