update codes
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		| @@ -16,6 +16,7 @@ conda install pytorch torchvision cuda100 -c pytorch | ||||
| Searching CNNs | ||||
| ``` | ||||
| bash ./scripts-cnn/search.sh 1 base cifar10 | ||||
| bash ./scripts-cnn/DMS-V-TrainV3.sh 1 | ||||
| bash ./scripts-cnn/search-acc-v2.sh 3 acc2 | ||||
| ``` | ||||
|  | ||||
|   | ||||
| @@ -219,8 +219,8 @@ def main(): | ||||
|   print_log('Finish with training time = {:}'.format( convert_secs2time(total_train_time, True) ), log) | ||||
|  | ||||
|   # clear GPU cache | ||||
|   torch.cuda.empty_cache() | ||||
|   main_procedure(config, args.dataset, args.data_path, args, basemodel.genotype(), 36, 20, log) | ||||
|   #torch.cuda.empty_cache() | ||||
|   #main_procedure(config, args.dataset, args.data_path, args, basemodel.genotype(), 36, 20, log) | ||||
|   log.close() | ||||
|  | ||||
|  | ||||
|   | ||||
| @@ -1,7 +1,8 @@ | ||||
| #!/usr/bin/env sh | ||||
| if [ "$#" -ne 2 ] ;then | ||||
| # bash scripts-cnn/DMS-V-TrainV3.sh 1 | ||||
| if [ "$#" -ne 1 ] ;then | ||||
|   echo "Input illegal number of parameters " $# | ||||
|   echo "Need 2 parameters for the GPUs and the epochs" | ||||
|   echo "Need 1 parameters for the GPUs and the epochs" | ||||
|   exit 1                | ||||
| fi  | ||||
| if [ "$TORCH_HOME" = "" ]; then | ||||
| @@ -15,10 +16,10 @@ gpus=$1 | ||||
| arch=acc2 | ||||
| cutout=0 | ||||
| dataset=cifar10 | ||||
| epoch=$2 | ||||
| epoch=200 | ||||
| SAVED=./snapshots/NAS/ACC-V3-Search-${arch}-${dataset}-cut${cutout}-${epoch}-E600 | ||||
| 
 | ||||
| CUDA_VISIBLE_DEVICES=${gpus} python ./exps-nas/acc_search_v3.py \ | ||||
| CUDA_VISIBLE_DEVICES=${gpus} python ./exps-cnn/GDAS-Search.py \ | ||||
| 	--data_path $TORCH_HOME/cifar.python \ | ||||
| 	--arch ${arch} --dataset ${dataset} --batch_size 128 \ | ||||
| 	--save_path ${SAVED} \ | ||||
| @@ -26,5 +27,5 @@ CUDA_VISIBLE_DEVICES=${gpus} python ./exps-nas/acc_search_v3.py \ | ||||
| 	--epochs ${epoch} --cutout ${cutout} --validate --grad_clip 5 \ | ||||
| 	--init_channels 16 --layers 8 \ | ||||
| 	--tau_max 10 --tau_min 1 \ | ||||
| 	--model_config ./configs/nas-cifar-cos.config \ | ||||
| 	--print_freq 100 --workers 8 | ||||
| 	--model_config ./configs/nas-cifar-cos-cut.config \ | ||||
| 	--print_freq 100 --workers 10 | ||||
| @@ -18,12 +18,12 @@ dataset=cifar10 | ||||
| epoch=200 | ||||
| SAVED=./snapshots/NAS/ACC-V2-Search-${arch}-${dataset}-cut${cutout}-${epoch}-E600 | ||||
|  | ||||
| CUDA_VISIBLE_DEVICES=${gpus} python ./exps-cnn/DARTS-Search.py \ | ||||
| CUDA_VISIBLE_DEVICES=${gpus} python ./exps-cnn/GDAS-Search.py \ | ||||
| 	--data_path $TORCH_HOME/cifar.python \ | ||||
| 	--arch ${arch} --dataset ${dataset} --batch_size 128 \ | ||||
| 	--save_path ${SAVED} \ | ||||
| 	--learning_rate_max 0.025 --learning_rate_min 0.001 --momentum 0.9 --weight_decay 0.0003 \ | ||||
| 	--epochs ${epoch} --cutout ${cutout} --validate --grad_clip 5 \ | ||||
| 	--init_channels 16 --layers 8 \ | ||||
| 	--model_config ./configs/nas-cifar-cos.config \ | ||||
| 	--model_config ./configs/nas-cifar-cos-cut.config \ | ||||
| 	--print_freq 100 --workers 10 | ||||
|   | ||||
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