class_docstr: MLflow entity for Registered Model.
class_docstr_tok: ["MLflow","entity","for","Registered","Model","."]
code: def __init__(
      self,
      name,
      creation_timestamp=None,
      last_updated_timestamp=None,
      description=None,
      latest_versions=None,
      tags=None,
      aliases=None,
  ):
      # Constructor is called only from within the system by various backend stores.
      super().__init__()
      self._name = name
      self._creation_time = creation_timestamp
      self._last_updated_timestamp = last_updated_timestamp
      self._description = description
      self._latest_version = latest_versions
      self._tags = {tag.key: tag.value for tag in (tags or [])}
      self._aliases = {
          alias.alias: alias.version for alias in (aliases or [])
      }
  
imports: from mlflow.entities.model_registry._model_registry_entity import _ModelRegistryEntity
  from mlflow.entities.model_registry.model_version import ModelVersion
  from mlflow.entities.model_registry.registered_model_alias import RegisteredModelAlias
  from mlflow.entities.model_registry.registered_model_tag import RegisteredModelTag
  from mlflow.protos.model_registry_pb2 import RegisteredModel
  from mlflow.protos.model_registry_pb2 import RegisteredModelAlias
  from mlflow.protos.model_registry_pb2 import RegisteredModelTag
label_desc: Use image node_id 1 to create a new RegisteredModel object from inherited base classes: _ModelRegistryEntity with example: obj = RegisteredModel(name, creation_timestamp, last_updated_timestamp, description, latest_versions, tags, aliases)