86 lines
2.7 KiB
Bash
86 lines
2.7 KiB
Bash
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#!/bin/bash
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# bash ./scripts-search/search-cifar.sh cifar10 ResNet110 CIFAR 0.57 777
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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 5 ] ;then
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echo "Input illegal number of parameters " $#
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echo "Need 5 parameters for the dataset and the-model-name and the-optimizer and FLOP-ratio and the-random-seed"
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exit 1
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fi
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if [ "$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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optim=$3
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batch=256
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gumbel_min=0.1
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gumbel_max=5
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expected_FLOP_ratio=$4
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rseed=$5
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PY_C="./env/bin/python"
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if [ ! -f ${PY_C} ]; then
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echo "Local Run with Python: "`which python`
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PY_C="python"
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SAVE_ROOT="./output"
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else
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echo "Cluster Run with Python: "${PY_C}
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SAVE_ROOT="./hadoop-data/TAS-checkpoints"
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mkdir -p $TORCH_HOME/TAS-checkpoints/
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cp -r ./hadoop-data/TAS-checkpoints/basemodels $TORCH_HOME/TAS-checkpoints/
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fi
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save_dir=${SAVE_ROOT}/search-shape/${dataset}-${model}-${optim}-Gumbel_${gumbel_min}_${gumbel_max}-${expected_FLOP_ratio}
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${PY_C} --version
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${PY_C} ./exps/search-transformable.py --dataset ${dataset} \
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--data_path $TORCH_HOME/cifar.python \
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--model_config ./configs/archs/CIFAR-${model}.config \
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--split_path ./.latent-data/splits/${dataset}-0.5.pth \
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--optim_config ./configs/search-opts/${optim}.config \
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--procedure search-v2 \
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--FLOP_ratio ${expected_FLOP_ratio} \
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--FLOP_weight 2 --FLOP_tolerant 0.05 \
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--save_dir ${save_dir} \
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--gumbel_tau_max ${gumbel_max} --gumbel_tau_min ${gumbel_min} \
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--cutout_length -1 \
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--batch_size ${batch} --rand_seed ${rseed} --workers 6 \
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--eval_frequency 1 --print_freq 100 --print_freq_eval 200
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if [ "$rseed" = "-1" ]; then
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echo "Skip training the last configuration"
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else
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# normal training
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xsave_dir=${save_dir}/seed-${rseed}-NMT
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${PY_C} ./exps/basic-main.py --dataset ${dataset} \
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--data_path $TORCH_HOME/cifar.python \
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--model_config ${save_dir}/seed-${rseed}-last.config \
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--optim_config ./configs/opts/CIFAR-E300-W5-L1-COS.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 256 --rand_seed ${rseed} --workers 6 \
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--eval_frequency 1 --print_freq 100 --print_freq_eval 200
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# KD training
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xsave_dir=${save_dir}/seed-${rseed}-KDT
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${PY_C} ./exps/KD-main.py --dataset ${dataset} \
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--data_path $TORCH_HOME/cifar.python \
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--model_config ${save_dir}/seed-${rseed}-last.config \
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--optim_config ./configs/opts/CIFAR-E300-W5-L1-COS.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 256 --rand_seed ${rseed} --workers 6 \
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--eval_frequency 1 --print_freq 100 --print_freq_eval 200
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fi
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