class_docstr: Multi-Task Intent and Slot tagging model (using tf.keras)
  
  Args:
      use_cudnn (bool, optional): use GPU based model (CUDNNA cells)
class_docstr_tok: ["Multi-Task","Intent","and","Slot","tagging","model","(","using","tf.keras",")","Args",":","use_cudnn","(","bool",",","optional",")",":","use","GPU","based","model","(","CUDNNA","cells",")"]
docstr: Save model to path
  
  Args:
      path (str): path to save model
docstr_tok: ["Save","model","to","path","Args",":","path","(","str",")",":","path","to","save","model"]
code: def save(self, path):
      """
      Save model to path
  
      Args:
          path (str): path to save model
      """
      super().save(path, ["use_cudnn"])
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import tensorflow
  from nlp_architect.nn.tensorflow.python.keras.layers.crf import CRF
  from nlp_architect.nn.tensorflow.python.keras.utils import load_model, save_model
label_desc: Use image node_id 4 for calling the MultiTaskIntentModel obj's underlying member method code with example usage: obj.save(path) without return types