add analysis
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@ -45,6 +45,10 @@ function _train(){
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rm ${log_file}
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rm ${log_file}
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cp mylog/workerlog.0 ${log_file}
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cp mylog/workerlog.0 ${log_file}
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fi
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fi
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# run log analysis
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analysis_cmd="python3.7 benchmark/analysis.py --filename ${log_file} --mission_name ${model_name} --run_mode ${mode} --direction_id 0 --keyword 'ips:' --base_batch_size ${batch_szie} --skip_steps 1 --gpu_num ${num_gpu_devices} --index 1 --model_mode=-1 --ips_unit=samples/sec"
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eval $analysis_cmd
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}
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}
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_set_params $@
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_set_params $@
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@ -8,7 +8,7 @@ python3.7 -m pip install -r requirements.txt
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#wget -p ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_pretrained.pdparams
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#wget -p ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_pretrained.pdparams
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# 3 批量运行(如不方便批量,1,2需放到单个模型中)
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# 3 批量运行(如不方便批量,1,2需放到单个模型中)
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model_mode_list=(ch_ppocr_v2.0/ch_det_res18_db_v2.0 det_r50_vd_east)
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model_mode_list=(det_res18_db_v2.0 det_r50_vd_east)
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fp_item_list=(fp32)
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fp_item_list=(fp32)
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bs_list=(8 16)
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bs_list=(8 16)
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for model_mode in ${model_mode_list[@]}; do
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for model_mode in ${model_mode_list[@]}; do
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