How do I add some Gaussian noise to a tensor in PyTorch?
I have a tensor I created using

    temp = torch.zeros(5, 10, 20, dtype=torch.float64)
    ## some values I set in temp


Now I want to add to each temp[i,j,k] a Gaussian noise (sampled from normal distribution with mean 0 and variance 0.1). How do I do it? I would expect there is a function to noise a tensor, but couldn't find anything. I did find this:

How to add Poisson noise and Gaussian noise?

but it seems to be related to images.

The function torch.randn produces a tensor with elements drawn from a Gaussian distribution of zero mean and unit variance. Multiply by sqrt(0.1) to have the desired variance.

x = torch.zeros(5, 10, 20, dtype=torch.float64)
x = x + (0.1**0.5)*torch.randn(5, 10, 20)

