typhoonzero
7 years ago
commit
fab63cc612
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After Width: | Height: | Size: 18 KiB |
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After Width: | Height: | Size: 20 KiB |
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After Width: | Height: | Size: 18 KiB |
@ -0,0 +1,87 @@
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set -e
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function clock_to_seconds() {
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hours=`echo $1 | awk -F ':' '{print $1}'`
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mins=`echo $1 | awk -F ':' '{print $2}'`
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secs=`echo $1 | awk -F ':' '{print $3}'`
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echo `awk 'BEGIN{printf "%.2f",('$secs' + '$mins' * 60 + '$hours' * 3600)}'`
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}
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function infer() {
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unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
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topology=$1
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layer_num=$2
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bs=$3
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use_mkldnn=$4
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if [ $4 == "True" ]; then
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thread=1
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log="logs/infer-${topology}-${layer_num}-mkldnn-${bs}.log"
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elif [ $4 == "False" ]; then
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thread=`nproc`
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if [ $thread -gt $bs ]; then
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thread=$bs
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fi
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log="logs/infer-${topology}-${layer_num}-${thread}mklml-${bs}.log"
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else
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echo "Wrong input $4, use True or False."
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exit 0
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fi
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models_in="models/${topology}-${layer_num}/pass-00000/"
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if [ ! -d $models_in ]; then
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echo "Training model ${topology}_${layer_num}"
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paddle train --job=train \
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--config="${topology}.py" \
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--use_mkldnn=True \
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--use_gpu=False \
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--trainer_count=1 \
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--num_passes=1 \
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--save_dir="models/${topology}-${layer_num}" \
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--config_args="batch_size=128,layer_num=${layer_num},num_samples=256" \
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> /dev/null 2>&1
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echo "Done"
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fi
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log_period=$((256 / bs))
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paddle train --job=test \
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--config="${topology}.py" \
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--use_mkldnn=$use_mkldnn \
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--use_gpu=False \
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--trainer_count=$thread \
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--log_period=$log_period \
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--config_args="batch_size=${bs},layer_num=${layer_num},is_infer=True" \
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--init_model_path=$models_in \
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2>&1 | tee ${log}
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# calculate the last 5 logs period time of 1280 samples,
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# the time before are burning time.
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start=`tail ${log} -n 7 | head -n 1 | awk -F ' ' '{print $2}' | xargs`
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end=`tail ${log} -n 2 | head -n 1 | awk -F ' ' '{print $2}' | xargs`
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start_sec=`clock_to_seconds $start`
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end_sec=`clock_to_seconds $end`
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fps=`awk 'BEGIN{printf "%.2f",(1280 / ('$end_sec' - '$start_sec'))}'`
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echo "Last 1280 samples start: ${start}(${start_sec} sec), end: ${end}(${end_sec} sec;" >> ${log}
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echo "FPS: $fps images/sec" 2>&1 | tee -a ${log}
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}
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if [ ! -f "train.list" ]; then
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echo " " > train.list
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fi
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if [ ! -f "test.list" ]; then
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echo " " > test.list
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fi
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if [ ! -d "logs" ]; then
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mkdir logs
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fi
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if [ ! -d "models" ]; then
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mkdir -p models
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fi
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# inference benchmark
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for use_mkldnn in True False; do
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for batchsize in 1 2 4 8 16; do
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infer vgg 19 $batchsize $use_mkldnn
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infer resnet 50 $batchsize $use_mkldnn
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infer googlenet v1 $batchsize $use_mkldnn
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infer alexnet 2 $batchsize $use_mkldnn
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done
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done
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@ -0,0 +1,68 @@
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set -e
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function clock_to_seconds() {
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hours=`echo $1 | awk -F ':' '{print $1}'`
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mins=`echo $1 | awk -F ':' '{print $2}'`
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secs=`echo $1 | awk -F ':' '{print $3}'`
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echo `awk 'BEGIN{printf "%.2f",('$secs' + '$mins' * 60 + '$hours' * 3600)}'`
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}
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function infer() {
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topology=$1
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layer_num=$2
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bs=$3
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trainers=`nproc`
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if [ $trainers -gt $bs ]; then
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trainers=$bs
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fi
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log="logs/infer-${topology}-${layer_num}-${trainers}openblas-${bs}.log"
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threads=$((`nproc` / trainers))
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if [ $threads -eq 0 ]; then
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threads=1
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fi
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export OPENBLAS_NUM_THREADS=$threads
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models_in="models/${topology}-${layer_num}/pass-00000/"
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if [ ! -d $models_in ]; then
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echo "./run_mkl_infer.sh to save the model first"
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exit 0
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fi
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log_period=$((32 / bs))
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paddle train --job=test \
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--config="${topology}.py" \
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--use_mkldnn=False \
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--use_gpu=False \
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--trainer_count=$trainers \
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--log_period=$log_period \
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--config_args="batch_size=${bs},layer_num=${layer_num},is_infer=True,num_samples=256" \
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--init_model_path=$models_in \
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2>&1 | tee ${log}
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# calculate the last 5 logs period time of 160(=32*5) samples,
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# the time before are burning time.
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start=`tail ${log} -n 7 | head -n 1 | awk -F ' ' '{print $2}' | xargs`
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end=`tail ${log} -n 2 | head -n 1 | awk -F ' ' '{print $2}' | xargs`
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start_sec=`clock_to_seconds $start`
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end_sec=`clock_to_seconds $end`
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fps=`awk 'BEGIN{printf "%.2f",(160 / ('$end_sec' - '$start_sec'))}'`
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echo "Last 160 samples start: ${start}(${start_sec} sec), end: ${end}(${end_sec} sec;" >> ${log}
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echo "FPS: $fps images/sec" 2>&1 | tee -a ${log}
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}
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if [ ! -f "train.list" ]; then
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echo " " > train.list
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fi
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if [ ! -f "test.list" ]; then
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echo " " > test.list
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fi
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if [ ! -d "logs" ]; then
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mkdir logs
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fi
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# inference benchmark
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for batchsize in 1 2 4 8 16; do
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infer vgg 19 $batchsize
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infer resnet 50 $batchsize
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infer googlenet v1 $batchsize
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infer alexnet 2 $batchsize
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done
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@ -0,0 +1,41 @@
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set -e
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function train() {
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export OPENBLAS_NUM_THREADS=1
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topology=$1
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layer_num=$2
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bs=$3
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thread=`nproc`
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# each trainer_count use only 1 core to avoid conflict
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log="logs/train-${topology}-${layer_num}-${thread}openblas-${bs}.log"
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args="batch_size=${bs},layer_num=${layer_num}"
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config="${topology}.py"
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paddle train --job=time \
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--config=$config \
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--use_mkldnn=False \
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--use_gpu=False \
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--trainer_count=$thread \
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--log_period=3 \
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--test_period=30 \
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--config_args=$args \
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2>&1 | tee ${log}
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avg_time=`tail ${log} -n 1 | awk -F ' ' '{print $8}' | sed 's/avg=//'`
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fps=`awk 'BEGIN{printf "%.2f",('$bs' / '$avg_time' * 1000)}'`
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echo "FPS: $fps images/sec" 2>&1 | tee -a ${log}
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}
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if [ ! -f "train.list" ]; then
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echo " " > train.list
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fi
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if [ ! -d "logs" ]; then
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mkdir logs
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fi
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# training benchmark
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for batchsize in 64 128 256; do
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train vgg 19 $batchsize
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train resnet 50 $batchsize
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train googlenet v1 $batchsize
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train alexnet 2 $batchsize
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done
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@ -0,0 +1,45 @@
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# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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IF(MOBILE_INFERENCE OR NOT WITH_DISTRIBUTE)
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return()
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ENDIF()
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include (ExternalProject)
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# NOTE: c-ares is needed when linking with grpc.
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SET(CARES_SOURCES_DIR ${THIRD_PARTY_PATH}/cares)
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SET(CARES_INSTALL_DIR ${THIRD_PARTY_PATH}/install/cares)
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SET(CARES_INCLUDE_DIR "${CARES_INSTALL_DIR}/include/" CACHE PATH "cares include directory." FORCE)
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ExternalProject_Add(
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extern_cares
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GIT_REPOSITORY "https://github.com/c-ares/c-ares.git"
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GIT_TAG "cares-1_13_0"
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PREFIX ${CARES_SOURCES_DIR}
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UPDATE_COMMAND ""
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CONFIGURE_COMMAND ./buildconf && ./configure --disable-shared --prefix=${CARES_INSTALL_DIR}
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BUILD_IN_SOURCE 1
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BUILD_COMMAND make -j8
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INSTALL_COMMAND make install
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)
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ADD_LIBRARY(cares STATIC IMPORTED GLOBAL)
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SET_PROPERTY(TARGET cares PROPERTY IMPORTED_LOCATION
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"${CARES_INSTALL_DIR}/lib/libcares.a")
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include_directories(${CARES_INCLUDE_DIR})
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ADD_DEPENDENCIES(cares extern_cares)
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