def METHOD_NAME(kernel_embedding):
    """Test kernel variance for the Lebesgue measure against Gauss-Legendre tensor
    product rule."""
    n_gl = 20
    x_gl, w_gl = gauss_legendre_tensor(
        n_points=n_gl,
        input_dim=kernel_embedding.input_dim,
        domain=kernel_embedding.measure.domain,
        normalized=kernel_embedding.measure.normalized,
    )
    num_kernel_variance = kernel_embedding.kernel_mean(x_gl) @ w_gl
    true_kernel_variance = kernel_embedding.kernel_variance()
    np.testing.assert_allclose(
        true_kernel_variance, num_kernel_variance, rtol=1.0e-3, atol=1.0e-3
    )