class_docstr: Callback for auto-logging metrics and parameters.
code: def on_train_end(self, logs=None):  # pylint: disable=unused-argument
      self.metrics_logger.flush()
      self.client.flush(synchronous=True)
  
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 5 for calling the __MLflowPaddleCallback obj's underlying member method code with example usage: obj.on_train_end(logs) without return types