def argpartition(
        self,
        kth: int | Sequence[int],
        axis: Any = -1,
        kind: SelectKind = "introselect",
        order: OrderType | None = None,
    ) -> ndarray:
        """a.argpartition(kth, axis=-1, kind='introselect', order=None)

        Returns the indices that would partition this array.

        Refer to :func:`cupynumeric.argpartition` for full documentation.

        See Also
        --------
        cupynumeric.argpartition : equivalent function

        Availability
        --------
        Multiple GPUs, Multiple CPUs

        """
        result = ndarray(self.shape, np.int64)
        result._thunk.partition(
            rhs=self._thunk,
            argpartition=True,
            kth=kth,
            axis=axis,
            kind=kind,
            order=order,
        )
        return result
a.argpartition(kth, axis=-1, kind='introselect', order=None)

        Returns the indices that would partition this array.

        Refer to :func:`cupynumeric.argpartition` for full documentation.

        See Also
        --------
        cupynumeric.argpartition : equivalent function

        Availability
        --------
        Multiple GPUs, Multiple CPUs

        
cupynumeric/_array/array.py