code: def profiling_filtering_phase(params: dict, args: Namespace):
      from src.logger import logger
  
      logger.info(f"begin run profiling_filtering_phase CPU only")
  
      mini_batch_m = params["mini_batch"]
  
      from src.eva_engine.run_ms import RunModelSelection
  
      logger.info(
          f"begin run filtering phase at {os.getcwd()}, with {mini_batch_m}"
      )
  
      mini_batch_data = json.loads(mini_batch_m)
      dataloader = generate_dataloader(
          mini_batch_data=mini_batch_data, args=args
      )
      data_loader = [dataloader, dataloader, dataloader]
  
      rms = RunModelSelection(
          args.search_space, args, is_simulate=args.is_simulate
      )
      score_time_per_model = rms.profile_filtering(
          data_loader=data_loader
      )
  
      return orjson.dumps({"time": score_time_per_model}).decode(
          "utf-8"
      )
  
imports: import calendar
  import os
  import time
  import requests
  import json
  from typing import List, Dict
  import traceback
  import orjson
  from argparse import Namespace
  from shared_config import parse_config_arguments
  from torch.utils.data import Dataset
  import torch
label_desc: Use image node_id 4 for calling a global function with example usage: profiling_filtering_phase(params, args) and returns: orjson