code: def forward(self, x: Tensor) -> Tensor:
      # fusecat = torch.cat(x, dim=1)
      attn = self.relu(self.norm_layer1(self.conv1(x)))
      attn = self.relu(self.norm_layer2(self.conv2(attn)))
      attn = F.softmax(self.conv3(attn), dim=1)
  
      # return ((fusecat * attn).sum(1)).unsqueeze(1)
      return ((x * attn).sum(1))[:, None, ...]
  
imports: from __future__ import annotations
  from collections import OrderedDict
  from typing import Optional
  import torch
  import torch.nn.functional
  from torch import nn
  from kornia.core import Module, Tensor, concatenate
  from kornia.core.check import KORNIA_CHECK
  from kornia.utils import map_location_to_cpu
label_desc: Use image node_id 2 for calling the CoFusion obj's underlying member method code with example usage: obj.forward(x) and returns: unknown