code: def backward(ctx: Any, combined_output: Tensor):
      combined_output = combined_output.contiguous()
      grad_expert_output = torch.zeros(
          ctx.expert_output.shape,
          dtype=combined_output.dtype,
          device=combined_output.device,
      )
      for g, i, l in zip(
          ctx.gates_h2, ctx.config.indices_, ctx.config.locations_
      ):
          ctx.config.func_fwd(
              g,
              i,
              l,
              combined_output,
              grad_expert_output,
              extra=[
                  ctx.config.indices_[0].size(0),
                  ctx.config.aligned_dim,
                  ctx.config.capacity,
              ],
          )
  
      grad_gates = []
      if id(ctx.gates_h2[0]) != id(ctx.config.ones_helper):
          for i, l in zip(ctx.config.indices_, ctx.config.locations_):
              grad_gates1_s = torch.empty(
                  [
                      ctx.config.sample_size,
                  ],
                  dtype=combined_output.dtype,
                  device=combined_output.device,
              )
              ctx.config.func_bwd_gate(
                  grad_gates1_s,
                  i,
                  l,
                  combined_output,
                  ctx.expert_output,
                  extra=[
                      ctx.config.indices_[0].size(0),
                      ctx.config.aligned_dim,
                      ctx.config.capacity,
                  ],
              )
              grad_gates.append(grad_gates1_s)
      return (None, grad_expert_output, *grad_gates)
  
imports: from typing import TYPE_CHECKING, Any, Optional, Tuple, Union, cast
  import logging
  import torch
  from torch import Tensor
  from .jit_compiler import IS_HIP_EXTENSION
  from ..jit_kernels import sparse
  from ..jit_kernels.gating import fast_cumsum_sub_one
  from .communicate import get_world_rank, simple_all_reduce
  from .None import losses
label_desc: Use image node_id 2 for calling the GatingDecoder obj's underlying member method code with example usage: obj.backward(ctx, combined_output) and returns: None,  grad_expert_output,  unknown