code: def generate_stream_gate(self, params):
      self.call_ct += 1
  
      try:
          for output in self.generate_stream_func(
              self.model,
              self.tokenizer,
              params,
              self.device,
              self.context_len,
              self.stream_interval,
          ):
              ret = {
                  "text": output["text"],
                  "error_code": 0,
              }
              if "usage" in output:
                  ret["usage"] = output["usage"]
              if "finish_reason" in output:
                  ret["finish_reason"] = output["finish_reason"]
              if "logprobs" in output:
                  ret["logprobs"] = output["logprobs"]
              yield json.dumps(ret).encode() + b"\0"
      except torch.cuda.OutOfMemoryError as e:
          ret = {
              "text": f"{SERVER_ERROR_MSG}\n\n({e})",
              "error_code": ErrorCode.CUDA_OUT_OF_MEMORY,
          }
          yield json.dumps(ret).encode() + b"\0"
      except (ValueError, RuntimeError) as e:
          ret = {
              "text": f"{SERVER_ERROR_MSG}\n\n({e})",
              "error_code": ErrorCode.INTERNAL_ERROR,
          }
          yield json.dumps(ret).encode() + b"\0"
  
imports: import argparse
  import asyncio
  import dataclasses
  import logging
  import json
  import os
  import time
  from typing import List, Optional
  import threading
  import uuid
  from bigdl.llm.utils.common import invalidInputError
  from fastapi import FastAPI, Request, BackgroundTasks
  from fastapi.responses import StreamingResponse, JSONResponse
  import requests
  from .bigdl_llm_model import patch_fastchat
  import torch
  import torch.nn.functional
  import uvicorn
  from fastchat.constants import WORKER_HEART_BEAT_INTERVAL, ErrorCode, SERVER_ERROR_MSG
  from fastchat.conversation import get_conv_template
  from fastchat.model.model_adapter import add_model_args, get_conversation_template, get_generate_stream_function
  from fastchat.modules.gptq import GptqConfig
  from fastchat.modules.awq import AWQConfig
  from fastchat.utils import build_logger, pretty_print_semaphore, get_context_length
label_desc: Use image node_id 2 for calling the ModelWorker obj's underlying member method code with example usage: obj.generate_stream_gate(params) without return types