code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      sc = self.shortcut(x)
  
      if self.shortcut.stride == (2, 2):
          sc = sc[:, :, :-1, :-1]
  
      for layer in self.layers:
          x = layer.forward(x)
          if x.shape[-2:] != sc.shape[-2:]:
              x = x[:, :, :-1, :-1]
  
          x = x + sc
          sc = x
  
      x = self.bna_block(x)
  
      return x
  
imports: from __future__ import annotations
  import os
  import re
  import warnings
  from collections import OrderedDict
  from collections.abc import Callable, Sequence
  import torch
  import torch.nn
  from monai.apps.utils import download_url
  from monai.networks.blocks import UpSample
  from monai.networks.layers.factories import Conv, Dropout
  from monai.networks.layers.utils import get_act_layer, get_norm_layer
  from monai.utils.enums import HoVerNetBranch, HoVerNetMode, InterpolateMode, UpsampleMode
  from monai.utils.module import export, look_up_option
label_desc: Use image node_id 2 for calling the _ResidualBlock obj's underlying member method code with example usage: obj.forward(x) and returns: x