code: def __init__(self, in_ch, out_ch):
      super().__init__()
      self.encode_enc = ResBlock(2 * in_ch, out_ch)
  
      self.scale = nn.Sequential(
          nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=1),
          nn.LeakyReLU(0.2, True),
          nn.Conv2d(out_ch, out_ch, kernel_size=3, padding=1),
      )
  
      self.shift = nn.Sequential(
          nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=1),
          nn.LeakyReLU(0.2, True),
          nn.Conv2d(out_ch, out_ch, kernel_size=3, padding=1),
      )
  
imports: import math
  import torch
  from torch import nn, Tensor
  import torch.nn.functional
  from typing import Optional
  from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock
  from basicsr.utils.registry import ARCH_REGISTRY
label_desc: Use image node_id 1 to create a new Fuse_sft_block object from inherited base classes: nn with example: obj = Fuse_sft_block(in_ch, out_ch)