code: def __init__(self, num_features, bias=True):
      super().__init__()
      self.num_features = num_features
      self.bias = bias
      self.instance_norm = nn.InstanceNorm2d(
          num_features, affine=False, track_running_stats=False
      )
      self.alpha = nn.Parameter(torch.zeros(num_features))
      self.gamma = nn.Parameter(torch.zeros(num_features))
      self.alpha.data.normal_(1, 0.02)
      self.gamma.data.normal_(1, 0.02)
      if bias:
          self.beta = nn.Parameter(torch.zeros(num_features))
  
imports: import functools
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new InstanceNorm2dPlus object from inherited base classes: nn with example: obj = InstanceNorm2dPlus(num_features, bias)