code: def get_sift_pooling_kernel(ksize: int = 25) -> Tensor:
      r"""Return a weighted pooling kernel for SIFT descriptor.
  
      Args:
          ksize: kernel_size.
  
      Returns:
          the pooling kernel with shape :math:`(ksize, ksize)`.
      """
      ks_2: float = float(ksize) / 2.0
      xc2 = ks_2 - (torch.arange(ksize).float() + 0.5 - ks_2).abs()
      kernel = torch.ger(xc2, xc2) / (ks_2**2)
      return kernel
  
imports: import math
  from typing import Tuple
  import torch
  from torch import nn
  from kornia.core import Module, Tensor, concatenate, eye, normalize
  from kornia.core.check import KORNIA_CHECK_SHAPE
  from kornia.filters import get_gaussian_kernel2d, spatial_gradient
  from kornia.geometry.conversions import pi
label_desc: Use image node_id 2 for calling a global function with example usage: get_sift_pooling_kernel(ksize) and returns: kernel