code: def forward(self, x, feat_size: List[int]):
      x = x + self.drop_path1(self.attn(self.norm1(x), feat_size))
      x = x + self.drop_path2(self.mlp(self.norm2(x), feat_size))
  
      return x
  
imports: import math
  from typing import Tuple, List, Callable, Union
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import DropPath, to_2tuple, to_ntuple, trunc_normal_, LayerNorm, use_fused_attn
  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 Block obj's underlying member method code with example usage: obj.forward(x, feat_size) and returns: x