class_docstr: Block in Shunted Transformer
  
  Args:
      dim (`int`): feature dimension
      num_heads (`int`): number of attention heads
      mlp_ratio (`float`): number to scale hidden dimension in mlp
      qkv_bias (`bool`): flag to use bias in qkv
      qk_scale (`int`): number to scale qk
      drop (`float`): drop rate of Mlp
      attn_drop (`float`): drop rate of attention
      drop_path (`float`): drop rate of drop path
      act_layer (`nn.Module`): activation layer
      norm_layer (`nn.Module`): normalization layer
      sr_ratio (`int`): shunt rate
class_docstr_tok: ["Block","in","Shunted","Transformer","Args",":","dim","(","`","int","`",")",":","feature","dimension","num_heads","(","`","int","`",")",":","number","of","attention","heads","mlp_ratio","(","`","float","`",")",":","number","to","scale","hidden","dimension","in","mlp","qkv_bias","(","`","bool","`",")",":","flag","to","use","bias","in","qkv","qk_scale","(","`","int","`",")",":","number","to","scale","qk","drop","(","`","float","`",")",":","drop","rate","of","Mlp","attn_drop","(","`","float","`",")",":","drop","rate","of","attention","drop_path","(","`","float","`",")",":","drop","rate","of","drop","path","act_layer","(","`","nn.Module","`",")",":","activation","layer","norm_layer","(","`","nn.Module","`",")",":","normalization","layer","sr_ratio","(","`","int","`",")",":","shunt","rate"]
code: def forward(self, x, h, w):
      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 torch
  from torch import nn
  from towhee.models.layers.patch_embed2d import PatchEmbed2D
  from towhee.models.layers.mlp import Mlp
  from towhee.models.layers.droppath import DropPath
  from towhee.models.utils.init_vit_weights import init_vit_weights
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.forward(x, h, w) and returns: x