code: def test_gpt_fast_mar(model_name_and_stdout):
      model_name, _ = model_name_and_stdout
  
      response = requests.post(
          url=f"http://localhost:8080/predictions/{model_name}",
          data=json.dumps(
              PROMPTS[0],
          ),
          stream=True,
      )
  
      assert response.status_code == 200
  
      assert response.headers["Transfer-Encoding"] == "chunked"
  
      prediction = []
      for chunk in response.iter_content(chunk_size=None):
          if chunk:
              prediction += [chunk.decode("utf-8")]
  
      assert len(prediction) > 1
  
      assert "".join(prediction) == EXPECTED_RESULTS[0]
  
imports: import json
  import shutil
  import sys
  from pathlib import Path
  from string import Template
  from unittest.mock import patch
  import pytest
  import requests
  import test_utils
  import torch
  import yaml
  from model_archiver.model_archiver_config import ModelArchiverConfig
  from ts.torch_handler.unit_tests.test_utils.mock_context import MockContext
label_desc: Use image node_id 8 for calling a global function with example usage: test_gpt_fast_mar(model_name_and_stdout) without return types