[Docs] Implementing Custom mean function documentation

Hello, all. While Gaussian Processes are often described as not needing a mean (or only a zero, or constant one), that is not true, and being able to implement custom means would be incredibly useful.

I see in the docs that gpytorch.means.Mean seems to be set aside for this specific purpose, but there exists no explanation (or examples) demonstrating how to use it.

Is there an obvious method of defining simple, custom means that I am not seeing? If not, I think a couple of basic examples would be helpful.

[jacobrgardner]

@dtort For that just use the constant mean, initialize the constant to 5 and then make the constant untrainable by setting requires_grad=False

self.mean_module = ConstantMean()
self.mean_module.initialize(constant=5.)
self.mean_module.constant.requires_grad = False

[Jahnvi99]

Sure, as u suggested I opened a discussion topic with my question!