code: def train_end(self, estimator, *args, **kwargs):
      if (
          isinstance(estimator.net, HybridSequential)
          and self.log_models
      ):
          registered_model_name = get_autologging_config(
              mlflow.gluon.FLAVOR_NAME, "registered_model_name", None
          )
          mlflow.gluon.log_model(
              estimator.net,
              artifact_path="model",
              registered_model_name=registered_model_name,
          )
  
file_path: mlflow/mlflow/gluon/_autolog.py
imports: from mxnet.gluon.contrib.estimator import EpochEnd, TrainBegin, TrainEnd
  from mxnet.gluon.nn import HybridSequential
  import mlflow
  from mlflow.utils.autologging_utils import ExceptionSafeClass, get_autologging_config
label_desc: Use image node_id 4 for calling the __MLflowGluonCallback obj's underlying member method code with example usage: obj.train_end(estimator) without return types