How to create a normal distribution in pytorch

Question

I want to create a random normal distribution in pytorch and mean and std are 4, 0.5 respectively. I didn\'t find a API for it. Anyone knows? Thanks very much.

Answer 1

For a standard normal distribution (i.e. mean=0 and variance=1), you can use torch.randn()

For your case of custom mean and std, you can use torch.distributions.Normal()

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Init signature:
tdist.Normal(loc, scale, validate_args=None)

Docstring:
Creates a normal (also called Gaussian) distribution parameterized by loc and scale.

Args:
loc (float or Tensor): mean of the distribution (often referred to as mu)
scale (float or Tensor): standard deviation of the distribution (often referred to as sigma)

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Here's an example:

In [32]: import torch.distributions as tdist

In [33]: n = tdist.Normal(torch.tensor([4.0]), torch.tensor([0.5]))

In [34]: n.sample((2,))
Out[34]: 
tensor([[ 3.6577],
        [ 4.7001]])