code: def __init__(
      self,
      num_features,
      pre_mask,
      post_mask,
      eps=1e-5,
      decay=0.9,
      affine=True,
  ):
      super(BatchNorm, self).__init__()
      self.mask_opt = Mask()
      self.pre_mask = pre_mask
      self.post_mask = post_mask
      self.bn = nn.BatchNorm1d(
          num_features, eps=eps, momentum=1.0 - decay, affine=affine
      )
  
imports: import torch
  import torch.nn.functional
  from torch import nn
  from utils import get_length, INF
label_desc: Use image node_id 1 to create a new BatchNorm object from inherited base classes: nn with example: obj = BatchNorm(num_features, pre_mask, post_mask, eps, decay, affine)