code: def __init__(self, n_units, n_out):
      super(MLP, self).__init__()
      with self.init_scope():
          self.l1 = L.Linear(784, n_units)
          self.l2 = L.Linear(n_units, n_units)
          self.l3 = L.Linear(n_units, n_out)
  
imports: import mock
  import tempfile
  import pytest
  import chainer
  import chainer.links
  import chainer.functions
  from chainer.training import extensions
  from chainer.training import StandardUpdater
  from chainer.training import Trainer
  import chainermn
  from chainermn import create_communicator
  from chainermn.extensions import multi_node_snapshot
  from chainermn.extensions import _multi_node_snapshot
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: chainer with example: obj = MLP(n_units, n_out)