mlflow/mlflow · error · MlflowException

RESOURCE_DOES_NOT_EXIST

RESOURCE_DOES_NOT_EXIST

Error message

Registered Model with name={name!r} not found.

What it means

Error "Registered Model with name={name!r} not found." thrown in mlflow/mlflow.

Source

Thrown at mlflow/tracking/client.py:181

_logger = logging.getLogger(__name__)

_STAGES_DEPRECATION_WARNING = (
    "Model registry stages will be removed in a future major release. To learn more about the "
    "deprecation of model registry stages, see our migration guide here: https://mlflow.org/docs/"
    "latest/model-registry.html#migrating-from-stages"
)


def _model_not_found(name: str) -> MlflowException:
    return MlflowException(
        f"Registered Model with name={name!r} not found.",
        RESOURCE_DOES_NOT_EXIST,
    )


def _validate_model_id_specified(model_id: str) -> None:
    if not model_id:
        raise MlflowException(
            f"`model_id` must be a non-empty string, but got {model_id!r}",
            INVALID_PARAMETER_VALUE,
        )


def _disable_in_databricks(use_uc_message=False):
    """Decorator to disable dataset operations when tracking URI is Databricks.

    Args:
        use_uc_message: If True, suggests Unity Catalog instead of fluent API.
    """

    def decorator(func):
        @functools.wraps(func)
        def wrapper(self, *args, **kwargs):
            if not is_databricks_uri(str(self.tracking_uri)):
                return func(self, *args, **kwargs)

View on GitHub (pinned to 6a27f2decc)

When it happens

Trigger: Thrown at mlflow/tracking/client.py:181 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of mlflow/mlflow@6a27f2decc (2026-08-29). Data as JSON: /api/errors/79d209d3b5edb94e. Report an issue: GitHub.