class_docstr: Client of an MLflow Model Registry Server that creates and manages registered
  models and model versions.
docstr: Update model version stage.
  
  :param name: Registered model name.
  :param version: Registered model version.
  :param stage: New desired stage for this model version.
  :param archive_existing_versions: If this flag is set to ``True``, all existing model
      versions in the stage will be automatically moved to the "archived" stage. Only valid
      when ``stage`` is ``"staging"`` or ``"production"`` otherwise an error will be raised.
  
  :return: A single :py:class:`mlflow.entities.model_registry.ModelVersion` object.
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code: def transition_model_version_stage(
      self, name, version, stage, archive_existing_versions=False
  ):
      """
      Update model version stage.
  
      :param name: Registered model name.
      :param version: Registered model version.
      :param stage: New desired stage for this model version.
      :param archive_existing_versions: If this flag is set to ``True``, all existing model
          versions in the stage will be automatically moved to the "archived" stage. Only valid
          when ``stage`` is ``"staging"`` or ``"production"`` otherwise an error will be raised.
  
      :return: A single :py:class:`mlflow.entities.model_registry.ModelVersion` object.
      """
      if stage.strip() == "":
          raise MlflowException(
              "The stage must not be an empty string."
          )
      return self.store.transition_model_version_stage(
          name=name,
          version=version,
          stage=stage,
          archive_existing_versions=archive_existing_versions,
      )
  
imports: import logging
  from mlflow.entities.model_registry import ModelVersionTag, RegisteredModelTag
  from mlflow.exceptions import MlflowException
  from mlflow.store.model_registry import SEARCH_MODEL_VERSION_MAX_RESULTS_DEFAULT, SEARCH_REGISTERED_MODEL_MAX_RESULTS_DEFAULT
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS, utils
  from mlflow.utils.arguments_utils import _get_arg_names
label_desc: Use image node_id 15 for calling the ModelRegistryClient obj's underlying member method code with example usage: obj.transition_model_version_stage(name, version, stage, archive_existing_versions) and returns: self