48 lines
1.9 KiB
Bash
48 lines
1.9 KiB
Bash
# Use docker: paddlepaddle/paddle:latest-gpu-cuda10.1-cudnn7 paddle=2.1.2 python3.7
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#
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# Usage:
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# git clone https://github.com/PaddlePaddle/PaddleDetection.git
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# cd PaddleDetection
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# bash benchmark/run_all.sh
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log_path=${LOG_PATH_INDEX_DIR:-$(pwd)} # benchmark系统指定该参数,不需要跑profile时,log_path指向存speed的目录
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# run prepare.sh
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bash benchmark/prepare.sh
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model_name_list=(faster_rcnn fcos deformable_detr gfl hrnet higherhrnet solov2 jde fairmot)
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fp_item_list=(fp32)
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max_epoch=2
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for model_item in ${model_name_list[@]}; do
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for fp_item in ${fp_item_list[@]}; do
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case ${model_item} in
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faster_rcnn) bs_list=(1 8) ;;
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fcos) bs_list=(2) ;;
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deformable_detr) bs_list=(2) ;;
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gfl) bs_list=(2) ;;
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hrnet) bs_list=(64) ;;
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higherhrnet) bs_list=(20) ;;
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solov2) bs_list=(2) ;;
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jde) bs_list=(4) ;;
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fairmot) bs_list=(6) ;;
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*) echo "wrong model_name"; exit 1;
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esac
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for bs_item in ${bs_list[@]}
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do
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run_mode=sp
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log_name=detection_${model_item}_bs${bs_item}_${fp_item} # 如:clas_MobileNetv1_mp_bs32_fp32_8
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echo "index is speed, 1gpus, begin, ${log_name}"
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CUDA_VISIBLE_DEVICES=0 bash benchmark/run_benchmark.sh ${run_mode} ${bs_item} \
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${fp_item} ${max_epoch} ${model_item} | tee ${log_path}/${log_name}_speed_1gpus 2>&1
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sleep 60
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run_mode=mp
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log_name=detection_${model_item}_bs${bs_item}_${fp_item} # 如:clas_MobileNetv1_mp_bs32_fp32_8
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echo "index is speed, 8gpus, run_mode is multi_process, begin, ${log_name}"
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CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 bash benchmark/run_benchmark.sh ${run_mode} \
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${bs_item} ${fp_item} ${max_epoch} ${model_item}| tee ${log_path}/${log_name}_speed_8gpus8p 2>&1
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sleep 60
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done
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done
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done
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