66 lines
		
	
	
		
			1.9 KiB
		
	
	
	
		
			Bash
		
	
	
	
	
	
			
		
		
	
	
			66 lines
		
	
	
		
			1.9 KiB
		
	
	
	
		
			Bash
		
	
	
	
	
	
#!/bin/bash
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# bash ./scripts/tas-infer-train.sh cifar10 C100-ResNet32 -1
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set -e
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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  echo "Input illegal number of parameters " $#
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  echo "Need 3 parameters for the dataset and the-config-name and the-random-seed"
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  exit 1
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fi
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if [ "$TORCH_HOME" = "" ]; then
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  echo "Must set TORCH_HOME envoriment variable for data dir saving"
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  exit 1
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else
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  echo "TORCH_HOME : $TORCH_HOME"
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fi
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dataset=$1
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model=$2
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rseed=$3
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batch=256
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save_dir=./output/search-shape/TAS-INFER-${dataset}-${model}
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if [ ${dataset} == 'cifar10' ] || [ ${dataset} == 'cifar100' ]; then
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  xpath=$TORCH_HOME/cifar.python
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  opt_config=./configs/opts/CIFAR-E300-W5-L1-COS.config
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  workers=4
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elif [ ${dataset} == 'imagenet-1k' ]; then
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  xpath=$TORCH_HOME/ILSVRC2012
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  #opt_config=./configs/opts/ImageNet-E120-Cos-Smooth.config
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  opt_config=./configs/opts/RImageNet-E120-Cos-Soft.config
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  workers=28
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else
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  echo 'Unknown dataset: '${dataset}
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  exit 1
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fi
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python --version
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# normal training
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xsave_dir=${save_dir}-NMT
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OMP_NUM_THREADS=4 python ./exps/basic-main.py --dataset ${dataset} \
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	--data_path ${xpath} \
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	--model_config ./configs/NeurIPS-2019/${model}.config \
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	--optim_config ${opt_config} \
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	--procedure    basic \
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	--save_dir     ${xsave_dir} \
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	--cutout_length -1 \
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	--batch_size ${batch} --rand_seed ${rseed} --workers ${workers} \
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	--eval_frequency 1 --print_freq 100 --print_freq_eval 200
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# KD training
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xsave_dir=${save_dir}-KDT
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OMP_NUM_THREADS=4 python ./exps/KD-main.py --dataset ${dataset} \
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	--data_path ${xpath} \
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	--model_config ./configs/NeurIPS-2019/${model}.config \
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	--optim_config  ${opt_config} \
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	--KD_checkpoint ./.latent-data/basemodels/${dataset}/${model}.pth \
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	--procedure    Simple-KD \
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	--save_dir     ${xsave_dir} \
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	--KD_alpha 0.9 --KD_temperature 4 \
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	--cutout_length -1 \
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	--batch_size ${batch} --rand_seed ${rseed} --workers ${workers} \
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	--eval_frequency 1 --print_freq 100 --print_freq_eval 200
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