class_docstr: Bi-LSTM NER model with CRF classification layer (tf.keras model)
  
  Args:
      use_cudnn (bool, optional): use cudnn LSTM cells
docstr: Save model to path
  
  Args:
      path (str): path to save model weights
docstr_tok: ["Save","model","to","path","Args",":","path","(","str",")",":","path","to","save","model","weights"]
code: def save(self, path):
      """
      Save model to path
  
      Args:
          path (str): path to save model weights
      """
      topology = {k: v for k, v in self.__dict__.items()}
      topology.pop("model")
      topology.pop("use_cudnn")
      save_model(self.model, topology, path)
  
file_path: nlp-architect/nlp_architect/models/ner_crf.py
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 7 for calling the NERCRF obj's underlying member method code with example usage: obj.save(path) without return types