def METHOD_NAME(dtype):
    q = get_queue_or_skip()
    skip_if_dtype_not_supported(dtype, q)
    np.random.seed(42)
    strides = np.array([-4, -3, -2, -1, 1, 2, 3, 4])
    sizes = [2, 4, 6, 8, 9, 24, 72]
    tol = 8 * dpt.finfo(dtype).resolution
    for ii in sizes:
        Xnp = np.random.uniform(low=0.01, high=88.1, size=ii)
        Xnp.astype(dtype)
        X = dpt.asarray(Xnp)
        Ynp = np.exp(Xnp)
        for jj in strides:
            assert_allclose(
                dpt.asnumpy(dpt.exp(X[::jj])),
                Ynp[::jj],
                atol=tol,
                rtol=tol,
            )