code: def _collect_run_params(run_info, run_params):
      """Log the parameter information for the benchmark run."""
  
      def process_param(name, value):
          type_check = {
              str: {"name": name, "string_value": value},
              int: {"name": name, "long_value": value},
              bool: {"name": name, "bool_value": str(value)},
              float: {"name": name, "float_value": value},
          }
          return type_check.get(
              type(value), {"name": name, "string_value": str(value)}
          )
  
      if run_params:
          run_info["run_parameters"] = [
              process_param(k, v) for k, v in sorted(run_params.items())
          ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import contextlib
  import datetime
  import json
  import multiprocessing
  import numbers
  import os
  import threading
  import uuid
  from six.moves import _thread
  from absl import flags
  import tensorflow
  from tensorflow.python.client import device_lib
  from utils.logs import cloud_lib
label_desc: Use image node_id 7 for calling a global function with example usage: _collect_run_params(run_info, run_params) and returns: type_check