code: def __init__(self, channels, eps=1e-5):
      super().__init__()
      self.channels = channels
      self.eps = eps
  
      self.gamma = nn.Parameter(torch.ones(channels))
      self.beta = nn.Parameter(torch.zeros(channels))
  
imports: import torch
  from torch import nn
  from torch.nn import Conv1d
  from torch.nn import functional
  from torch.nn.utils.parametrizations import weight_norm
  from torch.nn.utils.parametrize import remove_parametrizations
  import TTS.vc.modules.freevc.commons
  from TTS.vc.modules.freevc.commons import get_padding, init_weights
label_desc: Use image node_id 1 to create a new LayerNorm object from inherited base classes: nn with example: obj = LayerNorm(channels, eps)