code: def save_models(self, folder):
      with tf.device("/gpu:0"):
          saveNodes = list(
              [
                  n.name
                  for n in tf.get_default_graph().as_graph_def().node
                  if n.name.startswith("save/")
              ]
          )
          if len(saveNodes) == 0:
              saver = tf.train.Saver()
  
          variables_file = os.path.join(folder, "variables")
          self.ner.session.run(
              "save/control_dependency",
              feed_dict={"save/Const:0": variables_file},
          )
          tf.train.write_graph(
              self.ner.session.graph, folder, "saved_model.pb", False
          )
  
file_path: spark-nlp/examples/python/training/english/dl-ner/nerdl-graph/ner_model_saver.py
imports: import numpy
  import os
  import tensorflow
  import string
  import random
  import math
  import sys
label_desc: Use image node_id 3 for calling the NerModelSaver obj's underlying member method code with example usage: obj.save_models(folder) without return types