I love this! I was trying to load in a model written in Torch 0.4 from Torch 1.1 and was having issues. There were more layers in newer version -> so I printed the order dictionary of each model from both version and saw that the same Python nn.Module subclass (I am using pretrained Yolo from this repo:https://github.com/vietnguyen91/Yolo-v2-pytorch 15 ) has 133 layers in Torch 1.1 vs 111 in Torch .4. It was adding a bunch of “num_batches_tracked” layers.
In short, using the strict=False lets you run the saved parameters from Torch .4 to Torch 1.1 using the same Python class for the Yolo network. Hope this helps someone out there.