"'Found more than one basic block without predecessors." with my alea/c# code, and I do not have any idea why?

Question

So I am trying to implement some code with Alea/C#. For the moment, it is basic code. I tried the tutorials and examples available at the Alea site. The examples work just fine, but when I do my own version of codes, namely, using a random walk with a dynamically defined amount of steps for each walk, it does not seem to work.

I set up an double array as follows and initialize it to 0:

 [GpuParam] public static double[] gaussian = {0};

I then use a gpumanaged method:

[GpuManaged]
    private static void Random()
    {
        using (var rng = Generator.CreateGpu(Gpu.Default,RngType.PSEUDO_XORWOW))
        {
            rng.SetPseudoRandomGeneratorSeed(42);

            rng.GenerateUniform(gaussian);
        }
    }

I then use the parallel for function which there is a plethora of examples on the alea website.

    [GpuManaged]
    private static void Test()
    {
        var prices = new double[100];

        Gpu.Default.For(0, 100,
            i =>
            {
                Random();
                prices[i] = gaussian[0];
            });
    }

However, when I run this, I get the error:

System.Exception: 'Found more than one basic block without predecessors.

Source location stack:

-> in C:\Users\tub08918\source\repos\GpuMCOptics\GpuMCOptics\Program.cs(45,21-45,30)
-> at GpuMCOptics.Program+<>c__DisplayClass6_0.[Void <Test>b__0(Int32)]
-> at Alea.Parallel.Device.DeviceFor.[Void Kernel(Int32, Int32, System.Action`1[System.Int32])]
-> at defining runtime64 (sm52,64bit)
Loading method as kernel:
-> Method: Alea.Parallel.Device.DeviceFor.[Void Kernel(Int32, Int32, System.Action`1[System.Int32])]
-> InstanceOpt: <None>
-> Argument.#0: 0
-> Argument.#1: 100
-> Argument.#2: System.Action`1[System.Int32]
Getting or loading method as kernel:
-> Method: Alea.Parallel.Device.DeviceFor.[Void Kernel(Int32, Int32, System.Action`1[System.Int32])]
-> InstanceOpt: <None>
-> Argument.#0: 0
-> Argument.#1: 100
-> Argument.#2: System.Action`1[System.Int32]

Any help on this would be helpful. I am very interested in using these gpu architectures but I have been working on solving this problem all day and I am getting more and more confused as I try different methods such as launching kernels and actions and using shared memory, but none of it works.