add autodl

AutoDL-Projects/scripts/tas-infer-train.sh

@@ -0,0 +1,65 @@
+#!/bin/bash
+# bash ./scripts/tas-infer-train.sh cifar10 C100-ResNet32 -1
+set -e
+echo script name: $0
+echo $# arguments
+if [ "$#" -ne 3 ] ;then
+  echo "Input illegal number of parameters " $#
+  echo "Need 3 parameters for the dataset and the-config-name and the-random-seed"
+  exit 1
+fi
+if [ "$TORCH_HOME" = "" ]; then
+  echo "Must set TORCH_HOME envoriment variable for data dir saving"
+  exit 1
+else
+  echo "TORCH_HOME : $TORCH_HOME"
+fi
+
+dataset=$1
+model=$2
+rseed=$3
+batch=256
+
+save_dir=./output/search-shape/TAS-INFER-${dataset}-${model}
+
+if [ ${dataset} == 'cifar10' ] || [ ${dataset} == 'cifar100' ]; then
+  xpath=$TORCH_HOME/cifar.python
+  opt_config=./configs/opts/CIFAR-E300-W5-L1-COS.config
+  workers=4
+elif [ ${dataset} == 'imagenet-1k' ]; then
+  xpath=$TORCH_HOME/ILSVRC2012
+  #opt_config=./configs/opts/ImageNet-E120-Cos-Smooth.config
+  opt_config=./configs/opts/RImageNet-E120-Cos-Soft.config
+  workers=28
+else
+  echo 'Unknown dataset: '${dataset}
+  exit 1
+fi
+
+python --version
+
+# normal training
+xsave_dir=${save_dir}-NMT
+OMP_NUM_THREADS=4 python ./exps/basic/basic-main.py --dataset ${dataset} \
+	--data_path ${xpath} \
+	--model_config ./configs/NeurIPS-2019/${model}.config \
+	--optim_config ${opt_config} \
+	--procedure    basic \
+	--save_dir     ${xsave_dir} \
+	--cutout_length -1 \
+	--batch_size ${batch} --rand_seed ${rseed} --workers ${workers} \
+	--eval_frequency 1 --print_freq 100 --print_freq_eval 200
+
+# KD training
+xsave_dir=${save_dir}-KDT
+OMP_NUM_THREADS=4 python ./exps/basic/KD-main.py --dataset ${dataset} \
+	--data_path ${xpath} \
+	--model_config ./configs/NeurIPS-2019/${model}.config \
+	--optim_config  ${opt_config} \
+	--KD_checkpoint ./.latent-data/basemodels/${dataset}/${model}.pth \
+	--procedure    Simple-KD \
+	--save_dir     ${xsave_dir} \
+	--KD_alpha 0.9 --KD_temperature 4 \
+	--cutout_length -1 \
+	--batch_size ${batch} --rand_seed ${rseed} --workers ${workers} \
+	--eval_frequency 1 --print_freq 100 --print_freq_eval 200