def fetch_data_with_moabb(
    dataset_name: str,
    subject_ids: list[int] | int | None = None,
    dataset_kwargs: dict[str, Any] | None = None,
    dataset_load_kwargs: dict[str, Any] | None = None,
) -> tuple[list[mne.io.Raw], pd.DataFrame]:
    # ToDo: update path to where moabb downloads / looks for the data
    """Fetch data using moabb.

    Parameters
    ----------
    dataset_name: str | moabb.datasets.base.BaseDataset
        the name of a dataset included in moabb
    subject_ids: list(int) | int
        (list of) int of subject(s) to be fetched
    dataset_kwargs: dict, optional
        optional dictionary containing keyword arguments
        to pass to the moabb dataset when instantiating it.
    data_load_kwargs: dict, optional
        optional dictionary containing keyword arguments
        to pass to the moabb dataset's load_data method.
        Allows using the moabb cache_config=None and
        process_pipeline=None.

    Returns
    -------
    raws: mne.Raw
    info: pandas.DataFrame
    """
    if isinstance(dataset_name, str):
        dataset = _find_dataset_in_moabb(dataset_name, dataset_kwargs)
    else:
        from moabb.datasets.base import BaseDataset

        if isinstance(dataset_name, BaseDataset):
            dataset = dataset_name

    subject_id = [subject_ids] if isinstance(subject_ids, int) else subject_ids
    return _fetch_and_unpack_moabb_data(
        dataset, subject_id, dataset_load_kwargs=dataset_load_kwargs
    )
Fetch data using moabb.

    Parameters
    ----------
    dataset_name: str | moabb.datasets.base.BaseDataset
        the name of a dataset included in moabb
    subject_ids: list(int) | int
        (list of) int of subject(s) to be fetched
    dataset_kwargs: dict, optional
        optional dictionary containing keyword arguments
        to pass to the moabb dataset when instantiating it.
    data_load_kwargs: dict, optional
        optional dictionary containing keyword arguments
        to pass to the moabb dataset's load_data method.
        Allows using the moabb cache_config=None and
        process_pipeline=None.

    Returns
    -------
    raws: mne.Raw
    info: pandas.DataFrame
    
braindecode/datasets/moabb.py