Hi, I run the code on vgg16 and resnet56/CIFAR10, but failed to reproduce the result in your paper, I use the provided baseline checkpoints, and failed to achieve your paper result.
For vgg16, I run 10 times , but none of the results of your paper were reproduced. The best I got was 92.73 after pruning and retraining 30 epochs, while in your paper the result is 93.12.
For resnet56, I also failed to reproduce the result in your paper. I get 92.39 on method-D after 100 epochs training, but your paper result is 94.00. Meanwhile, I get 91.58 on method-P after pruning and retraining 30 epochs, but your paper result is 93.38. I set all the parameters as in your paper.
For resnet18, I didn’t run your code. The error is caused by dimension mismatch of residual layer. I tried to modify the residual in shrink_resnet code and replace down_SAMPLE with short_cut in the code, but still failed.
I sincerely hope you can give me some help!
Thank you very much!
Hi, I run the code on vgg16 and resnet56/CIFAR10, but failed to reproduce the result in your paper, I use the provided baseline checkpoints, and failed to achieve your paper result.
For vgg16, I run 10 times , but none of the results of your paper were reproduced. The best I got was 92.73 after pruning and retraining 30 epochs, while in your paper the result is 93.12.
For resnet56, I also failed to reproduce the result in your paper. I get 92.39 on method-D after 100 epochs training, but your paper result is 94.00. Meanwhile, I get 91.58 on method-P after pruning and retraining 30 epochs, but your paper result is 93.38. I set all the parameters as in your paper.
For resnet18, I didn’t run your code. The error is caused by dimension mismatch of residual layer. I tried to modify the residual in shrink_resnet code and replace down_SAMPLE with short_cut in the code, but still failed.
I sincerely hope you can give me some help!
Thank you very much!