code: def forward(self, x):
      pdtype = x.dtype
      x = x.float()
      u = x.mean(-1, keepdim=True)
      s = (x - u).pow(2).mean(-1, keepdim=True)
      x = (x - u) / torch.sqrt(s + self.variance_epsilon)
      return self.weight * x.to(pdtype) + self.bias
  
imports: import os
  from collections import OrderedDict
  import torch
  from mmcv.cnn.bricks import DropPath
  from torch import nn
  from transformers import CLIPTokenizer
  from .utils import get_prompt_templates
label_desc: Use image node_id 2 for calling the LayerNorm obj's underlying member method code with example usage: obj.forward(x) and returns: unknown