code: def __init__(self, input_dim, output_dim):
      super(DuplicatedLinearNet, self).__init__()
      self.fc1 = nn.Linear(input_dim, output_dim)
      self.fc2 = nn.Linear(output_dim, output_dim)
      self._num_parameters = input_dim * output_dim + output_dim**2
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import pytest
  import numpy
  import torch
  import torch.nn
  import torch.optim
  from torch.utils.data import Dataset, DataLoader
  import bluefog.torch
  from bluefog.common import topology_util
label_desc: Use image node_id 1 to create a new DuplicatedLinearNet object from inherited base classes: nn with example: obj = DuplicatedLinearNet(input_dim, output_dim)