code: def in_db_filtering_evaluate(params: dict, args: Namespace):
      global search_space_ins, _evaluator, sampler
      from src.common.structure import ModelAcquireData
      from src.logger import logger
  
      try:
          if (
              search_space_ins is None
              and _evaluator is None
              and sampler is None
          ):
              logger.info(
                  "search_space_ins, _evaluator, sampler is None"
              )
              return orjson.dumps(
                  {"error": "erroed, plz call init first"}
              ).decode("utf-8")
  
          sampled_result = json.loads(params["sample_result"])
          arch_id, model_encoding = str(sampled_result["arch_id"]), str(
              sampled_result["model_encoding"]
          )
  
          mini_batch = json.loads(params["mini_batch"])
          if mini_batch["status"] == "error":
              return orjson.dumps(
                  {"error": mini_batch["message"]}
              ).decode("utf-8")
          logger.info(
              f"Begin evaluate {params['model_index']}, "
              f"with size of batch = {len(mini_batch['data'])}, "
              f"size of columns = {len(mini_batch['data'][0])}"
          )
          model_acquire_data = ModelAcquireData(
              model_id=arch_id,
              model_encoding=model_encoding,
              is_last=False,
              spi_seconds=float(params["spi_seconds"]),
              spi_mini_batch=mini_batch["data"],
          )
  
          model_score = _evaluator._p1_evaluate_online(
              model_acquire_data
          )
          logger.info(
              f'Done evaluate {params["model_index"]}, '
              f'with {orjson.dumps({"index": params["model_index"], "score": model_score}).decode("utf-8")}'
          )
      except:
          logger.info(
              orjson.dumps({"Errored": traceback.format_exc()}).decode(
                  "utf-8"
              )
          )
  
          return orjson.dumps(
              {"Errored": traceback.format_exc()}
          ).decode("utf-8")
  
      return orjson.dumps(
          {"index": params["model_index"], "score": model_score}
      ).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 16 for calling a global function with example usage: in_db_filtering_evaluate(params, args) and returns: orjson, orjson, orjson, orjson