Hi familiy.
I am following the tutorial from oficial pytorch website, where teaches how to fine tunning with mask-rcnn
https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html 2
I have a question in the Main function (which is little down below).
You will see this code

params = [p for p in model.parameters() if p.requires_grad]


As far i know, when we need do fine tuning classification models (like VG 16), we freeze every layer except the last one. Why here we use this code?
I have already readed the official paper of the faster-rcnn where it described until 3 different ways to train this architecture
Please i will appreciate any explication 
PDT: this is my first project with this kind of architecture