code: def __init__(self):
      super(AliceNet, self).__init__()
      self.fc1 = torch.nn.Linear(50, 20)
      self.fc2 = torch.nn.Linear(20, 2)
  
imports: import copy
  import itertools
  import logging
  import unittest
  import crypten
  import crypten.communicator
  import torch
  import torch.nn.functional
  from crypten.common.rng import generate_random_ring_element
  from crypten.common.tensor_types import is_float_tensor
  from crypten.config import cfg
  from crypten.encoder import FixedPointEncoder
  from test.multiprocess_test_case import get_random_linear, get_random_test_tensor, MultiProcessTestCase, onehot
label_desc: Use image node_id 1 to create a new AliceNet object from inherited base classes: torch.nn with example: obj = AliceNet()