log_model¶

def log_model(
    forecaster: Any,
    name: str | None = None,
    *,
    registered_model_name: str | None = None,
    await_registration_for: int = 300,
    extra_trusted_types: Iterable[str] | None = None,
    extra_trusted_prefixes: Iterable[str] | None = None,
    extra_version_rules: Mapping[str, str] | None = None,
    signature: ModelSignature | None = None,
    conda_env: Any = None,
    pip_requirements: Any = None,
    extra_pip_requirements: Any = None,
    metadata: dict[str, Any] | None = None,
    **kwargs: Any,
) -> ModelInfo:
    """Log a fitted yohou forecaster as an MLflow model, optionally registering it.

    Parameters
    ----------
    forecaster : yohou forecaster
        A fitted yohou forecaster.
    name : str or None, default=None
        Name of the logged model, as for MLflow's built-in flavours.
    registered_model_name : str or None, default=None
        When given, also create a version of this registered model.
    await_registration_for : int, default=300
        Seconds to wait for the model version to become ready.
    extra_trusted_types : iterable of str or None, default=None
        See `save_model`.
    extra_trusted_prefixes : iterable of str or None, default=None
        See `save_model`.
    extra_version_rules : mapping of str to str or None, default=None
        See `save_model`.
    signature : mlflow.models.ModelSignature or None, default=None
        See `save_model`.
    conda_env : dict, str or None, default=None
        See `save_model`.
    pip_requirements : iterable of str, str or None, default=None
        See `save_model`.
    extra_pip_requirements : iterable of str, str or None, default=None
        See `save_model`.
    metadata : dict or None, default=None
        Custom metadata stored in the ``MLmodel`` file.
    **kwargs : Any
        Passed to ``mlflow.models.Model.log``.

    Returns
    -------
    mlflow.models.model.ModelInfo
        Metadata of the logged model, including its ``model_uri``.

    See Also
    --------
    save_model : The checks every logged model goes through.
    load_model : Load a logged or registered forecaster.
    """
    import yohou_mlflow

    return Model.log(
        artifact_path=None,
        name=name,
        flavor=yohou_mlflow,
        registered_model_name=registered_model_name,
        await_registration_for=await_registration_for,
        metadata=metadata,
        forecaster=forecaster,
        extra_trusted_types=extra_trusted_types,
        extra_trusted_prefixes=extra_trusted_prefixes,
        extra_version_rules=extra_version_rules,
        signature=signature,
        conda_env=conda_env,
        pip_requirements=pip_requirements,
        extra_pip_requirements=extra_pip_requirements,
        **kwargs,
    )