code: def __init__(self, num_features):
      super().__init__()
      self.num_features = num_features
      self.bn = nn.BatchNorm1d(num_features=num_features)
  
imports: import torch
  import torch.nn
  from timm.models.layers import DropPath, to_2tuple, trunc_normal_
  from typing import Optional, Callable
label_desc: Use image node_id 1 to create a new VITBatchNorm object from inherited base classes: nn with example: obj = VITBatchNorm(num_features)