hu @ptrblck 
I wasn’t sure if this was the right place to ask or ask a new question but the title seemed directly relevant to what I want (maybe not the details of his question), didn’t want to ask something where a title for what I want already exists.
I also want to modify a pre-trained nets but I just want to change the hyperparms of my net to my different data set (I do not want to transfer or pretrain my net).
e.g. I did this:
def modify_resnet_for_fsl(model, fc_out_features=5):
    for name, module in model.named_modules():
        if type(module) == torch.nn.BatchNorm2d:
            module.track_running_stats = False
    model.fc.out_features = fc_out_features

but when I run a sample image, the output is still 1000 labels except my 5 I put for debugging/unit testing.
model(x).size()
Out[19]: torch.Size([25, 1000]

any advice? is modifying the modules objects (How to get the module names of nn.Sequential 5) directly not the right thing to do?