code: def __init__(self, d_hid, eps=1e-3, affine=True):
      super(LayerNormalization, self).__init__()
  
      self.eps = eps
      self.affine = affine
      if self.affine:
          self.a_2 = nn.Parameter(torch.ones(d_hid), requires_grad=True)
          self.b_2 = nn.Parameter(
              torch.zeros(d_hid), requires_grad=True
          )
  
imports: import numpy
  import functools
  import sys
  import torch
  from torch.autograd import Variable
  import torch.nn
  import torch.nn.init
label_desc: Use image node_id 1 to create a new LayerNormalization object from inherited base classes: nn with example: obj = LayerNormalization(d_hid, eps, affine)