code: def filtering_phase(params: dict, args: Namespace):
      from src.logger import logger
  
      logger.info(f"begin run filtering_phase CPU only")
  
      # mini_batch_m = params["mini_batch"]
      n = int(params["n"])
      k = int(params["k"])
  
      from src.eva_engine.run_ms import RunModelSelection
  
      # mini_batch_data = json.loads(mini_batch_m)
      # dataloader = generate_dataloader(mini_batch_data=mini_batch_data, args=args)
  
      rms = RunModelSelection(
          args.search_space, args, is_simulate=args.is_simulate
      )
      k_models, _, _, _ = rms.filtering_phase(N=n, K=k)
  
      return orjson.dumps({"k_models": k_models}).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 7 for calling a global function with example usage: filtering_phase(params, args) and returns: orjson