code: def autolog_callback(env, metrics_logger, eval_results):
      metric_dict = _patch_metric_names(
          dict(env.evaluation_result_list)
      )
      metrics_logger.record_metrics(metric_dict, env.iteration)
      eval_results.append(metric_dict)
  
imports: import logging
  import xgboost
  from packaging.version import Version
  from mlflow.utils.autologging_utils import ExceptionSafeAbstractClass
label_desc: Use image node_id 2 for calling a global function with example usage: autolog_callback(env, metrics_logger, eval_results) without return types