code: def __init__(self, in_features, out_features):
      super().__init__()
      self.linear1 = torch.nn.Linear(in_features, 100)
      self.linear2 = torch.nn.Linear(100, 50)
      self.linear3 = torch.nn.Linear(50, out_features)
      self.bn1 = torch.nn.BatchNorm1d(100)
      self.bn2 = torch.nn.BatchNorm1d(50)
  
imports: import copy
  import itertools
  import logging
  import crypten
  import torch
  from crypten.common.tensor_types import is_float_tensor
  from crypten.config import cfg
  from crypten.nn.privacy import DPSplitModel, SkippedLoss
  from test.multiprocess_test_case import get_random_test_tensor, MultiProcessTestCase
label_desc: Use image node_id 1 to create a new TestMLPBN object from inherited base classes: torch.nn with example: obj = TestMLPBN(in_features, out_features)