code: def forward(self, x):
      for index, (attn, ff) in enumerate(self.layers):
          x = attn(x) + x
          x = ff(x) + x
  
          if index == self.patch_merge_layer_index:
              x = self.patch_merger(x)
  
      return self.norm(x)
  
imports: import torch
  from torch import nn
  from einops import rearrange, repeat
  from einops.layers.torch import Rearrange, Reduce
label_desc: Use image node_id 2 for calling the Transformer obj's underlying member method code with example usage: obj.forward(x) and returns: self