From eb827bb35b4a37dedfd3e0e7e62c8e37296b851a Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 16:07:24 +0800
Subject: [PATCH 01/34] add test shell

---
 test/params.txt |  18 +++++++
 test/test.sh    | 141 ++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 159 insertions(+)
 create mode 100644 test/params.txt
 create mode 100644 test/test.sh

diff --git a/test/params.txt b/test/params.txt
new file mode 100644
index 00000000..8101714f
--- /dev/null
+++ b/test/params.txt
@@ -0,0 +1,18 @@
+train_model_list: det;benchmark/benchmark_det.yml
+gpu_list: -1|0|0,1
+auto_cast_list: False|True
+trainer_list: norm|quant|prune
+python: python3.7
+
+inference: python|C++
+devices: cpu|gpu
+use_mkldnn_list: True|False
+cpu_threads_list: 1|6
+rec_batch_size_list: 1|6
+gpu_trt_list: True|False
+gpu_precision_list: fp32|fp16|int8
+img_dir: /paddle/OCR/test_set/benchmark_eval
+
+epoch: 10
+checkpoints: None
+
diff --git a/test/test.sh b/test/test.sh
new file mode 100644
index 00000000..24605130
--- /dev/null
+++ b/test/test.sh
@@ -0,0 +1,141 @@
+#!/bin/bash 
+FILENAME=$1
+
+# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer']
+MODE=$2
+# prepare pretrained weights and dataset 
+wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
+if [ ${MODE} = "lite_train_infer" ];then
+    # pretrain lite train data
+    rm -rf ./train_data/icdar2015
+    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
+    cd ./train_data/ && tar xf icdar2015_lite.tar && 
+    ln -s ./icdar2015_lite ./icdar2015
+    cd ../
+elif [ ${MODE} = "whole_train_infer" ];then
+    rm -rf ./train_data/icdar2015
+    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar
+    cd ./train_data/ && tar xf icdar2015.tar && cd ../
+else
+    echo "Do Nothing"
+fi
+
+
+dataline=$(cat ${FILENAME})
+# parser params
+IFS=$'\n'
+lines=(${dataline})
+function func_parser(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[1]}
+    echo ${tmp}
+}
+IFS=$'\n'
+# The training params
+train_model_list=$(func_parser "${lines[0]}")
+gpu_list=$(func_parser "${lines[1]}")
+auto_cast_list=$(func_parser "${lines[2]}")
+slim_trainer_list=$(func_parser "${lines[3]}")
+python=$(func_parser "${lines[4]}")
+# inference params
+inference=$(func_parser "${lines[5]}")
+devices=$(func_parser "${lines[6]}")
+use_mkldnn_list=$(func_parser "${lines[7]}")
+cpu_threads_list=$(func_parser "${lines[8]}")
+rec_batch_size_list=$(func_parser "${lines[9]}")
+gpu_trt_list=$(func_parser "${lines[10]}")
+gpu_precision_list=$(func_parser "${lines[11]}")
+img_dir=$(func_parser "${lines[12]}")
+
+# train superparameters
+epoch=$(func_parser "${lines[13]}")
+checkpoints=$(func_parser "${lines[14]}")
+
+
+for train_model in ${train_model_list[*]}; do 
+    if [ ${train_model} = "det" ];then
+        model_name="det"
+        yml_file="configs/det/det_mv3_db.yml"
+    elif [ ${train_model} = "rec" ];then
+        model_name="rec"
+        yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
+    else
+        model_name="det"
+        yml_file="configs/det/det_mv3_db.yml"
+    fi
+    # array=(${train_model})
+    # for j in "${!array[@]}"; do
+    #     model_name=${array[0]}
+    #     yml_file=${array[1]}
+    # done
+    IFS="|"
+    for gpu in ${gpu_list[*]}; do
+        use_gpu=True
+        if [ ${gpu} = "-1" ];then
+            lanuch=""
+            use_gpu=False
+        elif [ ${#gpu} -le 1 ];then
+            launch=""
+        else
+            launch="-m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu}"
+        fi
+        # echo "model_name: ${model_name}  yml_file: ${yml_file}   launch: ${launch}   gpu: ${gpu}" 
+        for auto_cast in ${auto_cast_list[*]}; do 
+            for slim_trainer in ${slim_trainer_list[*]}; do 
+                if [ ${slim_trainer} = "norm" ]; then
+                    trainer="tools/train.py"
+                    export_model="tools/export_model.py"
+                elif [ ${slim_trainer} = "quant" ]; then
+                    trainer="deploy/slim/quantization/quant.py"
+                    export_model="deploy/slim/quantization/export_model.py"
+                elif [ ${slim_trainer} = "prune" ]; then
+                    trainer="deploy/slim/prune/sensitivity_anal.py"
+                    export_model="deploy/slim/prune/export_prune_model.py"
+                elif [ ${slim_trainer} = "distill" ]; then
+                    trainer="deploy/slim/distill/train_dml.py"
+                    export_model="deploy/slim/distill/export_distill_model.py"
+                else
+                    trainer="tools/train.py"
+                    export_model="tools/export_model.py"
+                fi
+                # dataset="Train.dataset.data_dir=${train_dir}  Train.dataset.label_file_list=${train_label_file}  Eval.dataset.data_dir=${eval_dir} Eval.dataset.label_file_list=${eval_label_file}"
+                save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
+                echo ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Global.epoch=${epoch}
+                echo ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ 
+                if [ "${model_name}" = "det" ]; then 
+                    export rec_batch_size_list=( "1" )
+                    inference="tools/infer/predict_det.py"
+                elif [ "${model_name}" = "rec" ]; then
+                    inference="tools/infer/predict_rec.py"
+                fi
+                # inference 
+                for device in ${devices[*]}; do 
+                    if [ ${device} = "cpu" ]; then
+                        for use_mkldnn in ${use_mkldnn_list[*]}; do
+                            for threads in ${cpu_threads_list[*]}; do
+                                for rec_batch_size in ${rec_batch_size_list[*]}; do    
+                                    echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                    # ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  2>&1 | tee ${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                done
+                            done
+                        done
+                    else 
+                        for use_trt in ${gpu_trt_list[*]}; do
+                            for precision in ${gpu_precision_list[*]}; do
+                                if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
+                                    continue
+                                fi
+                                for rec_batch_size in ${rec_batch_size_list[*]}; do
+                                    # echo "${model_name}  ${det_model_dir} ${rec_model_dir}, use_trt: ${use_trt}   use_fp16: ${use_fp16}"
+                                    echo ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log
+                                done
+                            done
+                        done
+                    fi
+                done
+            done
+        done
+    done
+done

From 27b543ab13c206491acaf48003f03e92114d5eb4 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 16:08:52 +0800
Subject: [PATCH 02/34] delete echo and note

---
 test/test.sh | 11 +++--------
 1 file changed, 3 insertions(+), 8 deletions(-)

diff --git a/test/test.sh b/test/test.sh
index 24605130..559dc4b0 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -65,11 +65,6 @@ for train_model in ${train_model_list[*]}; do
         model_name="det"
         yml_file="configs/det/det_mv3_db.yml"
     fi
-    # array=(${train_model})
-    # for j in "${!array[@]}"; do
-    #     model_name=${array[0]}
-    #     yml_file=${array[1]}
-    # done
     IFS="|"
     for gpu in ${gpu_list[*]}; do
         use_gpu=True
@@ -103,7 +98,7 @@ for train_model in ${train_model_list[*]}; do
                 # dataset="Train.dataset.data_dir=${train_dir}  Train.dataset.label_file_list=${train_label_file}  Eval.dataset.data_dir=${eval_dir} Eval.dataset.label_file_list=${eval_label_file}"
                 save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
                 echo ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Global.epoch=${epoch}
-                echo ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ 
+                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ 
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
                     inference="tools/infer/predict_det.py"
@@ -117,7 +112,7 @@ for train_model in ${train_model_list[*]}; do
                             for threads in ${cpu_threads_list[*]}; do
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do    
                                     echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                                    # ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  2>&1 | tee ${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  2>&1 | tee ${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
                                 done
                             done
                         done
@@ -129,7 +124,7 @@ for train_model in ${train_model_list[*]}; do
                                 fi
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do
                                     # echo "${model_name}  ${det_model_dir} ${rec_model_dir}, use_trt: ${use_trt}   use_fp16: ${use_fp16}"
-                                    echo ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log
+                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log
                                 done
                             done
                         done

From 40f78f7531f0ff898be5b256401dc16d7faaf31d Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 16:11:20 +0800
Subject: [PATCH 03/34] rename key

---
 test/params.txt | 2 +-
 test/test.sh    | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/test/params.txt b/test/params.txt
index 8101714f..9a4b52e8 100644
--- a/test/params.txt
+++ b/test/params.txt
@@ -1,4 +1,4 @@
-train_model_list: det;benchmark/benchmark_det.yml
+train_model_list: ocr_det
 gpu_list: -1|0|0,1
 auto_cast_list: False|True
 trainer_list: norm|quant|prune
diff --git a/test/test.sh b/test/test.sh
index 559dc4b0..a17d3274 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -55,10 +55,10 @@ checkpoints=$(func_parser "${lines[14]}")
 
 
 for train_model in ${train_model_list[*]}; do 
-    if [ ${train_model} = "det" ];then
+    if [ ${train_model} = "ocr_det" ];then
         model_name="det"
         yml_file="configs/det/det_mv3_db.yml"
-    elif [ ${train_model} = "rec" ];then
+    elif [ ${train_model} = "ocr_rec" ];then
         model_name="rec"
         yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
     else

From a1494515a804516a0036926c496f2c457b8ca204 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 16:13:28 +0800
Subject: [PATCH 04/34] add usage

---
 test/test.sh | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/test/test.sh b/test/test.sh
index a17d3274..6ba13c19 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -1,4 +1,7 @@
 #!/bin/bash 
+# Usage:
+# bash test/test.sh ./test/params.txt 'lite_train_infer'
+
 FILENAME=$1
 
 # MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer']

From 83149576de2ab6b664c8608ed0106bd5967b8cc2 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 16:18:08 +0800
Subject: [PATCH 05/34] remove img_dir from params.txt

---
 test/params.txt | 3 +--
 test/test.sh    | 7 +++----
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/test/params.txt b/test/params.txt
index 9a4b52e8..67b2f8f1 100644
--- a/test/params.txt
+++ b/test/params.txt
@@ -1,6 +1,6 @@
 train_model_list: ocr_det
 gpu_list: -1|0|0,1
-auto_cast_list: False|True
+auto_cast_list: False
 trainer_list: norm|quant|prune
 python: python3.7
 
@@ -11,7 +11,6 @@ cpu_threads_list: 1|6
 rec_batch_size_list: 1|6
 gpu_trt_list: True|False
 gpu_precision_list: fp32|fp16|int8
-img_dir: /paddle/OCR/test_set/benchmark_eval
 
 epoch: 10
 checkpoints: None
diff --git a/test/test.sh b/test/test.sh
index 6ba13c19..1bc5a8f6 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -50,11 +50,10 @@ cpu_threads_list=$(func_parser "${lines[8]}")
 rec_batch_size_list=$(func_parser "${lines[9]}")
 gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
-img_dir=$(func_parser "${lines[12]}")
-
+img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
 # train superparameters
-epoch=$(func_parser "${lines[13]}")
-checkpoints=$(func_parser "${lines[14]}")
+epoch=$(func_parser "${lines[12]}")
+checkpoints=$(func_parser "${lines[13]}")
 
 
 for train_model in ${train_model_list[*]}; do 

From 1a06bff08a0b387ddc1c81b500f4394fc5d937b7 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 16:29:22 +0800
Subject: [PATCH 06/34] delete epoch from params.txt

---
 test/params.txt |  2 --
 test/test.sh    | 10 +++++++---
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/test/params.txt b/test/params.txt
index 67b2f8f1..3fe857d3 100644
--- a/test/params.txt
+++ b/test/params.txt
@@ -12,6 +12,4 @@ rec_batch_size_list: 1|6
 gpu_trt_list: True|False
 gpu_precision_list: fp32|fp16|int8
 
-epoch: 10
-checkpoints: None
 
diff --git a/test/test.sh b/test/test.sh
index 1bc5a8f6..1a40eb25 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -15,10 +15,14 @@ if [ ${MODE} = "lite_train_infer" ];then
     cd ./train_data/ && tar xf icdar2015_lite.tar && 
     ln -s ./icdar2015_lite ./icdar2015
     cd ../
+    epoch=10
+    eval_batch_step=10
 elif [ ${MODE} = "whole_train_infer" ];then
     rm -rf ./train_data/icdar2015
     wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar
     cd ./train_data/ && tar xf icdar2015.tar && cd ../
+    epoch=300
+    eval_batch_step=200
 else
     echo "Do Nothing"
 fi
@@ -52,8 +56,8 @@ gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
 img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
 # train superparameters
-epoch=$(func_parser "${lines[12]}")
-checkpoints=$(func_parser "${lines[13]}")
+#epoch=$(func_parser "${lines[12]}")
+#checkpoints=$(func_parser "${lines[13]}")
 
 
 for train_model in ${train_model_list[*]}; do 
@@ -99,7 +103,7 @@ for train_model in ${train_model_list[*]}; do
                 fi
                 # dataset="Train.dataset.data_dir=${train_dir}  Train.dataset.label_file_list=${train_label_file}  Eval.dataset.data_dir=${eval_dir} Eval.dataset.label_file_list=${eval_label_file}"
                 save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
-                echo ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Global.epoch=${epoch}
+                ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
                 ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ 
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )

From 553a6a29cac808792190e263e749e73ed68a3ab0 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 18:24:21 +0800
Subject: [PATCH 07/34] check the exit code

---
 test/test.sh | 17 ++++++++++++++++-
 1 file changed, 16 insertions(+), 1 deletion(-)

diff --git a/test/test.sh b/test/test.sh
index 1a40eb25..0ef5c1d9 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -103,8 +103,16 @@ for train_model in ${train_model_list[*]}; do
                 fi
                 # dataset="Train.dataset.data_dir=${train_dir}  Train.dataset.label_file_list=${train_label_file}  Eval.dataset.data_dir=${eval_dir} Eval.dataset.label_file_list=${eval_label_file}"
                 save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
+                
                 ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
-                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ 
+                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
+                if [ $? -eq 0 ]; then
+                    echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
+                else
+                    cat ${save_log}/train.log
+                    echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${save_log}/train.log
+                fi
+               
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
                     inference="tools/infer/predict_det.py"
@@ -119,6 +127,13 @@ for train_model in ${train_model_list[*]}; do
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do    
                                     echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
                                     ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  2>&1 | tee ${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                    if [ $? -eq 0 ]; then
+                                        echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${log_path}${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                    else
+                                        cat ${log_path}${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                        echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${log_path}${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                    fi
+
                                 done
                             done
                         done

From 07ff561bf0072a2e7cd0825bcaeb09f105564e9a Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 18:37:56 +0800
Subject: [PATCH 08/34] add save_log_path to inference

---
 test/test.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/test.sh b/test/test.sh
index 0ef5c1d9..cd4d93d9 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -126,7 +126,7 @@ for train_model in ${train_model_list[*]}; do
                             for threads in ${cpu_threads_list[*]}; do
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do    
                                     echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  2>&1 | tee ${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
                                     if [ $? -eq 0 ]; then
                                         echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${log_path}${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
                                     else

From 81f2ccb16da0a433d070be036f5534e6dbee84c2 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 20:38:30 +0800
Subject: [PATCH 09/34] add infer.sh

---
 test/infer.sh | 121 ++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 121 insertions(+)
 create mode 100644 test/infer.sh

diff --git a/test/infer.sh b/test/infer.sh
new file mode 100644
index 00000000..35c4db2d
--- /dev/null
+++ b/test/infer.sh
@@ -0,0 +1,121 @@
+#!/bin/bash
+
+dataline=$(cat ${FILENAME})
+# parser params
+IFS=$'\n'
+lines=(${dataline})
+function func_parser(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[1]}
+    echo ${tmp}
+}
+IFS=$'\n'
+# The training params
+train_model_list=$(func_parser "${lines[0]}")
+gpu_list=$(func_parser "${lines[1]}")
+auto_cast_list=$(func_parser "${lines[2]}")
+slim_trainer_list=$(func_parser "${lines[3]}")
+python=$(func_parser "${lines[4]}")
+# inference params
+inference=$(func_parser "${lines[5]}")
+devices=$(func_parser "${lines[6]}")
+use_mkldnn_list=$(func_parser "${lines[7]}")
+cpu_threads_list=$(func_parser "${lines[8]}")
+rec_batch_size_list=$(func_parser "${lines[9]}")
+gpu_trt_list=$(func_parser "${lines[10]}")
+gpu_precision_list=$(func_parser "${lines[11]}")
+
+
+for train_model in ${train_model_list[*]}; do 
+    if [ ${train_model} = "det" ];then
+        model_name="det"
+        yml_file="configs/det/det_mv3_db.yml"
+        img_dir=""
+    elif [ ${train_model} = "rec" ];then
+        model_name="rec"
+        yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
+        img_dir=""
+    fi
+
+    # eval 
+    for slim_trainer in ${slim_trainer_list[*]}; do 
+        if [ ${slim_trainer} = "norm" ]; then
+            if [ ${model_name} = "model_name" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_infer"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
+            else 
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_infer"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
+            fi 
+        elif [ ${slim_trainer} = "quant" ]; then
+            if [ ${model_name} = "model_name" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_quant_infer"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar
+            else
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_quant_infer"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar
+            fi 
+        elif [ ${slim_trainer} = "distill" ]; then
+            if [ ${model_name} = "model_name" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_distill_infer"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_distill_train.tar
+            else
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_distill_infer"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar
+            fi 
+        elif [ ${slim_trainer} = "prune" ]; then
+            if [ ${model_name} = "model_name" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_prune_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar
+            else
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_prune_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
+            fi
+        fi
+
+    echo ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${log_path}/${model_name}
+    echo ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer
+    if [ $? -eq 0 ]; then
+        echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
+    else
+        cat ${save_log}/train.log
+        echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${save_log}/train.log
+    fi
+    if [ "${model_name}" = "det" ]; then 
+        export rec_batch_size_list=( "1" )
+        inference="tools/infer/predict_det.py"
+        det_model_dir=${log_path}/${eval_model_name}_infer
+        rec_model_dir=""
+    elif [ "${model_name}" = "rec" ]; then
+        inference="tools/infer/predict_rec.py"
+        rec_model_dir=${log_path}/${eval_model_name}_infer
+        det_model_dir=""
+    fi
+    # inference 
+    for device in ${devices[*]}; do 
+        if [ ${device} = "cpu" ]; then
+            for use_mkldnn in ${use_mkldnn_list[*]}; do
+                for threads in ${cpu_threads_list[*]}; do
+                    for rec_batch_size in ${rec_batch_size_list[*]}; do    
+                        echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                        # ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  2>&1 | tee ${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                    done
+                done
+            done
+        else 
+            for use_trt in ${gpu_trt_list[*]}; do
+                for precision in ${gpu_precision_list[*]}; do
+                    if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
+                        continue
+                    fi
+                    for rec_batch_size in ${rec_batch_size_list[*]}; do
+                        # echo "${model_name}  ${det_model_dir} ${rec_model_dir}, use_trt: ${use_trt}   use_fp16: ${use_fp16}"
+                        echo ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log
+                    done
+                done
+            done
+        fi
+    done
+done

From f7a554c2af9cff0a40ea70abb01ca77c0884e1c9 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 20:42:11 +0800
Subject: [PATCH 10/34] fix det_model_dir rec_model_dir Null

---
 test/test.sh | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/test/test.sh b/test/test.sh
index cd4d93d9..b43b1a61 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -116,8 +116,12 @@ for train_model in ${train_model_list[*]}; do
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
                     inference="tools/infer/predict_det.py"
+                    det_model_dir=${save_log}/export_inference/
+                    rec_model_dir=""
                 elif [ "${model_name}" = "rec" ]; then
                     inference="tools/infer/predict_rec.py"
+                    rec_model_dir=${save_log}/export_inference/
+                    det_model_dir=""
                 fi
                 # inference 
                 for device in ${devices[*]}; do 

From 58437e644821d420871fae89334a848749181c34 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 21:22:54 +0800
Subject: [PATCH 11/34] refine status check

---
 test/infer.sh | 43 +++++++++++++++++++++++++++++++++----------
 test/test.sh  | 49 ++++++++++++++++++++++++++-----------------------
 2 files changed, 59 insertions(+), 33 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 35c4db2d..61d10b4d 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -28,6 +28,19 @@ gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
 
 
+function status_check(){
+    last_status=$1   # 上个阶段的退出码
+    run_model=$2
+    run_command=$3
+    save_log=$4
+    echo ${case3}
+    if [ $last_status -eq 0 ]; then
+        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+    else
+        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+    fi
+}
+
 for train_model in ${train_model_list[*]}; do 
     if [ ${train_model} = "det" ];then
         model_name="det"
@@ -42,7 +55,7 @@ for train_model in ${train_model_list[*]}; do
     # eval 
     for slim_trainer in ${slim_trainer_list[*]}; do 
         if [ ${slim_trainer} = "norm" ]; then
-            if [ ${model_name} = "model_name" ]; then
+            if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_infer"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
             else 
@@ -50,7 +63,7 @@ for train_model in ${train_model_list[*]}; do
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
             fi 
         elif [ ${slim_trainer} = "quant" ]; then
-            if [ ${model_name} = "model_name" ]; then
+            if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_quant_infer"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar
             else
@@ -58,7 +71,7 @@ for train_model in ${train_model_list[*]}; do
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar
             fi 
         elif [ ${slim_trainer} = "distill" ]; then
-            if [ ${model_name} = "model_name" ]; then
+            if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_distill_infer"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_distill_train.tar
             else
@@ -66,7 +79,7 @@ for train_model in ${train_model_list[*]}; do
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar
             fi 
         elif [ ${slim_trainer} = "prune" ]; then
-            if [ ${model_name} = "model_name" ]; then
+            if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_prune_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar
             else
@@ -74,9 +87,15 @@ for train_model in ${train_model_list[*]}; do
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
             fi
         fi
+    save_log_path="${log_path}/${eval_model_name}"
+    command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}"
+    ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}
+    status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
+
+    command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
+    ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}
+    status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
 
-    echo ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${log_path}/${model_name}
-    echo ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer
     if [ $? -eq 0 ]; then
         echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
     else
@@ -99,8 +118,10 @@ for train_model in ${train_model_list[*]}; do
             for use_mkldnn in ${use_mkldnn_list[*]}; do
                 for threads in ${cpu_threads_list[*]}; do
                     for rec_batch_size in ${rec_batch_size_list[*]}; do    
-                        echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                        # ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  2>&1 | tee ${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
+                        save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
+                        command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
+                        ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
+                        status_check $? "${trainer}" "${command}" "${save_log_path}"
                     done
                 done
             done
@@ -111,8 +132,10 @@ for train_model in ${train_model_list[*]}; do
                         continue
                     fi
                     for rec_batch_size in ${rec_batch_size_list[*]}; do
-                        # echo "${model_name}  ${det_model_dir} ${rec_model_dir}, use_trt: ${use_trt}   use_fp16: ${use_fp16}"
-                        echo ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log
+                        save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
+                        command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
+                        ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                        status_check $? "${trainer}" "${command}" "${save_log_path}"
                     done
                 done
             done
diff --git a/test/test.sh b/test/test.sh
index b43b1a61..cb894f26 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -21,7 +21,7 @@ elif [ ${MODE} = "whole_train_infer" ];then
     rm -rf ./train_data/icdar2015
     wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar
     cd ./train_data/ && tar xf icdar2015.tar && cd ../
-    epoch=300
+    epoch=500
     eval_batch_step=200
 else
     echo "Do Nothing"
@@ -55,9 +55,19 @@ rec_batch_size_list=$(func_parser "${lines[9]}")
 gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
 img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
-# train superparameters
-#epoch=$(func_parser "${lines[12]}")
-#checkpoints=$(func_parser "${lines[13]}")
+
+function status_check(){
+    last_status=$1   # 上个阶段的退出码
+    run_model=$2
+    run_command=$3
+    save_log=$4
+    echo ${case3}
+    if [ $last_status -eq 0 ]; then
+        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+    else
+        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+    fi
+}
 
 
 for train_model in ${train_model_list[*]}; do 
@@ -101,17 +111,14 @@ for train_model in ${train_model_list[*]}; do
                     trainer="tools/train.py"
                     export_model="tools/export_model.py"
                 fi
-                # dataset="Train.dataset.data_dir=${train_dir}  Train.dataset.label_file_list=${train_label_file}  Eval.dataset.data_dir=${eval_dir} Eval.dataset.label_file_list=${eval_label_file}"
                 save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
-                
+                command="${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}"
                 ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
+                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
+
+                command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
                 ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
-                if [ $? -eq 0 ]; then
-                    echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
-                else
-                    cat ${save_log}/train.log
-                    echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${save_log}/train.log
-                fi
+                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
                
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
@@ -129,15 +136,10 @@ for train_model in ${train_model_list[*]}; do
                         for use_mkldnn in ${use_mkldnn_list[*]}; do
                             for threads in ${cpu_threads_list[*]}; do
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do    
-                                    echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                                    if [ $? -eq 0 ]; then
-                                        echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${log_path}${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                                    else
-                                        cat ${log_path}${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                                        echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${log_path}${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log
-                                    fi
-
+                                    save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
+                                    command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
+                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
+                                    status_check $? "${inference}" "${command}" "${save_log}"
                                 done
                             done
                         done
@@ -148,8 +150,9 @@ for train_model in ${train_model_list[*]}; do
                                     continue
                                 fi
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do
-                                    # echo "${model_name}  ${det_model_dir} ${rec_model_dir}, use_trt: ${use_trt}   use_fp16: ${use_fp16}"
-                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log
+                                    save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
+                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                                    status_check $? "${inference}" "${command}" "${save_log}"
                                 done
                             done
                         done

From 4a179f5fc0f8c375828b285d79dd5427f9afa263 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Tue, 8 Jun 2021 21:24:43 +0800
Subject: [PATCH 12/34] refine status check

---
 test/infer.sh | 2 +-
 test/test.sh  | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 61d10b4d..4c49dde7 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -29,7 +29,7 @@ gpu_precision_list=$(func_parser "${lines[11]}")
 
 
 function status_check(){
-    last_status=$1   # 上个阶段的退出码
+    last_status=$1   # the exit code
     run_model=$2
     run_command=$3
     save_log=$4
diff --git a/test/test.sh b/test/test.sh
index cb894f26..d24f2795 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -57,7 +57,7 @@ gpu_precision_list=$(func_parser "${lines[11]}")
 img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
 
 function status_check(){
-    last_status=$1   # 上个阶段的退出码
+    last_status=$1   # the exit code
     run_model=$2
     run_command=$3
     save_log=$4
@@ -92,7 +92,7 @@ for train_model in ${train_model_list[*]}; do
         else
             launch="-m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu}"
         fi
-        # echo "model_name: ${model_name}  yml_file: ${yml_file}   launch: ${launch}   gpu: ${gpu}" 
+
         for auto_cast in ${auto_cast_list[*]}; do 
             for slim_trainer in ${slim_trainer_list[*]}; do 
                 if [ ${slim_trainer} = "norm" ]; then

From 04fb6148e15141387a881714143af58fc0305aea Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 10:12:32 +0800
Subject: [PATCH 13/34] add log_path to params.txt

---
 test/params.txt |  4 ++--
 test/test.sh    | 34 ++++++++++++++++++++++------------
 2 files changed, 24 insertions(+), 14 deletions(-)

diff --git a/test/params.txt b/test/params.txt
index 3fe857d3..e94b21e7 100644
--- a/test/params.txt
+++ b/test/params.txt
@@ -4,7 +4,7 @@ auto_cast_list: False
 trainer_list: norm|quant|prune
 python: python3.7
 
-inference: python|C++
+inference: python
 devices: cpu|gpu
 use_mkldnn_list: True|False
 cpu_threads_list: 1|6
@@ -12,4 +12,4 @@ rec_batch_size_list: 1|6
 gpu_trt_list: True|False
 gpu_precision_list: fp32|fp16|int8
 
-
+log_path: ./output
diff --git a/test/test.sh b/test/test.sh
index d24f2795..a7bb76f3 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -8,11 +8,12 @@ FILENAME=$1
 MODE=$2
 # prepare pretrained weights and dataset 
 wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
+
 if [ ${MODE} = "lite_train_infer" ];then
     # pretrain lite train data
     rm -rf ./train_data/icdar2015
     wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
-    cd ./train_data/ && tar xf icdar2015_lite.tar && 
+    cd ./train_data/ && tar xf icdar2015_lite.tar
     ln -s ./icdar2015_lite ./icdar2015
     cd ../
     epoch=10
@@ -24,9 +25,17 @@ elif [ ${MODE} = "whole_train_infer" ];then
     epoch=500
     eval_batch_step=200
 else
-    echo "Do Nothing"
+    rm -rf ./train_data/icdar2015
+    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_infer.tar
+    cd ./train_data/ && tar xf icdar2015_infer.tar
+    ln -s ./icdar2015_infer ./icdar2015
+    cd ../
+    epoch=10
+    eval_batch_step=10
 fi
 
+img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
+
 
 dataline=$(cat ${FILENAME})
 # parser params
@@ -34,7 +43,7 @@ IFS=$'\n'
 lines=(${dataline})
 function func_parser(){
     strs=$1
-    IFS=":"
+    IFS=": "
     array=(${strs})
     tmp=${array[1]}
     echo ${tmp}
@@ -54,7 +63,8 @@ cpu_threads_list=$(func_parser "${lines[8]}")
 rec_batch_size_list=$(func_parser "${lines[9]}")
 gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
-img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
+
+log_path=$(func_parser "${lines[12]}")
 
 function status_check(){
     last_status=$1   # the exit code
@@ -113,12 +123,12 @@ for train_model in ${train_model_list[*]}; do
                 fi
                 save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
                 command="${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}"
-                ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
-                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
+                echo ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
+                # status_check $? "${trainer}" "${command}" "${save_log}/train.log"
 
                 command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
-                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
-                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
+                echo ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
+                # status_check $? "${trainer}" "${command}" "${save_log}/train.log"
                
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
@@ -138,8 +148,8 @@ for train_model in ${train_model_list[*]}; do
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do    
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
                                     command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
-                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
-                                    status_check $? "${inference}" "${command}" "${save_log}"
+                                    echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
+                                    # status_check $? "${inference}" "${command}" "${save_log}"
                                 done
                             done
                         done
@@ -151,8 +161,8 @@ for train_model in ${train_model_list[*]}; do
                                 fi
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
-                                    status_check $? "${inference}" "${command}" "${save_log}"
+                                    echo ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                                    # status_check $? "${inference}" "${command}" "${save_log}"
                                 done
                             done
                         done

From 1203276fbd0cfdbcba8a40c00be8639915a96049 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 11:22:29 +0800
Subject: [PATCH 14/34] add env, add infer det imgs, add infer_gpu_id to
 params.txt

---
 test/infer.sh   | 17 ++++++++++-------
 test/params.txt |  2 +-
 test/test.sh    | 30 ++++++++++++++++++------------
 3 files changed, 29 insertions(+), 20 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 4c49dde7..db8b788c 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -14,8 +14,6 @@ function func_parser(){
 IFS=$'\n'
 # The training params
 train_model_list=$(func_parser "${lines[0]}")
-gpu_list=$(func_parser "${lines[1]}")
-auto_cast_list=$(func_parser "${lines[2]}")
 slim_trainer_list=$(func_parser "${lines[3]}")
 python=$(func_parser "${lines[4]}")
 # inference params
@@ -27,13 +25,15 @@ rec_batch_size_list=$(func_parser "${lines[9]}")
 gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
 
+infer_gpu_id=$(func_parser "${lines[12]}")
+log_path=$(func_parser "${lines[13]}")
+
 
 function status_check(){
     last_status=$1   # the exit code
     run_model=$2
     run_command=$3
     save_log=$4
-    echo ${case3}
     if [ $last_status -eq 0 ]; then
         echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${save_log}
     else
@@ -45,11 +45,13 @@ for train_model in ${train_model_list[*]}; do
     if [ ${train_model} = "det" ];then
         model_name="det"
         yml_file="configs/det/det_mv3_db.yml"
-        img_dir=""
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar && tar xf ./inference/ch_det_data_50.tar 
+        img_dir="./inference/ch_det_data_50/"
     elif [ ${train_model} = "rec" ];then
         model_name="rec"
         yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
-        img_dir=""
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar && tar xf ./inference/ch_rec_data_200.tar 
+        img_dir="./inference/ch_rec_data_200/"
     fi
 
     # eval 
@@ -126,6 +128,7 @@ for train_model in ${train_model_list[*]}; do
                 done
             done
         else 
+            env="CUDA_VISIBLE_DEVICES=${infer_gpu_id}"
             for use_trt in ${gpu_trt_list[*]}; do
                 for precision in ${gpu_precision_list[*]}; do
                     if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
@@ -133,8 +136,8 @@ for train_model in ${train_model_list[*]}; do
                     fi
                     for rec_batch_size in ${rec_batch_size_list[*]}; do
                         save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                        command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
-                        ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                        command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
+                        ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
                         status_check $? "${trainer}" "${command}" "${save_log_path}"
                     done
                 done
diff --git a/test/params.txt b/test/params.txt
index e94b21e7..ff1cc008 100644
--- a/test/params.txt
+++ b/test/params.txt
@@ -11,5 +11,5 @@ cpu_threads_list: 1|6
 rec_batch_size_list: 1|6
 gpu_trt_list: True|False
 gpu_precision_list: fp32|fp16|int8
-
+infer_gpu_id: 0
 log_path: ./output
diff --git a/test/test.sh b/test/test.sh
index a7bb76f3..cc1aee92 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -64,14 +64,13 @@ rec_batch_size_list=$(func_parser "${lines[9]}")
 gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
 
-log_path=$(func_parser "${lines[12]}")
+log_path=$(func_parser "${lines[13]}")
 
 function status_check(){
     last_status=$1   # the exit code
     run_model=$2
     run_command=$3
     save_log=$4
-    echo ${case3}
     if [ $last_status -eq 0 ]; then
         echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${save_log}
     else
@@ -97,10 +96,16 @@ for train_model in ${train_model_list[*]}; do
         if [ ${gpu} = "-1" ];then
             lanuch=""
             use_gpu=False
+            env=""
         elif [ ${#gpu} -le 1 ];then
             launch=""
+            env="CUDA_VISIBLE_DEVICES=${gpu}"
         else
             launch="-m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu}"
+            IFS=","
+            array=(${gpu})
+            env="CUDA_VISIBLE_DEVICES=${array[0]}"
+            IFS="|"
         fi
 
         for auto_cast in ${auto_cast_list[*]}; do 
@@ -122,13 +127,13 @@ for train_model in ${train_model_list[*]}; do
                     export_model="tools/export_model.py"
                 fi
                 save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
-                command="${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}"
-                echo ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
-                # status_check $? "${trainer}" "${command}" "${save_log}/train.log"
+                command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}"
+                ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
+                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
 
-                command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
-                echo ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
-                # status_check $? "${trainer}" "${command}" "${save_log}/train.log"
+                command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
+                ${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
+                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
                
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
@@ -148,8 +153,8 @@ for train_model in ${train_model_list[*]}; do
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do    
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
                                     command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
-                                    echo ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
-                                    # status_check $? "${inference}" "${command}" "${save_log}"
+                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
+                                    status_check $? "${inference}" "${command}" "${save_log}"
                                 done
                             done
                         done
@@ -161,8 +166,9 @@ for train_model in ${train_model_list[*]}; do
                                 fi
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                                    echo ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
-                                    # status_check $? "${inference}" "${command}" "${save_log}"
+                                    command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
+                                    ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                                    status_check $? "${inference}" "${command}" "${save_log}"
                                 done
                             done
                         done

From 0f84fc1e5a666273ddd1c85fcc72c46eccef4f85 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 11:59:04 +0800
Subject: [PATCH 15/34] fix ci error

---
 test/infer.sh   | 121 +++++++++++++++++++++++++-----------------------
 test/params.txt |   2 +-
 test/test.sh    |  10 ++--
 3 files changed, 68 insertions(+), 65 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index db8b788c..18aab1f1 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -1,12 +1,12 @@
 #!/bin/bash
-
+FILENAME=$1
 dataline=$(cat ${FILENAME})
 # parser params
 IFS=$'\n'
 lines=(${dataline})
 function func_parser(){
     strs=$1
-    IFS=":"
+    IFS=": "
     array=(${strs})
     tmp=${array[1]}
     echo ${tmp}
@@ -17,7 +17,7 @@ train_model_list=$(func_parser "${lines[0]}")
 slim_trainer_list=$(func_parser "${lines[3]}")
 python=$(func_parser "${lines[4]}")
 # inference params
-inference=$(func_parser "${lines[5]}")
+# inference=$(func_parser "${lines[5]}")
 devices=$(func_parser "${lines[6]}")
 use_mkldnn_list=$(func_parser "${lines[7]}")
 cpu_threads_list=$(func_parser "${lines[8]}")
@@ -40,14 +40,15 @@ function status_check(){
         echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${save_log}
     fi
 }
-
+IFS='|'
 for train_model in ${train_model_list[*]}; do 
-    if [ ${train_model} = "det" ];then
+    if [ ${train_model} = "ocr_det" ];then
         model_name="det"
         yml_file="configs/det/det_mv3_db.yml"
-        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar && tar xf ./inference/ch_det_data_50.tar 
+        # wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar 
+        tar xf ./inference/ch_det_data_50.tar 
         img_dir="./inference/ch_det_data_50/"
-    elif [ ${train_model} = "rec" ];then
+    elif [ ${train_model} = "ocr_rec" ];then
         model_name="rec"
         yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar && tar xf ./inference/ch_rec_data_200.tar 
@@ -71,7 +72,7 @@ for train_model in ${train_model_list[*]}; do
             else
                 eval_model_name="ch_ppocr_mobile_v2.0_rec_quant_infer"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar
-            fi 
+            fi
         elif [ ${slim_trainer} = "distill" ]; then
             if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_distill_infer"
@@ -89,59 +90,61 @@ for train_model in ${train_model_list[*]}; do
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
             fi
         fi
-    save_log_path="${log_path}/${eval_model_name}"
-    command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}"
-    ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}
-    status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
 
-    command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
-    ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}
-    status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
+        save_log_path="${log_path}/${eval_model_name}"
+        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}"
+        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}
+        status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
 
-    if [ $? -eq 0 ]; then
-        echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
-    else
-        cat ${save_log}/train.log
-        echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${save_log}/train.log
-    fi
-    if [ "${model_name}" = "det" ]; then 
-        export rec_batch_size_list=( "1" )
-        inference="tools/infer/predict_det.py"
-        det_model_dir=${log_path}/${eval_model_name}_infer
-        rec_model_dir=""
-    elif [ "${model_name}" = "rec" ]; then
-        inference="tools/infer/predict_rec.py"
-        rec_model_dir=${log_path}/${eval_model_name}_infer
-        det_model_dir=""
-    fi
-    # inference 
-    for device in ${devices[*]}; do 
-        if [ ${device} = "cpu" ]; then
-            for use_mkldnn in ${use_mkldnn_list[*]}; do
-                for threads in ${cpu_threads_list[*]}; do
-                    for rec_batch_size in ${rec_batch_size_list[*]}; do    
-                        save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
-                        command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
-                        ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
-                        status_check $? "${trainer}" "${command}" "${save_log_path}"
-                    done
-                done
-            done
-        else 
-            env="CUDA_VISIBLE_DEVICES=${infer_gpu_id}"
-            for use_trt in ${gpu_trt_list[*]}; do
-                for precision in ${gpu_precision_list[*]}; do
-                    if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
-                        continue
-                    fi
-                    for rec_batch_size in ${rec_batch_size_list[*]}; do
-                        save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                        command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
-                        ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
-                        status_check $? "${trainer}" "${command}" "${save_log_path}"
-                    done
-                done
-            done
+        command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
+        ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
+        status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
+
+        if [ $? -eq 0 ]; then
+            echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
+        else
+            cat ${save_log}/train.log
+            echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${save_log}/train.log
         fi
+        if [ "${model_name}" = "det" ]; then 
+            export rec_batch_size_list=( "1" )
+            inference="tools/infer/predict_det.py"
+            det_model_dir=${log_path}/${eval_model_name}_infer
+            rec_model_dir=""
+        elif [ "${model_name}" = "rec" ]; then
+            inference="tools/infer/predict_rec.py"
+            rec_model_dir=${log_path}/${eval_model_name}_infer
+            det_model_dir=""
+        fi
+        # inference 
+        for device in ${devices[*]}; do 
+            if [ ${device} = "cpu" ]; then
+                for use_mkldnn in ${use_mkldnn_list[*]}; do
+                    for threads in ${cpu_threads_list[*]}; do
+                        for rec_batch_size in ${rec_batch_size_list[*]}; do    
+                            save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
+                            command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
+                            ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
+                            status_check $? "${trainer}" "${command}" "${save_log_path}"
+                        done
+                    done
+                done
+            else 
+                env="CUDA_VISIBLE_DEVICES=${infer_gpu_id}"
+                for use_trt in ${gpu_trt_list[*]}; do
+                    for precision in ${gpu_precision_list[*]}; do
+                        if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
+                            continue
+                        fi
+                        for rec_batch_size in ${rec_batch_size_list[*]}; do
+                            save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
+                            command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
+                            ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                            status_check $? "${trainer}" "${command}" "${save_log_path}"
+                        done
+                    done
+                done
+            fi
+        done
     done
 done
diff --git a/test/params.txt b/test/params.txt
index ff1cc008..93c5ccde 100644
--- a/test/params.txt
+++ b/test/params.txt
@@ -1,7 +1,7 @@
 train_model_list: ocr_det
 gpu_list: -1|0|0,1
 auto_cast_list: False
-trainer_list: norm|quant|prune
+trainer_list: norm|quant
 python: python3.7
 
 inference: python
diff --git a/test/test.sh b/test/test.sh
index cc1aee92..24a68b26 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -78,7 +78,7 @@ function status_check(){
     fi
 }
 
-
+IFS="|"
 for train_model in ${train_model_list[*]}; do 
     if [ ${train_model} = "ocr_det" ];then
         model_name="det"
@@ -107,7 +107,7 @@ for train_model in ${train_model_list[*]}; do
             env="CUDA_VISIBLE_DEVICES=${array[0]}"
             IFS="|"
         fi
-
+        IFS="|"
         for auto_cast in ${auto_cast_list[*]}; do 
             for slim_trainer in ${slim_trainer_list[*]}; do 
                 if [ ${slim_trainer} = "norm" ]; then
@@ -126,13 +126,13 @@ for train_model in ${train_model_list[*]}; do
                     trainer="tools/train.py"
                     export_model="tools/export_model.py"
                 fi
-                save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
+                save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
                 command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}"
                 ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
                 status_check $? "${trainer}" "${command}" "${save_log}/train.log"
 
-                command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
-                ${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
+                command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
+                ${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
                 status_check $? "${trainer}" "${command}" "${save_log}/train.log"
                
                 if [ "${model_name}" = "det" ]; then 

From 4b56069d84138096817bcf30460f7ee0ecc63d1c Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 12:53:22 +0800
Subject: [PATCH 16/34] fix bug

---
 test/infer.sh | 35 ++++++++++++++++++++++-------------
 test/test.sh  |  4 ++--
 2 files changed, 24 insertions(+), 15 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 18aab1f1..30b91df7 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -45,13 +45,14 @@ for train_model in ${train_model_list[*]}; do
     if [ ${train_model} = "ocr_det" ];then
         model_name="det"
         yml_file="configs/det/det_mv3_db.yml"
-        # wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar 
-        tar xf ./inference/ch_det_data_50.tar 
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
+        cd ./inference && tar xf ch_det_data_50.tar && cd ../
         img_dir="./inference/ch_det_data_50/"
     elif [ ${train_model} = "ocr_rec" ];then
         model_name="rec"
         yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
-        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar && tar xf ./inference/ch_rec_data_200.tar 
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar 
+        cd ./inference && tar xf ch_rec_data_200.tar  && cd ../
         img_dir="./inference/ch_rec_data_200/"
     fi
 
@@ -59,45 +60,53 @@ for train_model in ${train_model_list[*]}; do
     for slim_trainer in ${slim_trainer_list[*]}; do 
         if [ ${slim_trainer} = "norm" ]; then
             if [ ${model_name} = "det" ]; then
-                eval_model_name="ch_ppocr_mobile_v2.0_det_infer"
+                eval_model_name="ch_ppocr_mobile_v2.0_det_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             else 
-                eval_model_name="ch_ppocr_mobile_v2.0_rec_infer"
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             fi 
         elif [ ${slim_trainer} = "quant" ]; then
             if [ ${model_name} = "det" ]; then
-                eval_model_name="ch_ppocr_mobile_v2.0_det_quant_infer"
+                eval_model_name="ch_ppocr_mobile_v2.0_det_quant_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             else
-                eval_model_name="ch_ppocr_mobile_v2.0_rec_quant_infer"
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_quant_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             fi
         elif [ ${slim_trainer} = "distill" ]; then
             if [ ${model_name} = "det" ]; then
-                eval_model_name="ch_ppocr_mobile_v2.0_det_distill_infer"
+                eval_model_name="ch_ppocr_mobile_v2.0_det_distill_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_distill_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             else
-                eval_model_name="ch_ppocr_mobile_v2.0_rec_distill_infer"
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_distill_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             fi 
         elif [ ${slim_trainer} = "prune" ]; then
             if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_prune_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             else
                 eval_model_name="ch_ppocr_mobile_v2.0_rec_prune_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             fi
         fi
 
         save_log_path="${log_path}/${eval_model_name}"
-        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}"
-        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}
+        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_model_dir=${save_log_path}"
+        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_model_dir=${save_log_path}
         status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
 
-        command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
-        ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
+        command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
+        ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
         status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
 
         if [ $? -eq 0 ]; then
diff --git a/test/test.sh b/test/test.sh
index 24a68b26..a1b711b7 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -127,8 +127,8 @@ for train_model in ${train_model_list[*]}; do
                     export_model="tools/export_model.py"
                 fi
                 save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
-                command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}"
-                ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
+                command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
+                ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
                 status_check $? "${trainer}" "${command}" "${save_log}/train.log"
 
                 command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"

From 3cdc9e53835de2fd06199e851efaea614fbef6b7 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 13:02:34 +0800
Subject: [PATCH 17/34] add pretrain to Global

---
 test/test.sh | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/test/test.sh b/test/test.sh
index a1b711b7..15a10d17 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -8,6 +8,8 @@ FILENAME=$1
 MODE=$2
 # prepare pretrained weights and dataset 
 wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
+wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar
+cd pretrain_models && tar xf det_mv3_db_v2.0_train.tar && cd ../
 
 if [ ${MODE} = "lite_train_infer" ];then
     # pretrain lite train data
@@ -107,28 +109,32 @@ for train_model in ${train_model_list[*]}; do
             env="CUDA_VISIBLE_DEVICES=${array[0]}"
             IFS="|"
         fi
-        IFS="|"
         for auto_cast in ${auto_cast_list[*]}; do 
             for slim_trainer in ${slim_trainer_list[*]}; do 
                 if [ ${slim_trainer} = "norm" ]; then
                     trainer="tools/train.py"
                     export_model="tools/export_model.py"
+                    pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
                 elif [ ${slim_trainer} = "quant" ]; then
                     trainer="deploy/slim/quantization/quant.py"
                     export_model="deploy/slim/quantization/export_model.py"
+                    pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
                 elif [ ${slim_trainer} = "prune" ]; then
                     trainer="deploy/slim/prune/sensitivity_anal.py"
                     export_model="deploy/slim/prune/export_prune_model.py"
+                    pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
                 elif [ ${slim_trainer} = "distill" ]; then
                     trainer="deploy/slim/distill/train_dml.py"
                     export_model="deploy/slim/distill/export_distill_model.py"
+                    pretrain=""
                 else
                     trainer="tools/train.py"
                     export_model="tools/export_model.py"
+                    pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
                 fi
                 save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
-                command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
-                ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
+                command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
+                ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
                 status_check $? "${trainer}" "${command}" "${save_log}/train.log"
 
                 command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"

From 90454c767eb480523404c1a22873ff4d966800f5 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 13:14:00 +0800
Subject: [PATCH 18/34] rename params.txt

---
 test/{params.txt => paddleocr_ci_params.txt} | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename test/{params.txt => paddleocr_ci_params.txt} (100%)

diff --git a/test/params.txt b/test/paddleocr_ci_params.txt
similarity index 100%
rename from test/params.txt
rename to test/paddleocr_ci_params.txt

From 9372741adf2d3d3997025b2522287ea18436eb14 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 14:48:56 +0800
Subject: [PATCH 19/34] return status to log_path/results.log

---
 test/infer.sh |  9 +++++----
 test/test.sh  | 11 ++++++-----
 2 files changed, 11 insertions(+), 9 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 30b91df7..9db893d3 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -27,6 +27,7 @@ gpu_precision_list=$(func_parser "${lines[11]}")
 
 infer_gpu_id=$(func_parser "${lines[12]}")
 log_path=$(func_parser "${lines[13]}")
+status_log="${log_path}/result.log"
 
 
 function status_check(){
@@ -103,11 +104,11 @@ for train_model in ${train_model_list[*]}; do
         save_log_path="${log_path}/${eval_model_name}"
         command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_model_dir=${save_log_path}"
         ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_model_dir=${save_log_path}
-        status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
+        status_check $? "${trainer}" "${command}" "${status_log}"
 
         command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
         ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
-        status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
+        status_check $? "${trainer}" "${command}" "${status_log}"
 
         if [ $? -eq 0 ]; then
             echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
@@ -134,7 +135,7 @@ for train_model in ${train_model_list[*]}; do
                             save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
                             command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
                             ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
-                            status_check $? "${trainer}" "${command}" "${save_log_path}"
+                            status_check $? "${trainer}" "${command}" "${status_log}"
                         done
                     done
                 done
@@ -149,7 +150,7 @@ for train_model in ${train_model_list[*]}; do
                             save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
                             command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
                             ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
-                            status_check $? "${trainer}" "${command}" "${save_log_path}"
+                            status_check $? "${trainer}" "${command}" "${status_log}"
                         done
                     done
                 done
diff --git a/test/test.sh b/test/test.sh
index 15a10d17..fdc54095 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -1,6 +1,6 @@
 #!/bin/bash 
 # Usage:
-# bash test/test.sh ./test/params.txt 'lite_train_infer'
+# bash test/test.sh ./test/paddleocr_ci_params.txt 'lite_train_infer'
 
 FILENAME=$1
 
@@ -67,6 +67,7 @@ gpu_trt_list=$(func_parser "${lines[10]}")
 gpu_precision_list=$(func_parser "${lines[11]}")
 
 log_path=$(func_parser "${lines[13]}")
+status_log="${log_path}/result.log"
 
 function status_check(){
     last_status=$1   # the exit code
@@ -135,11 +136,11 @@ for train_model in ${train_model_list[*]}; do
                 save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
                 command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
                 ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
-                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
+                status_check $? "${trainer}" "${command}" "${status_log}"
 
                 command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
                 ${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
-                status_check $? "${trainer}" "${command}" "${save_log}/train.log"
+                status_check $? "${trainer}" "${command}" "${status_log}"
                
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
@@ -160,7 +161,7 @@ for train_model in ${train_model_list[*]}; do
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
                                     command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
                                     ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
-                                    status_check $? "${inference}" "${command}" "${save_log}"
+                                    status_check $? "${inference}" "${command}" "${status_log}"
                                 done
                             done
                         done
@@ -174,7 +175,7 @@ for train_model in ${train_model_list[*]}; do
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
                                     command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
                                     ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
-                                    status_check $? "${inference}" "${command}" "${save_log}"
+                                    status_check $? "${inference}" "${command}" "${status_log}"
                                 done
                             done
                         done

From 95ae3c19d2af70405177c1b64b93b1d3196037db Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 15:38:54 +0800
Subject: [PATCH 20/34] rename save_log in func status_check

---
 test/test.sh | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/test/test.sh b/test/test.sh
index fdc54095..30fb42a3 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -73,11 +73,11 @@ function status_check(){
     last_status=$1   # the exit code
     run_model=$2
     run_command=$3
-    save_log=$4
+    run_log=$4
     if [ $last_status -eq 0 ]; then
-        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${run_log}
     else
-        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${run_log}
     fi
 }
 

From ef0467884ee44e886444fecd3743fc9d6a0ec504 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 15:47:46 +0800
Subject: [PATCH 21/34] rename save_log

---
 test/infer.sh | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 9db893d3..219ba547 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -34,11 +34,11 @@ function status_check(){
     last_status=$1   # the exit code
     run_model=$2
     run_command=$3
-    save_log=$4
+    run_log=$4
     if [ $last_status -eq 0 ]; then
-        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${run_log}
     else
-        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${save_log}
+        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${run_log}
     fi
 }
 IFS='|'

From 58ca7639fc1d7ae0266acf39ab590c131f39414c Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 16:14:03 +0800
Subject: [PATCH 22/34] fix eval bug and inference path

---
 test/infer.sh | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 219ba547..49f0c4f7 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -48,7 +48,7 @@ for train_model in ${train_model_list[*]}; do
         yml_file="configs/det/det_mv3_db.yml"
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
         cd ./inference && tar xf ch_det_data_50.tar && cd ../
-        img_dir="./inference/ch_det_data_50/"
+        img_dir="./inference/ch_det_data_50/all-sum-50"
     elif [ ${train_model} = "ocr_rec" ];then
         model_name="rec"
         yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
@@ -102,12 +102,13 @@ for train_model in ${train_model_list[*]}; do
         fi
 
         save_log_path="${log_path}/${eval_model_name}"
-        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_model_dir=${save_log_path}"
-        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_model_dir=${save_log_path}
+        eval_img="Eval.dataset.data_dir=./inference/ch_det_data_50/ Eval.dataset.label_file_list=./inference/ch_det_data_50/test_gt_50.txt"
+        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} ${eval_img}"
+        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='./inference/${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} ${eval_img}
         status_check $? "${trainer}" "${command}" "${status_log}"
 
         command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
-        ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
+        ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="./inference/${eval_model_name}/best_accuracy" Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
         status_check $? "${trainer}" "${command}" "${status_log}"
 
         if [ $? -eq 0 ]; then
@@ -119,11 +120,11 @@ for train_model in ${train_model_list[*]}; do
         if [ "${model_name}" = "det" ]; then 
             export rec_batch_size_list=( "1" )
             inference="tools/infer/predict_det.py"
-            det_model_dir=${log_path}/${eval_model_name}_infer
+            det_model_dir="./inference/${log_path}/${eval_model_name}_infer"
             rec_model_dir=""
         elif [ "${model_name}" = "rec" ]; then
             inference="tools/infer/predict_rec.py"
-            rec_model_dir=${log_path}/${eval_model_name}_infer
+            rec_model_dir="./inference/${log_path}/${eval_model_name}_infer"
             det_model_dir=""
         fi
         # inference 

From a4fe159bc07acfc4c3d277448f9103599a54391b Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 09:42:41 +0000
Subject: [PATCH 23/34] fix infer bug

---
 test/infer.sh | 23 ++++++++++++-----------
 1 file changed, 12 insertions(+), 11 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index 49f0c4f7..324c346b 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -45,10 +45,12 @@ IFS='|'
 for train_model in ${train_model_list[*]}; do 
     if [ ${train_model} = "ocr_det" ];then
         model_name="det"
-        yml_file="configs/det/det_mv3_db.yml"
+        yml_file="configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml"
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
         cd ./inference && tar xf ch_det_data_50.tar && cd ../
-        img_dir="./inference/ch_det_data_50/all-sum-50"
+        img_dir="./inference/ch_det_data_50/all-sum-510"
+        data_dir=./inference/ch_det_data_50/
+        data_label_file=[./inference/ch_det_data_50/test_gt_50.txt]
     elif [ ${train_model} = "ocr_rec" ];then
         model_name="rec"
         yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
@@ -102,9 +104,8 @@ for train_model in ${train_model_list[*]}; do
         fi
 
         save_log_path="${log_path}/${eval_model_name}"
-        eval_img="Eval.dataset.data_dir=./inference/ch_det_data_50/ Eval.dataset.label_file_list=./inference/ch_det_data_50/test_gt_50.txt"
-        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} ${eval_img}"
-        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='./inference/${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} ${eval_img}
+        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='./inference/${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} Eval.dataset.data_dir=${data_dir}  Eval.dataset.label_file_list=${data_label_file}"
+        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=./inference/${eval_model_name}/best_accuracy Global.save_model_dir=${save_log_path} Eval.dataset.data_dir=${data_dir}  Eval.dataset.label_file_list=${data_label_file}
         status_check $? "${trainer}" "${command}" "${status_log}"
 
         command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
@@ -120,11 +121,11 @@ for train_model in ${train_model_list[*]}; do
         if [ "${model_name}" = "det" ]; then 
             export rec_batch_size_list=( "1" )
             inference="tools/infer/predict_det.py"
-            det_model_dir="./inference/${log_path}/${eval_model_name}_infer"
+            det_model_dir="${log_path}/${eval_model_name}_infer"
             rec_model_dir=""
         elif [ "${model_name}" = "rec" ]; then
             inference="tools/infer/predict_rec.py"
-            rec_model_dir="./inference/${log_path}/${eval_model_name}_infer"
+            rec_model_dir="${log_path}/${eval_model_name}_infer"
             det_model_dir=""
         fi
         # inference 
@@ -140,8 +141,8 @@ for train_model in ${train_model_list[*]}; do
                         done
                     done
                 done
-            else 
-                env="CUDA_VISIBLE_DEVICES=${infer_gpu_id}"
+            else
+                # env="export CUDA_VISIBLE_DEVICES=${infer_gpu_id}"
                 for use_trt in ${gpu_trt_list[*]}; do
                     for precision in ${gpu_precision_list[*]}; do
                         if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
@@ -149,8 +150,8 @@ for train_model in ${train_model_list[*]}; do
                         fi
                         for rec_batch_size in ${rec_batch_size_list[*]}; do
                             save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                            command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
-                            ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                            command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
+                            ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
                             status_check $? "${trainer}" "${command}" "${status_log}"
                         done
                     done

From b5aa9bdea17c6b4498efe0ed7fde72f572942428 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 09:48:45 +0000
Subject: [PATCH 24/34] delete env

---
 test/test.sh | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/test/test.sh b/test/test.sh
index 30fb42a3..df8dabdb 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -134,12 +134,12 @@ for train_model in ${train_model_list[*]}; do
                     pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
                 fi
                 save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
-                command="${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
-                ${env} ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
+                command="${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
+                ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
                 status_check $? "${trainer}" "${command}" "${status_log}"
 
-                command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
-                ${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
+                command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
+                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
                 status_check $? "${trainer}" "${command}" "${status_log}"
                
                 if [ "${model_name}" = "det" ]; then 
@@ -173,8 +173,8 @@ for train_model in ${train_model_list[*]}; do
                                 fi
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                                    command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
-                                    ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                                    command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
+                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
                                     status_check $? "${inference}" "${command}" "${status_log}"
                                 done
                             done

From f3efa9be6bae30fd836d7e6cc8c2482ba6708a1b Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 10:03:27 +0000
Subject: [PATCH 25/34] fix test.sh bug

---
 test/test.sh | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/test/test.sh b/test/test.sh
index df8dabdb..cc87c772 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -138,18 +138,18 @@ for train_model in ${train_model_list[*]}; do
                 ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
                 status_check $? "${trainer}" "${command}" "${status_log}"
 
-                command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
-                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log} 
+                command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}_infer/ Global.save_model_dir=${save_log}"
+                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}_infer/ Global.save_model_dir=${save_log} 
                 status_check $? "${trainer}" "${command}" "${status_log}"
                
                 if [ "${model_name}" = "det" ]; then 
                     export rec_batch_size_list=( "1" )
                     inference="tools/infer/predict_det.py"
-                    det_model_dir=${save_log}/export_inference/
+                    det_model_dir=${save_log}_infer
                     rec_model_dir=""
                 elif [ "${model_name}" = "rec" ]; then
                     inference="tools/infer/predict_rec.py"
-                    rec_model_dir=${save_log}/export_inference/
+                    rec_model_dir=${save_log}_infer
                     det_model_dir=""
                 fi
                 # inference 
@@ -159,8 +159,8 @@ for train_model in ${train_model_list[*]}; do
                             for threads in ${cpu_threads_list[*]}; do
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do    
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
-                                    command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
-                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
+                                    command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
+                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
                                     status_check $? "${inference}" "${command}" "${status_log}"
                                 done
                             done
@@ -173,8 +173,8 @@ for train_model in ${train_model_list[*]}; do
                                 fi
                                 for rec_batch_size in ${rec_batch_size_list[*]}; do
                                     save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                                    command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
-                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${save_log}/export_inference/ --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
+                                    command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
+                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
                                     status_check $? "${inference}" "${command}" "${status_log}"
                                 done
                             done

From e0d1779faee5e79e5c60df75a00348176453cf20 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Wed, 9 Jun 2021 11:27:36 +0000
Subject: [PATCH 26/34] add requirments

---
 test/infer.sh | 5 +++++
 test/test.sh  | 5 +++++
 2 files changed, 10 insertions(+)

diff --git a/test/infer.sh b/test/infer.sh
index 324c346b..eb70cafb 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -29,6 +29,11 @@ infer_gpu_id=$(func_parser "${lines[12]}")
 log_path=$(func_parser "${lines[13]}")
 status_log="${log_path}/result.log"
 
+# install requirments
+${python} -m pip install pynvml;
+${python} -m pip install psutil;
+${python} -m pip install GPUtil;
+
 
 function status_check(){
     last_status=$1   # the exit code
diff --git a/test/test.sh b/test/test.sh
index cc87c772..927abd19 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -69,6 +69,11 @@ gpu_precision_list=$(func_parser "${lines[11]}")
 log_path=$(func_parser "${lines[13]}")
 status_log="${log_path}/result.log"
 
+# install requirments
+${python} -m pip install pynvml;
+${python} -m pip install psutil;
+${python} -m pip install GPUtil;
+
 function status_check(){
     last_status=$1   # the exit code
     run_model=$2

From c270500a56845469c01b48474ca54fc4feb3885b Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Thu, 10 Jun 2021 14:19:52 +0800
Subject: [PATCH 27/34] delete launch

---
 test/test.sh | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/test/test.sh b/test/test.sh
index 927abd19..6c584810 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -102,14 +102,11 @@ for train_model in ${train_model_list[*]}; do
     for gpu in ${gpu_list[*]}; do
         use_gpu=True
         if [ ${gpu} = "-1" ];then
-            lanuch=""
             use_gpu=False
             env=""
         elif [ ${#gpu} -le 1 ];then
-            launch=""
             env="CUDA_VISIBLE_DEVICES=${gpu}"
         else
-            launch="-m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu}"
             IFS=","
             array=(${gpu})
             env="CUDA_VISIBLE_DEVICES=${array[0]}"
@@ -139,8 +136,13 @@ for train_model in ${train_model_list[*]}; do
                     pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
                 fi
                 save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
-                command="${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
-                ${python}  ${launch}  ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
+                if [ ${#gpu} -le 2 ];then
+                    command="${python} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
+                    ${python} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
+                else 
+                    command="${python} -m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
+                    ${python} -m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
+                fi
                 status_check $? "${trainer}" "${command}" "${status_log}"
 
                 command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}_infer/ Global.save_model_dir=${save_log}"

From fcd080851b87de0fb4c8735058e87b924ca02fb3 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Thu, 10 Jun 2021 15:49:33 +0800
Subject: [PATCH 28/34] add paddleslim

---
 test/test.sh | 1 +
 1 file changed, 1 insertion(+)

diff --git a/test/test.sh b/test/test.sh
index 6c584810..39a60033 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -73,6 +73,7 @@ status_log="${log_path}/result.log"
 ${python} -m pip install pynvml;
 ${python} -m pip install psutil;
 ${python} -m pip install GPUtil;
+${python} -m pip install paddlesim==2.0.0
 
 function status_check(){
     last_status=$1   # the exit code

From 868d3062ab012d980254327e5b0d45a7423d8883 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Thu, 10 Jun 2021 15:53:02 +0800
Subject: [PATCH 29/34] support download sen.pickle

---
 test/test.sh | 1 +
 1 file changed, 1 insertion(+)

diff --git a/test/test.sh b/test/test.sh
index 39a60033..92c61f43 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -127,6 +127,7 @@ for train_model in ${train_model_list[*]}; do
                     trainer="deploy/slim/prune/sensitivity_anal.py"
                     export_model="deploy/slim/prune/export_prune_model.py"
                     pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
+                    wget -nc -P https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/sen.pickle
                 elif [ ${slim_trainer} = "distill" ]; then
                     trainer="deploy/slim/distill/train_dml.py"
                     export_model="deploy/slim/distill/export_distill_model.py"

From 777857ec8944b180788da9f888bdff81ebbe1f78 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Thu, 17 Jun 2021 12:02:05 +0800
Subject: [PATCH 30/34] rename quant and prune

---
 test/infer.sh                | 4 ++--
 test/paddleocr_ci_params.txt | 4 ++--
 test/test.sh                 | 5 +++--
 3 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index eb70cafb..78057705 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -76,7 +76,7 @@ for train_model in ${train_model_list[*]}; do
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
                 cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             fi 
-        elif [ ${slim_trainer} = "quant" ]; then
+        elif [ ${slim_trainer} = "pact" ]; then
             if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_quant_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar
@@ -96,7 +96,7 @@ for train_model in ${train_model_list[*]}; do
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar
                 cd ./inference && tar xf ${eval_model_name}.tar && cd ../
             fi 
-        elif [ ${slim_trainer} = "prune" ]; then
+        elif [ ${slim_trainer} = "fpgm" ]; then
             if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_prune_train"
                 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar
diff --git a/test/paddleocr_ci_params.txt b/test/paddleocr_ci_params.txt
index 93c5ccde..4cd035ea 100644
--- a/test/paddleocr_ci_params.txt
+++ b/test/paddleocr_ci_params.txt
@@ -1,7 +1,7 @@
 train_model_list: ocr_det
 gpu_list: -1|0|0,1
-auto_cast_list: False
-trainer_list: norm|quant
+auto_cast_list: False|True
+trainer_list: norm|pact|fpgm
 python: python3.7
 
 inference: python
diff --git a/test/test.sh b/test/test.sh
index 92c61f43..02379baa 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -75,6 +75,7 @@ ${python} -m pip install psutil;
 ${python} -m pip install GPUtil;
 ${python} -m pip install paddlesim==2.0.0
 
+
 function status_check(){
     last_status=$1   # the exit code
     run_model=$2
@@ -119,11 +120,11 @@ for train_model in ${train_model_list[*]}; do
                     trainer="tools/train.py"
                     export_model="tools/export_model.py"
                     pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
-                elif [ ${slim_trainer} = "quant" ]; then
+                elif [ ${slim_trainer} = "pact" ]; then
                     trainer="deploy/slim/quantization/quant.py"
                     export_model="deploy/slim/quantization/export_model.py"
                     pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
-                elif [ ${slim_trainer} = "prune" ]; then
+                elif [ ${slim_trainer} = "fpgm" ]; then
                     trainer="deploy/slim/prune/sensitivity_anal.py"
                     export_model="deploy/slim/prune/export_prune_model.py"
                     pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"

From e4a51f40d4c3dd371786ac558fe9d7364060684d Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Thu, 17 Jun 2021 12:11:57 +0800
Subject: [PATCH 31/34] get cpuinfo and ip info to status_log

---
 test/infer.sh | 6 ++++++
 test/test.sh  | 6 ++++++
 2 files changed, 12 insertions(+)

diff --git a/test/infer.sh b/test/infer.sh
index 78057705..ad32ffc5 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -34,6 +34,12 @@ ${python} -m pip install pynvml;
 ${python} -m pip install psutil;
 ${python} -m pip install GPUtil;
 
+paddle_info="$(python3.7 -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
+echo -e "\033[33m $paddle_info \033[0m" | tee -a ${status_log}
+cpu_model=`cat /proc/cpuinfo | grep "model name" | awk -F ':' '{print $2}' | sort | uniq`
+echo -e "\033[33m cpu_info:$cpu_model \033[0m" | tee -a ${status_log}
+ip=`ifconfig| grep -A 1 'eth0'|grep 'inet'|awk -F ':' '{print $2}'|awk '{print $1}'`
+echo -e "\033[33m ip_info:$ip \033[0m" | tee -a ${status_log}
 
 function status_check(){
     last_status=$1   # the exit code
diff --git a/test/test.sh b/test/test.sh
index 02379baa..63686401 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -75,6 +75,12 @@ ${python} -m pip install psutil;
 ${python} -m pip install GPUtil;
 ${python} -m pip install paddlesim==2.0.0
 
+paddle_info="$(python3.7 -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
+echo -e "\033[33m $paddle_info \033[0m" | tee -a ${status_log}
+cpu_model=`cat /proc/cpuinfo | grep "model name" | awk -F ':' '{print $2}' | sort | uniq`
+echo -e "\033[33m cpu_info:$cpu_model \033[0m" | tee -a ${status_log}
+ip=`ifconfig| grep -A 1 'eth0'|grep 'inet'|awk -F ':' '{print $2}'|awk '{print $1}'`
+echo -e "\033[33m ip_info:$ip \033[0m" | tee -a ${status_log}
 
 function status_check(){
     last_status=$1   # the exit code

From 3ba4d543a60319702eb1475f6edeb7053d9b832e Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Thu, 17 Jun 2021 13:51:45 +0800
Subject: [PATCH 32/34] python3.7 to

---
 test/infer.sh | 2 +-
 test/test.sh  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/infer.sh b/test/infer.sh
index ad32ffc5..5b2c7d30 100644
--- a/test/infer.sh
+++ b/test/infer.sh
@@ -34,7 +34,7 @@ ${python} -m pip install pynvml;
 ${python} -m pip install psutil;
 ${python} -m pip install GPUtil;
 
-paddle_info="$(python3.7 -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
+paddle_info="$(${python} -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
 echo -e "\033[33m $paddle_info \033[0m" | tee -a ${status_log}
 cpu_model=`cat /proc/cpuinfo | grep "model name" | awk -F ':' '{print $2}' | sort | uniq`
 echo -e "\033[33m cpu_info:$cpu_model \033[0m" | tee -a ${status_log}
diff --git a/test/test.sh b/test/test.sh
index 63686401..5bb48ac5 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -75,7 +75,7 @@ ${python} -m pip install psutil;
 ${python} -m pip install GPUtil;
 ${python} -m pip install paddlesim==2.0.0
 
-paddle_info="$(python3.7 -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
+paddle_info="$(${python} -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
 echo -e "\033[33m $paddle_info \033[0m" | tee -a ${status_log}
 cpu_model=`cat /proc/cpuinfo | grep "model name" | awk -F ':' '{print $2}' | sort | uniq`
 echo -e "\033[33m cpu_info:$cpu_model \033[0m" | tee -a ${status_log}

From 069d994c16e313fb2af22f7697cb7e271f18bc23 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Mon, 28 Jun 2021 20:31:21 +0800
Subject: [PATCH 33/34] test to test_v5

---
 test/infer.sh                | 173 ----------------
 test/ocr_det_params.txt      |  35 ++++
 test/paddleocr_ci_params.txt |  15 --
 test/prepare.sh              | 138 +++++++++++++
 test/test.sh                 | 374 ++++++++++++++++++-----------------
 5 files changed, 369 insertions(+), 366 deletions(-)
 delete mode 100644 test/infer.sh
 create mode 100644 test/ocr_det_params.txt
 delete mode 100644 test/paddleocr_ci_params.txt
 create mode 100644 test/prepare.sh

diff --git a/test/infer.sh b/test/infer.sh
deleted file mode 100644
index 5b2c7d30..00000000
--- a/test/infer.sh
+++ /dev/null
@@ -1,173 +0,0 @@
-#!/bin/bash
-FILENAME=$1
-dataline=$(cat ${FILENAME})
-# parser params
-IFS=$'\n'
-lines=(${dataline})
-function func_parser(){
-    strs=$1
-    IFS=": "
-    array=(${strs})
-    tmp=${array[1]}
-    echo ${tmp}
-}
-IFS=$'\n'
-# The training params
-train_model_list=$(func_parser "${lines[0]}")
-slim_trainer_list=$(func_parser "${lines[3]}")
-python=$(func_parser "${lines[4]}")
-# inference params
-# inference=$(func_parser "${lines[5]}")
-devices=$(func_parser "${lines[6]}")
-use_mkldnn_list=$(func_parser "${lines[7]}")
-cpu_threads_list=$(func_parser "${lines[8]}")
-rec_batch_size_list=$(func_parser "${lines[9]}")
-gpu_trt_list=$(func_parser "${lines[10]}")
-gpu_precision_list=$(func_parser "${lines[11]}")
-
-infer_gpu_id=$(func_parser "${lines[12]}")
-log_path=$(func_parser "${lines[13]}")
-status_log="${log_path}/result.log"
-
-# install requirments
-${python} -m pip install pynvml;
-${python} -m pip install psutil;
-${python} -m pip install GPUtil;
-
-paddle_info="$(${python} -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
-echo -e "\033[33m $paddle_info \033[0m" | tee -a ${status_log}
-cpu_model=`cat /proc/cpuinfo | grep "model name" | awk -F ':' '{print $2}' | sort | uniq`
-echo -e "\033[33m cpu_info:$cpu_model \033[0m" | tee -a ${status_log}
-ip=`ifconfig| grep -A 1 'eth0'|grep 'inet'|awk -F ':' '{print $2}'|awk '{print $1}'`
-echo -e "\033[33m ip_info:$ip \033[0m" | tee -a ${status_log}
-
-function status_check(){
-    last_status=$1   # the exit code
-    run_model=$2
-    run_command=$3
-    run_log=$4
-    if [ $last_status -eq 0 ]; then
-        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${run_log}
-    else
-        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${run_log}
-    fi
-}
-IFS='|'
-for train_model in ${train_model_list[*]}; do 
-    if [ ${train_model} = "ocr_det" ];then
-        model_name="det"
-        yml_file="configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml"
-        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
-        cd ./inference && tar xf ch_det_data_50.tar && cd ../
-        img_dir="./inference/ch_det_data_50/all-sum-510"
-        data_dir=./inference/ch_det_data_50/
-        data_label_file=[./inference/ch_det_data_50/test_gt_50.txt]
-    elif [ ${train_model} = "ocr_rec" ];then
-        model_name="rec"
-        yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
-        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar 
-        cd ./inference && tar xf ch_rec_data_200.tar  && cd ../
-        img_dir="./inference/ch_rec_data_200/"
-    fi
-
-    # eval 
-    for slim_trainer in ${slim_trainer_list[*]}; do 
-        if [ ${slim_trainer} = "norm" ]; then
-            if [ ${model_name} = "det" ]; then
-                eval_model_name="ch_ppocr_mobile_v2.0_det_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            else 
-                eval_model_name="ch_ppocr_mobile_v2.0_rec_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            fi 
-        elif [ ${slim_trainer} = "pact" ]; then
-            if [ ${model_name} = "det" ]; then
-                eval_model_name="ch_ppocr_mobile_v2.0_det_quant_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            else
-                eval_model_name="ch_ppocr_mobile_v2.0_rec_quant_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            fi
-        elif [ ${slim_trainer} = "distill" ]; then
-            if [ ${model_name} = "det" ]; then
-                eval_model_name="ch_ppocr_mobile_v2.0_det_distill_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_distill_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            else
-                eval_model_name="ch_ppocr_mobile_v2.0_rec_distill_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            fi 
-        elif [ ${slim_trainer} = "fpgm" ]; then
-            if [ ${model_name} = "det" ]; then
-                eval_model_name="ch_ppocr_mobile_v2.0_det_prune_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            else
-                eval_model_name="ch_ppocr_mobile_v2.0_rec_prune_train"
-                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
-                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
-            fi
-        fi
-
-        save_log_path="${log_path}/${eval_model_name}"
-        command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='./inference/${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} Eval.dataset.data_dir=${data_dir}  Eval.dataset.label_file_list=${data_label_file}"
-        ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=./inference/${eval_model_name}/best_accuracy Global.save_model_dir=${save_log_path} Eval.dataset.data_dir=${data_dir}  Eval.dataset.label_file_list=${data_label_file}
-        status_check $? "${trainer}" "${command}" "${status_log}"
-
-        command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
-        ${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="./inference/${eval_model_name}/best_accuracy" Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
-        status_check $? "${trainer}" "${command}" "${status_log}"
-
-        if [ $? -eq 0 ]; then
-            echo -e "\033[33m training of $model_name successfully!\033[0m" | tee -a ${save_log}/train.log
-        else
-            cat ${save_log}/train.log
-            echo -e "\033[33m training of $model_name failed!\033[0m" | tee -a ${save_log}/train.log
-        fi
-        if [ "${model_name}" = "det" ]; then 
-            export rec_batch_size_list=( "1" )
-            inference="tools/infer/predict_det.py"
-            det_model_dir="${log_path}/${eval_model_name}_infer"
-            rec_model_dir=""
-        elif [ "${model_name}" = "rec" ]; then
-            inference="tools/infer/predict_rec.py"
-            rec_model_dir="${log_path}/${eval_model_name}_infer"
-            det_model_dir=""
-        fi
-        # inference 
-        for device in ${devices[*]}; do 
-            if [ ${device} = "cpu" ]; then
-                for use_mkldnn in ${use_mkldnn_list[*]}; do
-                    for threads in ${cpu_threads_list[*]}; do
-                        for rec_batch_size in ${rec_batch_size_list[*]}; do    
-                            save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
-                            command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
-                            ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
-                            status_check $? "${trainer}" "${command}" "${status_log}"
-                        done
-                    done
-                done
-            else
-                # env="export CUDA_VISIBLE_DEVICES=${infer_gpu_id}"
-                for use_trt in ${gpu_trt_list[*]}; do
-                    for precision in ${gpu_precision_list[*]}; do
-                        if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
-                            continue
-                        fi
-                        for rec_batch_size in ${rec_batch_size_list[*]}; do
-                            save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                            command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
-                            ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
-                            status_check $? "${trainer}" "${command}" "${status_log}"
-                        done
-                    done
-                done
-            fi
-        done
-    done
-done
diff --git a/test/ocr_det_params.txt b/test/ocr_det_params.txt
new file mode 100644
index 00000000..9752ba43
--- /dev/null
+++ b/test/ocr_det_params.txt
@@ -0,0 +1,35 @@
+model_name:ocr_det
+python:python3.7
+gpu_list:-1|0|0,1
+Global.auto_cast:False|True
+Global.epoch_num:10
+Global.save_model_dir:./output/
+Global.save_inference_dir:./output/
+Train.loader.batch_size_per_card:
+Global.use_gpu
+Global.pretrained_model
+
+trainer:norm|pact|fpgm
+norm_train:tools/train.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
+quant_train:deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy
+fpgm_train:null
+distill_train:null
+
+eval:tools/eval.py -c configs/det/det_mv3_db.yml -o 
+
+norm_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o 
+quant_export:deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o 
+fpgm_export:deploy/slim/prune/export_prune_model.py
+distill_export:null
+
+inference:tools/infer/predict_det.py
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:True|False
+--precision:fp32|fp16|int8
+--det_model_dir
+--image_dir
+--save_log_path
+
diff --git a/test/paddleocr_ci_params.txt b/test/paddleocr_ci_params.txt
deleted file mode 100644
index 4cd035ea..00000000
--- a/test/paddleocr_ci_params.txt
+++ /dev/null
@@ -1,15 +0,0 @@
-train_model_list: ocr_det
-gpu_list: -1|0|0,1
-auto_cast_list: False|True
-trainer_list: norm|pact|fpgm
-python: python3.7
-
-inference: python
-devices: cpu|gpu
-use_mkldnn_list: True|False
-cpu_threads_list: 1|6
-rec_batch_size_list: 1|6
-gpu_trt_list: True|False
-gpu_precision_list: fp32|fp16|int8
-infer_gpu_id: 0
-log_path: ./output
diff --git a/test/prepare.sh b/test/prepare.sh
new file mode 100644
index 00000000..65ea28c1
--- /dev/null
+++ b/test/prepare.sh
@@ -0,0 +1,138 @@
+#!/bin/bash
+FILENAME=$1
+# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer']
+MODE=$2
+
+dataline=$(cat ${FILENAME})
+
+# parser params
+IFS=$'\n'
+lines=(${dataline})
+function func_parser_key(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[0]}
+    echo ${tmp}
+}
+function func_parser_value(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[1]}
+    echo ${tmp}
+}
+IFS=$'\n'
+# The training params
+model_name=$(func_parser_value "${lines[0]}")
+train_model_list=$(func_parser_value "${lines[0]}")
+slim_trainer_list=$(func_parser_value "${lines[12]}")
+
+# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer']
+MODE=$2
+# prepare pretrained weights and dataset 
+wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
+wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar
+cd pretrain_models && tar xf det_mv3_db_v2.0_train.tar && cd ../
+
+if [ ${MODE} = "lite_train_infer" ];then
+    # pretrain lite train data
+    rm -rf ./train_data/icdar2015
+    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
+    cd ./train_data/ && tar xf icdar2015_lite.tar
+    ln -s ./icdar2015_lite ./icdar2015
+    cd ../
+    epoch=10
+    eval_batch_step=10
+elif [ ${MODE} = "whole_train_infer" ];then
+    rm -rf ./train_data/icdar2015
+    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar
+    cd ./train_data/ && tar xf icdar2015.tar && cd ../
+    epoch=500
+    eval_batch_step=200
+elif [ ${MODE} = "whole_infer" ];then
+    rm -rf ./train_data/icdar2015
+    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_infer.tar
+    cd ./train_data/ && tar xf icdar2015_infer.tar
+    ln -s ./icdar2015_infer ./icdar2015
+    cd ../
+    epoch=10
+    eval_batch_step=10
+else
+    rm -rf ./train_data/icdar2015
+    wget -nc -P ./train_data https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
+    if [ ${model_name} = "ocr_det" ]; then
+        eval_model_name="ch_ppocr_mobile_v2.0_det_train"
+        wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
+        cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+    else 
+        eval_model_name="ch_ppocr_mobile_v2.0_rec_train"
+        wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
+        cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+    fi 
+fi
+
+
+IFS='|'
+for train_model in ${train_model_list[*]}; do 
+    if [ ${train_model} = "ocr_det" ];then
+        model_name="det"
+        yml_file="configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml"
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
+        cd ./inference && tar xf ch_det_data_50.tar && cd ../
+        img_dir="./inference/ch_det_data_50/all-sum-510"
+        data_dir=./inference/ch_det_data_50/
+        data_label_file=[./inference/ch_det_data_50/test_gt_50.txt]
+    elif [ ${train_model} = "ocr_rec" ];then
+        model_name="rec"
+        yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar 
+        cd ./inference && tar xf ch_rec_data_200.tar  && cd ../
+        img_dir="./inference/ch_rec_data_200/"
+    fi
+
+    # eval 
+    for slim_trainer in ${slim_trainer_list[*]}; do 
+        if [ ${slim_trainer} = "norm" ]; then
+            if [ ${model_name} = "det" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            else 
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            fi 
+        elif [ ${slim_trainer} = "pact" ]; then
+            if [ ${model_name} = "det" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_quant_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            else
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_quant_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            fi
+        elif [ ${slim_trainer} = "distill" ]; then
+            if [ ${model_name} = "det" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_distill_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_distill_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            else
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_distill_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            fi 
+        elif [ ${slim_trainer} = "fpgm" ]; then
+            if [ ${model_name} = "det" ]; then
+                eval_model_name="ch_ppocr_mobile_v2.0_det_prune_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            else
+                eval_model_name="ch_ppocr_mobile_v2.0_rec_prune_train"
+                wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
+                cd ./inference && tar xf ${eval_model_name}.tar && cd ../
+            fi
+        fi
+    done
+done
diff --git a/test/test.sh b/test/test.sh
index 5bb48ac5..b95b8ead 100644
--- a/test/test.sh
+++ b/test/test.sh
@@ -1,203 +1,221 @@
-#!/bin/bash 
-# Usage:
-# bash test/test.sh ./test/paddleocr_ci_params.txt 'lite_train_infer'
-
+#!/bin/bash
 FILENAME=$1
-
-# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer']
+# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer']
 MODE=$2
-# prepare pretrained weights and dataset 
-wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
-wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar
-cd pretrain_models && tar xf det_mv3_db_v2.0_train.tar && cd ../
-
-if [ ${MODE} = "lite_train_infer" ];then
-    # pretrain lite train data
-    rm -rf ./train_data/icdar2015
-    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
-    cd ./train_data/ && tar xf icdar2015_lite.tar
-    ln -s ./icdar2015_lite ./icdar2015
-    cd ../
-    epoch=10
-    eval_batch_step=10
-elif [ ${MODE} = "whole_train_infer" ];then
-    rm -rf ./train_data/icdar2015
-    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar
-    cd ./train_data/ && tar xf icdar2015.tar && cd ../
-    epoch=500
-    eval_batch_step=200
-else
-    rm -rf ./train_data/icdar2015
-    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_infer.tar
-    cd ./train_data/ && tar xf icdar2015_infer.tar
-    ln -s ./icdar2015_infer ./icdar2015
-    cd ../
-    epoch=10
-    eval_batch_step=10
-fi
-
-img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
-
 
 dataline=$(cat ${FILENAME})
+
 # parser params
 IFS=$'\n'
 lines=(${dataline})
-function func_parser(){
+function func_parser_key(){
     strs=$1
-    IFS=": "
+    IFS=":"
+    array=(${strs})
+    tmp=${array[0]}
+    echo ${tmp}
+}
+function func_parser_value(){
+    strs=$1
+    IFS=":"
     array=(${strs})
     tmp=${array[1]}
     echo ${tmp}
 }
-IFS=$'\n'
-# The training params
-train_model_list=$(func_parser "${lines[0]}")
-gpu_list=$(func_parser "${lines[1]}")
-auto_cast_list=$(func_parser "${lines[2]}")
-slim_trainer_list=$(func_parser "${lines[3]}")
-python=$(func_parser "${lines[4]}")
-# inference params
-inference=$(func_parser "${lines[5]}")
-devices=$(func_parser "${lines[6]}")
-use_mkldnn_list=$(func_parser "${lines[7]}")
-cpu_threads_list=$(func_parser "${lines[8]}")
-rec_batch_size_list=$(func_parser "${lines[9]}")
-gpu_trt_list=$(func_parser "${lines[10]}")
-gpu_precision_list=$(func_parser "${lines[11]}")
-
-log_path=$(func_parser "${lines[13]}")
-status_log="${log_path}/result.log"
-
-# install requirments
-${python} -m pip install pynvml;
-${python} -m pip install psutil;
-${python} -m pip install GPUtil;
-${python} -m pip install paddlesim==2.0.0
-
-paddle_info="$(${python} -c "import paddle;print(f'paddle_version:{paddle.__version__}');print(f'paddle_commit:{paddle.__git_commit__}')")"
-echo -e "\033[33m $paddle_info \033[0m" | tee -a ${status_log}
-cpu_model=`cat /proc/cpuinfo | grep "model name" | awk -F ':' '{print $2}' | sort | uniq`
-echo -e "\033[33m cpu_info:$cpu_model \033[0m" | tee -a ${status_log}
-ip=`ifconfig| grep -A 1 'eth0'|grep 'inet'|awk -F ':' '{print $2}'|awk '{print $1}'`
-echo -e "\033[33m ip_info:$ip \033[0m" | tee -a ${status_log}
-
 function status_check(){
     last_status=$1   # the exit code
-    run_model=$2
-    run_command=$3
-    run_log=$4
+    run_command=$2
+    run_log=$3
     if [ $last_status -eq 0 ]; then
-        echo -e "\033[33m $run_model successfully with command - ${run_command}!  \033[0m" | tee -a ${run_log}
+        echo -e "\033[33m Run successfully with command - ${run_command}!  \033[0m" | tee -a ${run_log}
     else
-        echo -e "\033[33m $case failed with command - ${run_command}!  \033[0m" | tee -a ${run_log}
+        echo -e "\033[33m Run failed with command - ${run_command}!  \033[0m" | tee -a ${run_log}
     fi
 }
 
-IFS="|"
-for train_model in ${train_model_list[*]}; do 
-    if [ ${train_model} = "ocr_det" ];then
-        model_name="det"
-        yml_file="configs/det/det_mv3_db.yml"
-    elif [ ${train_model} = "ocr_rec" ];then
-        model_name="rec"
-        yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
-    else
-        model_name="det"
-        yml_file="configs/det/det_mv3_db.yml"
-    fi
-    IFS="|"
-    for gpu in ${gpu_list[*]}; do
-        use_gpu=True
-        if [ ${gpu} = "-1" ];then
-            use_gpu=False
-            env=""
-        elif [ ${#gpu} -le 1 ];then
-            env="CUDA_VISIBLE_DEVICES=${gpu}"
-        else
-            IFS=","
-            array=(${gpu})
-            env="CUDA_VISIBLE_DEVICES=${array[0]}"
-            IFS="|"
-        fi
-        for auto_cast in ${auto_cast_list[*]}; do 
-            for slim_trainer in ${slim_trainer_list[*]}; do 
-                if [ ${slim_trainer} = "norm" ]; then
-                    trainer="tools/train.py"
-                    export_model="tools/export_model.py"
-                    pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
-                elif [ ${slim_trainer} = "pact" ]; then
-                    trainer="deploy/slim/quantization/quant.py"
-                    export_model="deploy/slim/quantization/export_model.py"
-                    pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
-                elif [ ${slim_trainer} = "fpgm" ]; then
-                    trainer="deploy/slim/prune/sensitivity_anal.py"
-                    export_model="deploy/slim/prune/export_prune_model.py"
-                    pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
-                    wget -nc -P https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/sen.pickle
-                elif [ ${slim_trainer} = "distill" ]; then
-                    trainer="deploy/slim/distill/train_dml.py"
-                    export_model="deploy/slim/distill/export_distill_model.py"
-                    pretrain=""
-                else
-                    trainer="tools/train.py"
-                    export_model="tools/export_model.py"
-                    pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
-                fi
-                save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
-                if [ ${#gpu} -le 2 ];then
-                    command="${python} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
-                    ${python} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
-                else 
-                    command="${python} -m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
-                    ${python} -m paddle.distributed.launch --log_dir=./debug/ --gpus ${gpu} ${trainer}  -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain}  Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}  Train.loader.batch_size_per_card=2
-                fi
-                status_check $? "${trainer}" "${command}" "${status_log}"
+IFS=$'\n'
+# The training params
+model_name=$(func_parser_value "${lines[0]}")
+python=$(func_parser_value "${lines[1]}")
+gpu_list=$(func_parser_value "${lines[2]}")
+autocast_list=$(func_parser_value "${lines[3]}")
+autocast_key=$(func_parser_key "${lines[3]}")
+epoch_key=$(func_parser_key "${lines[4]}")
+save_model_key=$(func_parser_key "${lines[5]}")
+save_infer_key=$(func_parser_key "${lines[6]}")
+train_batch_key=$(func_parser_key "${lines[7]}")
+train_use_gpu_key=$(func_parser_key "${lines[8]}")
+pretrain_model_key=$(func_parser_key "${lines[9]}")
 
-                command="${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}_infer/ Global.save_model_dir=${save_log}"
-                ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}_infer/ Global.save_model_dir=${save_log} 
-                status_check $? "${trainer}" "${command}" "${status_log}"
-               
-                if [ "${model_name}" = "det" ]; then 
-                    export rec_batch_size_list=( "1" )
-                    inference="tools/infer/predict_det.py"
-                    det_model_dir=${save_log}_infer
-                    rec_model_dir=""
-                elif [ "${model_name}" = "rec" ]; then
-                    inference="tools/infer/predict_rec.py"
-                    rec_model_dir=${save_log}_infer
-                    det_model_dir=""
-                fi
-                # inference 
-                for device in ${devices[*]}; do 
-                    if [ ${device} = "cpu" ]; then
-                        for use_mkldnn in ${use_mkldnn_list[*]}; do
-                            for threads in ${cpu_threads_list[*]}; do
-                                for rec_batch_size in ${rec_batch_size_list[*]}; do    
-                                    save_log_path="${log_path}/${model_name}_${slim_trainer}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_recbatchnum_${rec_batch_size}_infer.log"
-                                    command="${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}"
-                                    ${python} ${inference} --enable_mkldnn=${use_mkldnn} --use_gpu=False --cpu_threads=${threads} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir}  --image_dir=${img_dir}  --save_log_path=${save_log_path}
-                                    status_check $? "${inference}" "${command}" "${status_log}"
-                                done
-                            done
-                        done
-                    else 
-                        for use_trt in ${gpu_trt_list[*]}; do
-                            for precision in ${gpu_precision_list[*]}; do
-                                if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
-                                    continue
-                                fi
-                                for rec_batch_size in ${rec_batch_size_list[*]}; do
-                                    save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log"
-                                    command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}"
-                                    ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt}  --precision=${precision} --benchmark=True --det_model_dir=${det_model_dir} --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}
-                                    status_check $? "${inference}" "${command}" "${status_log}"
-                                done
-                            done
-                        done
-                    fi
+trainer_list=$(func_parser_value "${lines[10]}")
+norm_trainer=$(func_parser_value "${lines[11]}")
+pact_trainer=$(func_parser_value "${lines[12]}")
+fpgm_trainer=$(func_parser_value "${lines[13]}")
+distill_trainer=$(func_parser_value "${lines[14]}")
+
+eval_py=$(func_parser_value "${lines[15]}")
+norm_export=$(func_parser_value "${lines[16]}")
+pact_export=$(func_parser_value "${lines[17]}")
+fpgm_export=$(func_parser_value "${lines[18]}")
+distill_export=$(func_parser_value "${lines[19]}")
+
+inference_py=$(func_parser_value "${lines[20]}")
+use_gpu_key=$(func_parser_key "${lines[21]}")
+use_gpu_list=$(func_parser_value "${lines[21]}")
+use_mkldnn_key=$(func_parser_key "${lines[22]}")
+use_mkldnn_list=$(func_parser_value "${lines[22]}")
+cpu_threads_key=$(func_parser_key "${lines[23]}")
+cpu_threads_list=$(func_parser_value "${lines[23]}")
+batch_size_key=$(func_parser_key "${lines[24]}")
+batch_size_list=$(func_parser_value "${lines[24]}")
+use_trt_key=$(func_parser_key "${lines[25]}")
+use_trt_list=$(func_parser_value "${lines[25]}")
+precision_key=$(func_parser_key "${lines[26]}")
+precision_list=$(func_parser_value "${lines[26]}")
+model_dir_key=$(func_parser_key "${lines[27]}")
+image_dir_key=$(func_parser_key "${lines[28]}")
+save_log_key=$(func_parser_key "${lines[29]}")
+
+LOG_PATH="./test/output"
+mkdir -p ${LOG_PATH}
+status_log="${LOG_PATH}/results.log"
+
+if [ ${MODE} = "lite_train_infer" ]; then
+    export infer_img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
+    export epoch_num=10
+elif [ ${MODE} = "whole_infer" ]; then
+    export infer_img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
+    export epoch_num=10
+elif [ ${MODE} = "whole_train_infer" ]; then
+    export infer_img_dir="./train_data/icdar2015/text_localization/ch4_test_images/"
+    export epoch_num=300
+else
+    export infer_img_dir="./inference/ch_det_data_50/all-sum-510"
+    export infer_model_dir="./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy"
+fi
+
+
+function func_inference(){
+    IFS='|'
+    _python=$1
+    _script=$2
+    _model_dir=$3
+    _log_path=$4
+    _img_dir=$5
+    
+    # inference 
+    for use_gpu in ${use_gpu_list[*]}; do 
+        if [ ${use_gpu} = "False" ]; then
+            for use_mkldnn in ${use_mkldnn_list[*]}; do
+                for threads in ${cpu_threads_list[*]}; do
+                    for batch_size in ${batch_size_list[*]}; do
+                        _save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}"
+                        command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${cpu_threads_key}=${threads} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir}  ${save_log_key}=${_save_log_path}"
+                        eval $command
+                        status_check $? "${command}" "${status_log}"
+                    done
                 done
             done
+        else
+            for use_trt in ${use_trt_list[*]}; do
+                for precision in ${precision_list[*]}; do
+                    if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
+                        continue
+                    fi
+                    for batch_size in ${batch_size_list[*]}; do
+                        _save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}"
+                        command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_trt_key}=${use_trt} ${precision_key}=${precision} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir}  ${save_log_key}=${_save_log_path}"
+                        eval $command
+                        status_check $? "${command}" "${status_log}"
+                    done
+                done
+            done
+        fi
+    done
+}
+
+if [ ${MODE} != "infer" ]; then
+
+IFS="|"
+for gpu in ${gpu_list[*]}; do
+    use_gpu=True
+    if [ ${gpu} = "-1" ];then
+        use_gpu=False
+        env=""
+    elif [ ${#gpu} -le 1 ];then
+        env="export CUDA_VISIBLE_DEVICES=${gpu}"
+    elif [ ${#gpu} -le 15 ];then
+        IFS=","
+        array=(${gpu})
+        env="export CUDA_VISIBLE_DEVICES=${array[0]}"
+        IFS="|"
+    else
+        IFS=";"
+        array=(${gpu})
+        ips=${array[0]}
+        gpu=${array[1]}
+        IFS="|"
+    fi
+    for autocast in ${autocast_list[*]}; do 
+        for trainer in ${trainer_list[*]}; do 
+            if [ ${trainer} = "pact" ]; then
+                run_train=${pact_trainer}
+                run_export=${pact_export}
+            elif [ ${trainer} = "fpgm" ]; then
+                run_train=${fpgm_trainer}
+                run_export=${fpgm_export}
+            elif [ ${trainer} = "distill" ]; then
+                run_train=${distill_trainer}
+                run_export=${distill_export}
+            else
+                run_train=${norm_trainer}
+                run_export=${norm_export}
+            fi
+
+            if [ ${run_train} = "null" ]; then
+                continue
+            fi
+            if [ ${run_export} = "null" ]; then
+                continue
+            fi
+
+            save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}"
+            if [ ${#gpu} -le 2 ];then  # epoch_num #TODO
+                cmd="${python} ${run_train} ${train_use_gpu_key}=${use_gpu} ${autocast_key}=${autocast} ${epoch_key}=${epoch_num} ${save_model_key}=${save_log} "
+            elif [ ${#gpu} -le 15 ];then
+                cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${autocast_key}=${autocast} ${epoch_key}=${epoch_num}  ${save_model_key}=${save_log}"
+            else
+                cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${autocast_key}=${autocast} ${epoch_key}=${epoch_num} ${save_model_key}=${save_log}"
+            fi
+            # run train
+            eval $cmd
+            status_check $? "${cmd}" "${status_log}"
+
+            # run eval
+            eval_cmd="${python} ${eval_py} ${save_model_key}=${save_log} ${pretrain_model_key}=${save_log}/latest" 
+            eval $eval_cmd
+            status_check $? "${eval_cmd}" "${status_log}"
+
+            # run export model
+            save_infer_path="${save_log}"
+            export_cmd="${python} ${run_export} ${save_model_key}=${save_log} ${pretrain_model_key}=${save_log}/latest ${save_infer_key}=${save_infer_path}"
+            eval $export_cmd
+            status_check $? "${export_cmd}" "${status_log}"
+
+            #run inference
+            save_infer_path="${save_log}"
+            func_inference "${python}" "${inference_py}" "${save_infer_path}" "${LOG_PATH}" "${infer_img_dir}"
         done
     done
 done
+
+else
+    save_infer_path="${LOG_PATH}/${MODE}"
+    run_export=${norm_export}
+    export_cmd="${python} ${run_export} ${save_model_key}=${save_infer_path} ${pretrain_model_key}=${infer_model_dir} ${save_infer_key}=${save_infer_path}"
+    eval $export_cmd
+    status_check $? "${export_cmd}" "${status_log}"
+
+    #run inference
+    func_inference "${python}" "${inference_py}" "${save_infer_path}" "${LOG_PATH}" "${infer_img_dir}"
+fi

From 9cac660093e4046ed13cefa5b1a7a61b44a0b2a8 Mon Sep 17 00:00:00 2001
From: LDOUBLEV <liuvv0203@outlook.com>
Date: Mon, 28 Jun 2021 20:49:36 +0800
Subject: [PATCH 34/34] update prepare.sh

---
 test/prepare.sh | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/test/prepare.sh b/test/prepare.sh
index 65ea28c1..42f12b57 100644
--- a/test/prepare.sh
+++ b/test/prepare.sh
@@ -26,7 +26,7 @@ IFS=$'\n'
 # The training params
 model_name=$(func_parser_value "${lines[0]}")
 train_model_list=$(func_parser_value "${lines[0]}")
-slim_trainer_list=$(func_parser_value "${lines[12]}")
+trainer_list=$(func_parser_value "${lines[10]}")
 
 # MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer']
 MODE=$2
@@ -76,7 +76,7 @@ fi
 IFS='|'
 for train_model in ${train_model_list[*]}; do 
     if [ ${train_model} = "ocr_det" ];then
-        model_name="det"
+        model_name="ocr_det"
         yml_file="configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml"
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
         cd ./inference && tar xf ch_det_data_50.tar && cd ../
@@ -84,7 +84,7 @@ for train_model in ${train_model_list[*]}; do
         data_dir=./inference/ch_det_data_50/
         data_label_file=[./inference/ch_det_data_50/test_gt_50.txt]
     elif [ ${train_model} = "ocr_rec" ];then
-        model_name="rec"
+        model_name="ocr_rec"
         yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar 
         cd ./inference && tar xf ch_rec_data_200.tar  && cd ../
@@ -92,7 +92,7 @@ for train_model in ${train_model_list[*]}; do
     fi
 
     # eval 
-    for slim_trainer in ${slim_trainer_list[*]}; do 
+    for slim_trainer in ${trainer_list[*]}; do 
         if [ ${slim_trainer} = "norm" ]; then
             if [ ${model_name} = "det" ]; then
                 eval_model_name="ch_ppocr_mobile_v2.0_det_train"