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📖 Documentation

Refrence

https://github.com/VainF/Torch-Pruning

How to Run this project

Install the requirements:

pip3 install -r requirements.txt

FOR CIFAR DATASET

To Run a baseline model for channel==3

RGB

!python3 main_train.py --model 'ResNet50' --num_channel 3 --model_path 'l1_norm/model/ResNet50/RGB' --cuda --gpuids 0 1 --epochs 150 --data cifar10 --batch_size 128
!python3 main_train.py --model 'VGG16' --num_channel 3 --model_path 'l1_norm/model/VGG16/RGB' --cuda --gpuids 0 1 --epochs 150 --data cifar10 --batch_size 128

GREY

! python3 main_train.py --model 'ResNet50' --num_channel 1 --model_path 'l1_norm/model/ResNet50/grey' --cuda --gpuids 0 1 --epochs 150 --data cifar10 --batch_size 128
! python3 main_train.py --model 'VGG16' --num_channel 1 --model_path 'l1_norm/model/VGG16/grey' --cuda --gpuids 0 1 --epochs 150 --data cifar10 --batch_size 128

Run Prune l1_norm

RGB

!python l1_norm/resnetprune.py --num_channel 3 --dataset cifar10 --model l1_norm/model/resnet/RGB/ckpt_best.pth --save l1_norm/prune/resnset/RGB
!python l1_norm/vggprune.py --num_channel 3 --dataset cifar10 --model l1_norm/model/VGG16/RGB/ckpt_best.pth --save l1_norm/prune/vgg/RGB

GREY

!python l1_norm/resnetprune.py --num_channel 1 --dataset cifar10 --model l1_norm/model/resnet/grey/ckpt_best.pth --save l1_norm/prune/resnset/grey
!python l1_norm/vggprune.py --num_channel 1 --dataset cifar10 --model l1_norm/model/VGG16/grey/ckpt_best.pth --save l1_norm/prune/vgg/grey