Hi, I’m using pytorch’s pretrained resnet50 model, and i came across some problems with the output.
Assume I train for 10 epches and the best validation epoch 5, so i saved epoch 5’s model, and re-run the saved epoch 5’s model on the validation, i found this prediction is different with the prediction in the training process(of course also using the epoch 5).
After some investigation,  it seems the problems comes from a layer(backbone.layer1) which contains a bn, before this layer, the input is the same, after this layer, small errors start appearing and then the error is propagated to the later layers until the output.
during both evaluation phase(one is in training, and one is after training), i set model.eval(), so I’m confused why there is still difference?