code: def __init__(self, input_dim, output_dim):
      super(HierarchicalLinearNet, self).__init__()
      self.fc1 = LinearNet(input_dim, output_dim)
      self.fc2 = LinearNet(output_dim, output_dim)
      self._num_parameters = (
          self.fc1.num_parameters + self.fc2.num_parameters
      )
  
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 HierarchicalLinearNet object from inherited base classes: nn with example: obj = HierarchicalLinearNet(input_dim, output_dim)