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#!/bin/bash
CUR_DIR = ${ PWD }
ROOT_DIR = ../../
# 提供可稳定复现性能的脚本， ：
# collect env info
bash ${ ROOT_DIR } /utils/pd_env_collect.sh
#cat pd_env.txt
# 1 安装该模型需要的依赖 (如需开启优化策略请注明)
#pushd ${ROOT_DIR}/tools; make; popd
#source ${ROOT_DIR}/tools/venv/bin/activate
#pushd ${ROOT_DIR}; bash setup.sh; popd
# 2 拷贝该模型需要数据、预训练模型
# 执行目录：需说明
#pushd ${ROOT_DIR}/examples/aishell/s1
pushd ${ ROOT_DIR } /examples/tiny/s1
mkdir -p exp/log
. path.sh
#bash local/data.sh &> exp/log/data.log
# 3 批量运行（ ， ， ）
model_mode_list = ( conformer transformer)
fp_item_list = ( fp32)
bs_item_list = ( 32 64 96)
for model_mode in ${ model_mode_list [@] } ; do
for fp_item in ${ fp_item_list [@] } ; do
for bs_item in ${ bs_item_list [@] }
do
echo " index is speed, 1gpus, begin, ${ model_name } "
run_mode = sp
CUDA_VISIBLE_DEVICES = 0 bash ${ CUR_DIR } /run_benchmark.sh ${ run_mode } ${ bs_item } ${ fp_item } 500 ${ model_mode } # (5min)
sleep 60
echo " index is speed, 8gpus, run_mode is multi_process, begin, ${ model_name } "
run_mode = mp
CUDA_VISIBLE_DEVICES = 0,1,2,3,4,5,6,7 bash ${ CUR_DIR } /run_benchmark.sh ${ run_mode } ${ bs_item } ${ fp_item } 500 ${ model_mode }
sleep 60
done
done
done
popd # aishell/s1
