code: def backward(ctx, grad):
      if ctx.needs_input_grad[0]:
          var = ctx.saved_tensors
          opt = ctx.opt
          return (
              _C.grid_count_backward(grad, *var, *opt),
              None,
              None,
              None,
              None,
          )
      return None, None, 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 _GridCount obj's underlying member method code with example usage: obj.backward(ctx, grad) and returns: None,  None,  None,  None,  None, _C,  None,  None,  None,  None