Hi,
I have a bit of misunderstanding regarding the difference between the Normal distribution and the MultiVariateNormal distribution in pytorch. As I understand it, Normal distribution are univariate and so loc and scale should be floats. However, it is possible to define Normal distribution with vector mean and vector covariance which is in this case a multivariate gaussian right ? So in pytorch the following works for instance:
batch_size = 512
dim = 4
mean = torch.rand((batch_size,dim))
log_var = torch.rand(((batch_size,dim))
d = Normal(mean,torch.exp(0.5*log_var))

But in this case I define a multivariate normal using the univariate Normal distribution from pytorch right  ? How does pytorch interpret this ?
Please help me clear this misunderstanding