code: def forward(self, enc_feat, dec_feat, w=1):
      enc_feat = self.encode_enc(torch.cat([enc_feat, dec_feat], dim=1))
      scale = self.scale(enc_feat)
      shift = self.shift(enc_feat)
      residual = w * (dec_feat * scale + shift)
      out = dec_feat + residual
      return out
  
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 2 for calling the Fuse_sft_block obj's underlying member method code with example usage: obj.forward(enc_feat, dec_feat, w) and returns: out