Hi everyone 
I have two models that are essentially the same (same architecture, same number of parameters) but they yield different results. The first model is one from the PyTorch model selection (a ResNet18 without pretrained weights) and the other one is essentially copy pasted code a bit reformatted (I want to later try some stuff with the ResNet architecture which is why I had to code it myself).
Somehow they yield different results even if I seed my code to make it reproducible…Does anyone know why that is the case? Is it because altough conceptually they are the same, PyTorch initialises different weights for them because they are different instances?
Any help is very much appreciated!
All the best
snowe
Edit: I just realised that when I instantiate two ResNets from PyTorch they also yield different results, even though they are the same. Is that behaviour to be expected? Is this because of some randomness in the batchnorm or so?