docstr: :param x: B, H * W, C
  :param H: Height
  :param W: Width
  :return: B, H * W, C
docstr_tok: [":","param","x",":","B",",","H","*","W",",","C",":","param","H",":","Height",":","param","W",":","Width",":","return",":","B",",","H","*","W",",","C"]
code: def forward(self, x, H, W):
      """
  
      :param x: B, H * W, C
      :param H: Height
      :param W: Width
      :return: B, H * W, C
      """
      x = x + self.drop_path(self.attn(self.norm1(x), H, W))
      x = x + self.drop_path(self.mlp(self.norm2(x), H, W))
  
      return x
  
imports: import math
  from functools import partial
  from typing import Optional
  import torch
  import torch.nn
  from pytorch_toolbelt.modules.interfaces import AbstractEncoder, FeatureMapsSpecification
  from pytorch_toolbelt.modules.activations import instantiate_activation_block, ACT_GELU
  from pytorch_toolbelt.modules.drop_path import DropPath
label_desc: Use image node_id 3 for calling the Block obj's underlying member method code with example usage: obj.forward(x, H, W) and returns: x