class_docstr: Flask SentenceBERT server, which helps to calculate str/token embeddings
class_docstr_tok: ["Flask","SentenceBERT","server",",","which","helps","to","calculate","str\/token","embeddings"]
code: def run(self, url, port=None):
      if port is None:
          port = BERT_RETRIEVER_PORT_NUM
      threading.Thread(
          target=lambda: self.app.run(
              host=url, threaded=True, port=port
          )
      ).start()
  
file_path: NeMo/nemo/collections/nlp/modules/common/megatron/retrieval_services/bert_service.py
imports: import base64
  import pickle
  import threading
  import time
  from typing import List, Union
  import torch
  from flask import Flask, jsonify, request
  from flask_restful import Api, Resource
  from sentence_transformers import SentenceTransformer
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
label_desc: Use image node_id 2 for calling the SentenceBertServer obj's underlying member method code with example usage: obj.run(url, port) without return types