code: def metric_type_trans(metric_type):
      if metric_type in METRIC_MAP.keys():
          return METRIC_MAP[metric_type]
      else:
          raise Exception(
              "metric_type: %s not in METRIC_MAP" % metric_type
          )
  
imports: import os
  import logging
  import numpy
  import sklearn.preprocessing
  import h5py
  import random
  from itertools import product
  from pymilvus import DataType
  from milvus_benchmark import config
label_desc: Use image node_id 6 for calling a global function with example usage: metric_type_trans(metric_type) and returns: METRIC_MAP