code: def _log_early_stop_params(early_stop_callback, client, run_id):
      """
      Logs early stopping configuration parameters 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.
      """
      client.log_params(
          run_id,
          {
              p: getattr(early_stop_callback, p)
              for p in ["monitor", "patience", "min_delta", "baseline"]
              if hasattr(early_stop_callback, p)
          },
      )
  
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 1 for calling a global function with example usage: _log_early_stop_params(early_stop_callback, client, run_id) without return types