code: def load_saved_model():
      if model_type == "seq2seq":
          model = Seq2SeqIntentModel()
      else:
          model = MultiTaskIntentModel()
      model.load(args.model_path)
      return model
  
file_path: nlp-architect/examples/intent_extraction/interactive.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import argparse
  import pickle
  import numpy
  from nlp_architect.models.intent_extraction import MultiTaskIntentModel, Seq2SeqIntentModel
  from nlp_architect.utils.generic import pad_sentences
  from nlp_architect.utils.io import validate_existing_filepath
  from nlp_architect.utils.text import SpacyInstance
label_desc: Use image node_id 2 for calling a global function with example usage: load_saved_model() and returns: model