code: def forward(self, x):
      mean = torch.mean(x, 1, keepdim=True)
      variance = torch.mean((x - mean) ** 2, 1, keepdim=True)
      x = (x - mean) * torch.rsqrt(variance + self.eps)
      x = x * self.gamma + self.beta
      return x
  
file_path: TTS/TTS/tts/layers/generic/normalization.py
imports: import torch
  from torch import nn
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: x