class_docstr: We just want input[:, :-padding, :-padding, :] but the backward pass of slicing is slower
  that it should be (it goes through 2 SliceBackward functions instead of just 1).
  https://github.com/pytorch/pytorch/issues/63921
  So we write a custom backward function.
code: def forward(ctx, input, padding):
      assert input.ndim == 4
      ctx.padding = padding
      return input[:, :-padding, :-padding, :]
  
file_path: zoo/src/ops/dwconv.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.cuda.amp import custom_bwd, custom_fwd
  from einops import rearrange
label_desc: Use image node_id 1 for calling the SubsetHW obj's underlying member method code with example usage: obj.forward(ctx, input, padding) and returns: input