Trigger computation, keeping data as dask arrays

        This operation can be used to trigger computation on underlying dask
        arrays, similar to ``.compute()``.  However this operation keeps the
        data as dask arrays.  This is particularly useful when using the
        dask.distributed scheduler and you want to load a large amount of data
        into distributed memory.

        Parameters
        ----------
        **kwargs : dict
            Additional keyword arguments passed on to ``dask.persist``.

        See Also
        --------
        dask.persist

def persist(self: T, **kwargs) -> T:
        """ Trigger computation, keeping data as dask arrays

        This operation can be used to trigger computation on underlying dask
        arrays, similar to ``.compute()``.  However this operation keeps the
        data as dask arrays.  This is particularly useful when using the
        dask.distributed scheduler and you want to load a large amount of data
        into distributed memory.

        Parameters
        ----------
        **kwargs : dict
            Additional keyword arguments passed on to ``dask.persist``.

        See Also
        --------
        dask.persist
        """
        new = self.copy(deep=False)
        return new._persist_inplace(**kwargs)