code: def forward(self, x, x_prev):
      x_left = self.conv_prev_1x1(x_prev)
      x_right = self.conv_1x1(x)
  
      x_comb_iter_0_left = self.comb_iter_0_left(x_right)
      x_comb_iter_0_right = self.comb_iter_0_right(x_left)
      x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right
  
      x_comb_iter_1_left = self.comb_iter_1_left(x_left)
      x_comb_iter_1_right = self.comb_iter_1_right(x_left)
      x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right
  
      x_comb_iter_2_left = self.comb_iter_2_left(x_right)
      x_comb_iter_2 = x_comb_iter_2_left + x_left
  
      x_comb_iter_3_left = self.comb_iter_3_left(x_left)
      x_comb_iter_3_right = self.comb_iter_3_right(x_left)
      x_comb_iter_3 = x_comb_iter_3_left + x_comb_iter_3_right
  
      x_comb_iter_4_left = self.comb_iter_4_left(x_right)
      x_comb_iter_4 = x_comb_iter_4_left + x_right
  
      x_out = torch.cat(
          [
              x_left,
              x_comb_iter_0,
              x_comb_iter_1,
              x_comb_iter_2,
              x_comb_iter_3,
              x_comb_iter_4,
          ],
          1,
      )
      return x_out
  
imports: from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.layers import ConvNormAct, create_conv2d, create_pool2d, create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 2 for calling the NormalCell obj's underlying member method code with example usage: obj.forward(x, x_prev) and returns: x_out