code: def backward(ctx, grad):
      if not (ctx.needs_input_grad[0] or ctx.needs_input_grad[1]):
          return None, None, None, None, None
      var = ctx.saved_tensors
      opt = ctx.opt
      grads = _C.grid_grad_backward(grad, *var, *opt)
      if ctx.needs_input_grad[0]:
          return (
              grads[0],
              grads[1] if ctx.needs_input_grad[1] else None,
              None,
              None,
              None,
          )
      if ctx.needs_input_grad[1]:
          return None, grads[0], None, None, None
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  import torch
  import torch.nn
  import monai
  from monai.networks import to_norm_affine
  from monai.utils import GridSampleMode, GridSamplePadMode, convert_to_dst_type, ensure_tuple, look_up_option, optional_import
label_desc: Use image node_id 2 for calling the _GridGrad obj's underlying member method code with example usage: obj.backward(ctx, grad) and returns: None,  None,  None,  None,  None, grads,  unknown,  None,  None,  None, None,  grads,  None,  None,  None