def METHOD_NAME(c1, c2):
    if not type_can_asarray(c1):
        msg = 'The argument "c1" must be array-like'
        raise errors.TypingError(msg)
    if not type_can_asarray(c2):
        msg = 'The argument "c2" must be array-like'
        raise errors.TypingError(msg)
    if np.ndim(c1) > 1 or np.ndim(c2) > 1:
        msg = 'Coefficient array is not 1-d'
        raise errors.NumbaValueError(msg)
    result_dtype = _poly_result_dtype((c1, c2))
    def impl(c1, c2):
        c1 = np.asarray(c1)
        c2 = np.asarray(c2)
        arr1 = np.atleast_1d(c1)
        arr2 = np.atleast_1d(c2)
        val = np.convolve(arr1, arr2).astype(result_dtype)
        return pu.trimseq(val)
    return imp