code: def load_model(directory):
      """Loads a model saved.
  
      Args:
          directory (str): Path to a directory where you load a model.
  
      Returns:
          tuple: ``(model, vocab)`` where ``model`` is a loaded model and
          ``vocab`` is a ``dict`` storing its vocabulary.
  
      """
      with open(os.path.join(directory, "parameter.json")) as f:
          parameters = json.load(f)
  
      max_memory = parameters["max_memory"]
      vocab = collections.defaultdict(lambda: 0)
      vocab.update(parameters["vocabulary"])
  
      encoder = make_encoder(parameters["sentence_repr"])
      network = MemNN(
          parameters["unit"],
          len(vocab),
          encoder,
          max_memory,
          parameters["hop"],
      )
      model = chainer.links.Classifier(network, label_key="answer")
      chainer.serializers.load_npz(
          os.path.join(directory, "model.npz"), model
      )
  
      return model, vocab
  
imports: import collections
  import json
  import os
  import numpy
  import six
  import chainer
  from chainer import backend
  import chainer.functions
  from chainer import initializers
  import chainer.links
  import babi
label_desc: Use image node_id 6 for calling a global function with example usage: load_model(directory) and returns: model,  vocab