code: def _log_early_stop_metrics(early_stop_callback, client, run_id):
      """
      Logs early stopping behavior results (e.g. stopped epoch) as metrics to MLflow.
  
      Args:
          early_stop_callback: The early stopping callback instance used during training.
          client: An `MlflowAutologgingQueueingClient` instance used for MLflow logging.
          run_id: The ID of the MLflow Run to which to log configuration parameters.
      """
      if early_stop_callback.stopped_epoch == 0:
          return
  
      metrics = {
          "stopped_epoch": early_stop_callback.stopped_epoch,
          "best_value": early_stop_callback.best_value,
      }
      client.log_metrics(run_id, metrics)
  
file_path: mlflow/mlflow/paddle/_paddle_autolog.py
imports: import paddle
  import mlflow
  from mlflow.utils.autologging_utils import BatchMetricsLogger, ExceptionSafeAbstractClass, MlflowAutologgingQueueingClient, get_autologging_config
label_desc: Use image node_id 2 for calling a global function with example usage: _log_early_stop_metrics(early_stop_callback, client, run_id) without return types