I’m using a resnet18 network from torchvision.models.
During test time, I observe If I alter the batch size for the data loader, the accuracy of the model on test data changes. I can not comprehend why should this happen. Isn’t the case that the weights of the network are fixed during testing(I haven’t called any optimizer.step())? I also went through resnet’s architecture, there is no randomized output at any layer.
Any pointers where I could be wrong in my code or my information?