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# 提供可稳定复现性能的脚本， ：
# 执行目录：需说明
CUR_DIR = ${ PWD }
source ../../tools/venv/bin/activate
#cd **
pushd ../../examples/aishell/s1
# 1 安装该模型需要的依赖 (如需开启优化策略请注明)
# 2 拷贝该模型需要数据、预训练模型
source path.sh
fp_item_list = ( fp32)
bs_item = ( 16)
config_path = conf/conformer.yaml
seed = 0
output = exp/conformer
profiler_options = None
for fp_item in ${ fp_item_list [@] } ; do
for batch_size in ${ bs_item [@] }
do
rm exp -rf
echo "index is speed, 8gpus, run_mode is multi_process, begin, conformer"
run_mode = mp
ngpu = 8
CUDA_VISIBLE_DEVICES = 0,1,2,3,4,5,6,7 bash ${ CUR_DIR } /run_benchmark.sh ${ run_mode } ${ config_path } ${ output } ${ seed } ${ ngpu } ${ profiler_options } ${ batch_size } ${ fp_item } ${ CUR_DIR }
rm exp -rf
echo "index is speed, 1gpus, begin, conformer"
run_mode = sp
ngpu = 1
CUDA_VISIBLE_DEVICES = 0 bash ${ CUR_DIR } /run_benchmark.sh ${ run_mode } ${ config_path } ${ output } ${ seed } ${ ngpu } ${ profiler_options } ${ batch_size } ${ fp_item } ${ CUR_DIR }
done
done
popd
mkdir -p log
bash run_analysis_sp.sh > log/log_sp.out
bash run_analysis_mp.sh > log/log_mp.out
