code: def _get_reshape_kernel(kd: int, ky: int, kx: int) -> Tensor:
      """Utility function, which returns neigh2channels conv kernel."""
      numel: int = kd * ky * kx
      weight = eye(numel)
      return weight.view(numel, kd, ky, kx)
  
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 1 for calling a global function with example usage: _get_reshape_kernel(kd, ky, kx) and returns: weight