code: def log_metrics(metrics, prefix=""):
      log = ["{0} = {1}".format(m.name, m.result()) for m in metrics]
      logging.info("%s \n\t\t %s", prefix, "\n\t\t ".join(log))
  
file_path: agents/tf_agents/eval/metric_utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from absl import logging
  import gin
  import tensorflow
  from tf_agents.drivers import dynamic_episode_driver
  from tf_agents.drivers import py_driver
  from tf_agents.metrics import py_metric
  from tf_agents.utils import common
label_desc: Use image node_id 1 for calling a global function with example usage: log_metrics(metrics, prefix) without return types