For now use this pattern torch.cuda.*Tensor(*shape).inplace_sampling_method_here_(). Here are the available inplace sampling methods: http://pytorch.org/docs/master/torch.html#in-place-random-sampling 10. Notice that these are the basic building block distributions. You can use the results to generate samples of more complex distributions, e.g. multivariate Gaussian.
In the next version we will have dtype in tensor factory methods, so you can just do things like torch.randn(3, 4, dtype=torch.cuda.double).