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Code for the paper: "BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems"
My name is Mingjie Wang and I am a Researcher at UIC University. I have read your excellent work 'BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems ' and want to figure out the details of the network and how it works.
Could you share pre-train code of resnet and vgg with me?
Traceback (most recent call last):
File "/WdHeDisk/users/wangyd/wangyd/24BottleNet/BottleNet++_VGG16.py", line 96, in
model = BottleNetPlusPlus_VGG().to(device)
File "/WdHeDisk/users/wangyd/wangyd/24BottleNet/BottleNet++_VGG16.py", line 59, in init
self.vgg_model = torch.load('vgg16_74.02.pth')
File "/mnt/miniconda3/envs/wangyd/lib/python3.6/site-packages/torch/serialization.py", line 595, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File "/mnt/miniconda3/envs/wangyd/lib/python3.6/site-packages/torch/serialization.py", line 774, in _legacy_load
result = unpickler.load()
ModuleNotFoundError: No module named 'vgg'
Could you provide the training code?
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