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View Code? Open in Web Editor NEWPyTorch code for training neural networks without global back-propagation
PyTorch code for training neural networks without global back-propagation
Hello! Thanks for making this code available. I wanted to ask what your experiences / results have been running this algorithm on ImageNet, and how this code may be used to do so (when I try setting ImageNet as the dataset, my GPU runs out of memory -- I can imagine various ways to address this, but I wanted to see if you have encountered a similar issue and if so, how you've addressed it). Thank you!
Hi, Arild,
Thanks for the wonderful work. I am quite interested in this work. I am trying to run the models, like resnet50 and resnet100 which you do not show specific guide in the paper. The terminal command I use is like this: python train.py --model resnet101 --dataset CIFAR10 --dropout 0.3 --lr 3e-4 --nonlin leakyrelu. But I got the following error:
TypeError: set_learning_rate() missing 3 required positional arguments: 'lr', 'weight_decay', and 'momentum'
Really appreciate your help!
hello, could you provide your environment
such as the pytorch version and the python version
thanks
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