Normally distributed vector given mean, stddev|variance

Question

how to do this in torch

 np.random.normal(loc=mean,scale=stdev,size=vsize)

i.e. by providing mean, stddev or variance

Answer 1

There's a similar torch function torch.normal:

torch.normal(mean=mean, std=std)

If mean and std are scalars, this will produce a scalar value. You can simply repeat them for the target you want it to be, eg:

mean = 2
std = 10
size = (3,3)
r = torch.normal(mean=torch.full(size,mean).float(),std=torch.full(size,mean).float())
print(r)

> tensor([[ 2.2263,  1.1374,  4.5766],
    [ 3.4727,  2.6712,  2.4878],
    [-0.1787,  2.9600,  2.7598]])