code: def _log_early_stop_params(early_stop_callback, client, run_id):
      """
      Logs early stopping configuration parameters to MLflow.
  
      :param early_stop_callback: The early stopping callback instance used during training.
      :param client: An `MlflowAutologgingQueueingClient` instance used for MLflow logging.
      :param 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",
                  "mode",
                  "patience",
                  "min_delta",
                  "stopped_epoch",
              ]
              if hasattr(early_stop_callback, p)
          },
      )
  
imports: import logging
  import os
  import tempfile
  import warnings
  from packaging.version import Version
  import mlflow.pytorch
  from mlflow.exceptions import MlflowException
  from mlflow.ml_package_versions import _ML_PACKAGE_VERSIONS
  from mlflow.pytorch import _pytorch_autolog
  from mlflow.utils.autologging_utils import BatchMetricsLogger, ExceptionSafeAbstractClass, MlflowAutologgingQueueingClient, get_autologging_config
  import pytorch_lightning
  from pytorch_lightning.utilities import rank_zero_only
label_desc: Use image node_id 2 for calling a global function with example usage: _log_early_stop_params(early_stop_callback, client, run_id) without return types