code: def __init__(self):
      super(NetworkA, self).__init__()
      self.fc1 = nn.Linear(784, 128)
      self.fc2 = nn.Linear(128, 128)
      self.fc3 = nn.Linear(128, 10)
      self.batchnorm1 = nn.BatchNorm1d(128)
      self.batchnorm2 = nn.BatchNorm1d(128)
  
imports: import logging
  import os
  import random
  import shutil
  import tempfile
  import time
  import warnings
  import crypten
  import crypten.communicator
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torch.utils.data
  import torch.utils.data.distributed
  from examples.meters import AverageMeter
  from examples.util import NoopContextManager, process_mnist_files
  from torchvision import datasets, transforms
label_desc: Use image node_id 1 to create a new NetworkA object from inherited base classes: nn with example: obj = NetworkA()