I am working on converting a legacy torch(lua based) project to pytorch. The authors of the legacy code have used a vgg16 pretrained model (on caffe framework) for their experiments. I used the torchvision pretrained model. I wanted to pass a 28x28x3 image through said models feature extractor but I am getting different output tensor sizes when passing the image through these. The caffe model returns a 512x2x2 (CHW) tensor whereas torchvision one returns a 512x1x1. I printed the model submodules and they exactly match each other. What should I do?