def METHOD_NAME(
    combination_type: CombinationKernel, kernel: AbstractKernel, n_kerns: int
) -> None:
    # Create inputs
    n = 20
    x = jnp.linspace(0.0, 1.0, num=n).reshape(-1, 1)
    # Create list of kernels
    kernels = [kernel() for _ in range(n_kerns)]
    # Create combination kernel
    combination_kernel = combination_type(kernels=kernels)
    # Check params are a list of dictionaries
    assert combination_kernel.kernels == kernels
    # Check combination kernel set
    assert len(combination_kernel.kernels) == n_kerns
    assert isinstance(combination_kernel.kernels, list)
    assert isinstance(combination_kernel.kernels[0], AbstractKernel)
    # Compute gram matrix
    Kxx = combination_kernel.gram(x)
    # Check shapes
    assert Kxx.shape[0] == Kxx.shape[1]
    assert Kxx.shape[1] == n
    # Check positive definiteness
    jitter = 1e-6
    eigen_values = jnp.linalg.eigvalsh(Kxx.to_dense() + jnp.eye(n) * jitter)
    assert (eigen_values > 0).all()