code: def forward(self, x):
      out = self.conv1(x)
      out = self.batchnorm1(out)
      out = F.relu(out)
      out = F.avg_pool2d(out, 2)
      out = self.conv2(out)
      out = self.batchnorm2(out)
      out = F.relu(out)
      out = F.avg_pool2d(out, 2)
      out = out.view(out.size(0), -1)
      out = self.fc1(out)
      out = self.batchnorm3(out)
      out = F.relu(out)
      out = self.fc2(out)
      return out
  
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 2 for calling the AliceNet2 obj's underlying member method code with example usage: obj.forward(x) and returns: out