code: def backward(ctx, grad_output):
      x, _ = ctx.saved_tensors
      pos_mask_1 = (x > 0).type_as(grad_output)
      pos_mask_2 = (grad_output > 0).type_as(grad_output)
      y = torch.mul(grad_output, pos_mask_1)
      grad_input = torch.mul(y, pos_mask_2)
      return grad_input
  
imports: from __future__ import annotations
  from functools import partial
  from typing import Any, Callable
  import torch
  from monai.networks.utils import replace_modules_temp
  from monai.utils.module import optional_import
  from monai.visualize.class_activation_maps import ModelWithHooks
label_desc: Use image node_id 2 for calling the _AutoGradReLU obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: grad_input