the different feature size in the training and tracking process

In your tracking process, the output feature size is 125 *125*32 before the DCF layer.
However, in your training code, the networkType is set to 12, and the output size after two convolutional laysers is smaller than the input image size by 4. (feature_za=input_size-[4,4])
I wonder why the saved netork (.mat file) after training can generate different feature size?
Look for your early reply! And thank you very much.