add analysis

benchmark/run_benchmark_det.sh

@@ -45,6 +45,10 @@ function _train(){
         rm ${log_file}
         cp mylog/workerlog.0 ${log_file}
     fi
+
+    # run log analysis
+    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"
+    eval $analysis_cmd
 }
 
 _set_params $@

benchmark/run_det.sh

@@ -8,7 +8,7 @@ python3.7 -m pip install -r requirements.txt
 #wget -p ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_pretrained.pdparams
 # 3 批量运行（如不方便批量，1，2需放到单个模型中）
 
-model_mode_list=(ch_ppocr_v2.0/ch_det_res18_db_v2.0 det_r50_vd_east)
+model_mode_list=(det_res18_db_v2.0 det_r50_vd_east)
 fp_item_list=(fp32)
 bs_list=(8 16)
 for model_mode in ${model_mode_list[@]}; do