code: def __init__(
      self,
      num_features: int,
      momentum: float = 0.05,
      epsilon: float = 1e-3,
      virtual_batch_size: Optional[int] = 128,
  ):
      super().__init__()
      self.num_features = num_features
      self.virtual_batch_size = virtual_batch_size
      self.bn = torch.nn.BatchNorm1d(
          num_features, momentum=momentum, eps=epsilon
      )
  
imports: import logging
  from typing import Optional
  import numpy
  import torch
  from torch.nn import BatchNorm1d, BatchNorm2d, LayerNorm, Module
  from ludwig.utils.torch_utils import LudwigModule
label_desc: Use image node_id 1 to create a new GhostBatchNormalization object from inherited base classes: LudwigModule with example: obj = GhostBatchNormalization(num_features, momentum, epsilon, virtual_batch_size)