Add input validation to LazyTensor constructors and methods

[Balandat]

Currently, incompatibilities in shape, device or dtype between LazyTensors can be very hard to debug, since they manifest at evaluation time deep inside the code, multiple levels deep.

Let's add validation of these to all the LazyTensor constructors and/or methods. For instance, in the MatmulLazyTensor constructor we'd validate that both args have the same device and dtype, and that their shapes are compatible for matrix multiplication: https://github.com/cornellius-gp/gpytorch/blob/master/gpytorch/lazy/matmul_lazy_tensor.py#L20 Similarly, we'd check this compatibility in the _matmul method here: https://github.com/cornellius-gp/gpytorch/blob/master/gpytorch/lazy/matmul_lazy_tensor.py#L42

[eytan]

There are many other places for validation too, including active_dims for the RBFKernel().