code: def forward(self, x, size: Size_):
      x = x + self.drop_path1(self.attn(self.norm1(x), size))
      x = x + self.drop_path2(self.mlp(self.norm2(x)))
      return x
  
imports: import math
  from functools import partial
  from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import Mlp, DropPath, to_2tuple, trunc_normal_, use_fused_attn
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_module
  from ._registry import register_model, generate_default_cfgs
  from .vision_transformer import Attention
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.forward(x, size) and returns: x