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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.
749
AddGaussianNoise adds gaussian noise using the specified mean and std to the input tensor in the preprocessing of the data. torch. randn creates a tensor filled with random numbers from the standard normal distribution (zero mean, unit variance) as described in the docs. In AddGaussianNoise.
White Gaussian Noise can be generated using randn function in Matlab which generates random numbers that follow a Gaussian distribution. Similarly, rand function can be used to generate Uniform White Noise in Matlab that follows a uniform distribution.
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)
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