class_docstr: Construct a layernorm module in the TF style (epsilon inside the square root).
class_docstr_tok: ["Construct","a","layernorm","module","in","the","TF","style","(","epsilon","inside","the","square","root",")","."]
code: def forward(self, x):
      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 + self.bias
  
imports: import torch
  from torch import nn
  from collections import OrderedDict
  from towhee.models.utils.weight_init import trunc_normal_
  from towhee.models.utils.init_vit_weights import init_vit_weights
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