code: def __init__(self, in_ch: int, out_ch: int) -> None:
      super().__init__()
      self.conv1 = nn.Conv2d(
          in_ch, 64, kernel_size=3, stride=1, padding=1
      )
      self.conv2 = nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=1)
      self.conv3 = nn.Conv2d(
          64, out_ch, kernel_size=3, stride=1, padding=1
      )
      self.relu = nn.ReLU()
      self.norm_layer1 = nn.GroupNorm(4, 64)
      self.norm_layer2 = nn.GroupNorm(4, 64)
  
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 1 to create a new CoFusion object from inherited base classes: Module with example: obj = CoFusion(in_ch, out_ch)