update ImageNet training
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@@ -1,7 +1,7 @@
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#!/usr/bin/env sh
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if [ "$#" -ne 3 ] ;then
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if [ "$#" -ne 5 ] ;then
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echo "Input illegal number of parameters " $#
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echo "Need 3 parameters for the architecture, and the channel and the layers"
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echo "Need 5 parameters for the architecture, and the channel, and the layers, and the batch-size, and the seed"
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exit 1
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fi
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if [ "$TORCH_HOME" = "" ]; then
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@@ -15,7 +15,9 @@ arch=$1
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dataset=imagenet
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channels=$2
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layers=$3
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SAVED=./output/NAS-CNN/${arch}-${dataset}-C${channels}-L${layers}-E250
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BATCH=$4
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seed=$5
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SAVED=./output/NAS-CNN/${arch}-${dataset}-C${channels}-L${layers}-${BATCH}-E250
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PY_C="./env/bin/python"
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#PY_C="$CONDA_PYTHON_EXE"
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@@ -27,8 +29,8 @@ else
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echo "Cluster Run with Python: "${PY_C}
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echo "Unzip ILSVRC2012"
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tar --version
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#tar xf ./hadoop-data/ILSVRC2012.tar -C ${TORCH_HOME}
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commands="./data/data/get_imagenet.sh"
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tar -xf ./hadoop-data/ILSVRC2012.tar -C ${TORCH_HOME}
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#commands="./data/data/get_imagenet.sh"
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#${PY_C} ./data/decompress.py ./hadoop-data/ILSVRC2012-TAR ./data/data/ILSVRC2012 tar > ${commands}
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#${PY_C} ./data/decompress.py ./hadoop-data/ILSVRC2012-ZIP ./data/data/ILSVRC2012 zip > ./data/data/get_imagenet.sh
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#bash ./data/data/get_imagenet.sh
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@@ -42,16 +44,16 @@ else
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# free -g
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#done < "${commands}"
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#wget http://10.127.2.44:8000/ILSVRC2012.tar --directory-prefix=${TORCH_HOME}
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${PY_C} ./data/decompress.py ./data/classes.txt ${TORCH_HOME}/ILSVRC2012 wget > ${commands}
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count=0
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while read -r line; do
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temp_file="./data/data/TEMP-${count}.sh"
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echo "${line}" > ${temp_file}
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bash ${temp_file}
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count=$((count+1))
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#${PY_C} ./data/decompress.py ./data/classes.txt ${TORCH_HOME}/ILSVRC2012 wget > ${commands}
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#count=0
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#while read -r line; do
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# temp_file="./data/data/TEMP-${count}.sh"
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# echo "${line}" > ${temp_file}
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# bash ${temp_file}
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# count=$((count+1))
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#${PY_C} ./data/ps_mem.py -p $$
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# free -g
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done < "${commands}"
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#done < "${commands}"
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#echo "Copy ILSVRC2012 done"
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#tar -xvf ${TORCH_HOME}/ILSVRC2012.tar -C ${TORCH_HOME}
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#rm ${TORCH_HOME}/ILSVRC2012.tar
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@@ -66,5 +68,6 @@ ${PY_C} ./exps-cnn/train_base.py \
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--save_path ${SAVED} \
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--grad_clip 5 \
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--init_channels ${channels} --layers ${layers} \
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--model_config ./configs/nas-imagenet.config \
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--model_config ./configs/nas-imagenet-${BATCH}.config \
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--manualSeed ${seed} \
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--print_freq 200 --workers 20
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