├── README.md ├── evaluate.py ├── imgs ├── figure1.png ├── figure2.png └── figure3.png ├── loss.py ├── main.py ├── network.py ├── optimizer.py ├── parameter.py ├── prune.py ├── prune_filter_for_efficient_convnets.ipynb ├── train.py └── utils.py /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/README.md -------------------------------------------------------------------------------- /evaluate.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/evaluate.py -------------------------------------------------------------------------------- /imgs/figure1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/imgs/figure1.png -------------------------------------------------------------------------------- /imgs/figure2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/imgs/figure2.png -------------------------------------------------------------------------------- /imgs/figure3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/imgs/figure3.png -------------------------------------------------------------------------------- /loss.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/loss.py -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/main.py -------------------------------------------------------------------------------- /network.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/network.py -------------------------------------------------------------------------------- /optimizer.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/optimizer.py -------------------------------------------------------------------------------- /parameter.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/parameter.py -------------------------------------------------------------------------------- /prune.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/prune.py -------------------------------------------------------------------------------- /prune_filter_for_efficient_convnets.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/prune_filter_for_efficient_convnets.ipynb -------------------------------------------------------------------------------- /train.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/train.py -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tyui592/Pruning_filters_for_efficient_convnets/HEAD/utils.py --------------------------------------------------------------------------------