class_docstr: LayerNorm for DRL.
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 logging
  import torch
  from torch import nn
  import torch.nn.functional
  import math
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