diff --git a/test_tipc/static/mask_rcnn_r50_1x_coco/N1C1/mask_rcnn_r50_1x_coco_bs2_fp32_SingleP_DP.sh b/test_tipc/static/mask_rcnn_r50_1x_coco/N1C1/mask_rcnn_r50_1x_coco_bs2_fp32_SingleP_DP.sh
index 698b4f7c3fd3b5c1fad7039e80f540445a16a337..66cd2adbc8e404ad364a58dc215e33e4a5fb9302 100644
--- a/test_tipc/static/mask_rcnn_r50_1x_coco/N1C1/mask_rcnn_r50_1x_coco_bs2_fp32_SingleP_DP.sh
+++ b/test_tipc/static/mask_rcnn_r50_1x_coco/N1C1/mask_rcnn_r50_1x_coco_bs2_fp32_SingleP_DP.sh
@@ -4,7 +4,7 @@ fp_item=fp32
 run_process_type=SingleP
 run_mode=DP
 device_num=N1C1
-max_iter=500
+max_iter=100
 num_workers=2
 
 # get data
@@ -14,4 +14,4 @@ bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_it
 # run profiling
 sleep 10;
 export PROFILING=true
-bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_process_type} ${run_mode} ${device_num} ${max_iter} ${num_workers} 2>&1;
+bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_process_type} ${run_mode} ${device_num} 11 ${num_workers} 2>&1;
diff --git a/test_tipc/static/mask_rcnn_r50_1x_coco/N1C8/mask_rcnn_r50_1x_coco_bs2_fp32_MultiP_DP.sh b/test_tipc/static/mask_rcnn_r50_1x_coco/N1C8/mask_rcnn_r50_1x_coco_bs2_fp32_MultiP_DP.sh
index ee3a9ddd0e8dc6700bfe386fe254d43dee426893..1dabcecc8c09e9b61d9f56e4040c0c5487e597f6 100644
--- a/test_tipc/static/mask_rcnn_r50_1x_coco/N1C8/mask_rcnn_r50_1x_coco_bs2_fp32_MultiP_DP.sh
+++ b/test_tipc/static/mask_rcnn_r50_1x_coco/N1C8/mask_rcnn_r50_1x_coco_bs2_fp32_MultiP_DP.sh
@@ -4,7 +4,7 @@ fp_item=fp32
 run_process_type=MultiP
 run_mode=DP
 device_num=N1C8
-max_iter=500
+max_iter=100
 num_workers=2
 
 # get data
diff --git a/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/prepare.sh b/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/prepare.sh
index e5a7024d41b3799f56ab850ec4ffba9c3a33fd60..f2325a10799319ff3293aeb97d5c00c18fd1a8e0 100644
--- a/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/prepare.sh
+++ b/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/prepare.sh
@@ -2,14 +2,13 @@
 # 执行路径在模型库的根目录下
 ################################# 安装框架 如:
 echo "*******prepare benchmark start ***********"
-pip install -U pip -i https://pypi.tuna.tsinghua.edu.cn/simple
+pip install -U pip
 echo `pip --version`
-pip install Cython -i https://pypi.tuna.tsinghua.edu.cn/simple
-python -m pip install paddlepaddle-gpu==2.2.2.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
-pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+pip install Cython
+pip install -r requirements.txt
 
 ################################# 准备训练数据 如:
-wget -nc -P static/data/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar
-cd ./static/data/coco/ && tar -xf coco_benchmark.tar && mv -u coco_benchmark/* .
+wget -nc -P static/dataset/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar
+cd ./static/dataset/coco/ && tar -xf coco_benchmark.tar && mv -u coco_benchmark/* .
 rm -rf coco_benchmark/ && cd ../../../
 echo "*******prepare benchmark end***********"
diff --git a/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/run_benchmark.sh b/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/run_benchmark.sh
index d8d5b44cb027a0e5c266d8e16f6e0088d212d894..57e685d5390cf7d3f87deb887b01f443c50eade1 100644
--- a/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/run_benchmark.sh
+++ b/test_tipc/static/mask_rcnn_r50_1x_coco/benchmark_common/run_benchmark.sh
@@ -14,7 +14,7 @@ function _set_params(){
     skip_steps=10                  # (必选)解析日志，跳过模型前几个性能不稳定的step
     keyword="ips:"                 # (必选)解析日志，筛选出性能数据所在行的关键字
     convergence_key="loss:"        # (可选)解析日志，筛选出收敛数据所在行的关键字 如：convergence_key="loss:"
-    max_iter=${7:-"500"}           # （可选）需保证模型执行时间在5分钟内，需要修改代码提前中断的直接提PR 合入套件；或使用max_epoch参数
+    max_iter=${7:-"100"}           # （可选）需保证模型执行时间在5分钟内，需要修改代码提前中断的直接提PR 合入套件；或使用max_epoch参数
     num_workers=${8:-"8"}                  # (可选)
 #   以下为通用执行命令，无特殊可不用修改
     model_name=${model_item}_bs${base_batch_size}_${fp_item}_${run_process_type}_${run_mode}  # (必填) 且格式不要改动,与竞品名称对齐
@@ -48,9 +48,9 @@ function _train(){
     fi
 
     train_cmd="-c configs/mask_rcnn_r50_1x.yml -o LearningRate.base_lr=0.001 snapshot_iter=100000 \
-         TrainReader.batch_size==${batch_size} \
+         TrainReader.batch_size=${batch_size} \
          max_iters=${max_iter} log_iter=1 \
-         TrainReader.worker_num==${num_workers} ${use_fp16_cmd} \
+         TrainReader.worker_num=${num_workers} ${use_fp16_cmd} \
          --is_profiler=${is_profiler} "
 #   以下为通用执行命令，无特殊可不用修改
     case ${run_mode} in
@@ -84,5 +84,5 @@ function _train(){
 }
 source ${BENCHMARK_ROOT}/scripts/run_model.sh   # 在该脚本中会对符合benchmark规范的log使用analysis.py 脚本进行性能数据解析;如果不联调只想要产出训练log可以注掉本行,提交时需打开
 _set_params $@
-_train       # 如果只产出训练log,不解析,可取消注释
+#_train       # 如果只产出训练log,不解析,可取消注释
 _run     # 该函数在run_model.sh中,执行时会调用_train; 如果不联调只产出训练log可以注掉本行,提交时需打开
diff --git a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C1/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_SingleP_DP.sh b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C1/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_SingleP_DP.sh
index 499468244c5a2d3f24a58ee70cb5dd88487508ef..266a5a7560787761398856eca6063a26b5bfacb3 100644
--- a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C1/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_SingleP_DP.sh
+++ b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C1/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_SingleP_DP.sh
@@ -4,7 +4,7 @@ fp_item=fp32
 run_process_type=SingleP
 run_mode=DP
 device_num=N1C1
-max_iter=500
+max_iter=100
 num_workers=2
 
 # get data
@@ -14,4 +14,4 @@ bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_it
 # run profiling
 sleep 10;
 export PROFILING=true
-bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_process_type} ${run_mode} ${device_num} ${max_iter} ${num_workers} 2>&1;
+bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_process_type} ${run_mode} ${device_num} 11 ${num_workers} 2>&1;
diff --git a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C8/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_MultiP_DP.sh b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C8/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_MultiP_DP.sh
index 7781efff832d10b9b843c0a2ba3f379461c00772..b8000b8eb1ce6e629bb7e6250a3f4899cf04cc5e 100644
--- a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C8/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_MultiP_DP.sh
+++ b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/N1C8/mask_rcnn_r50_fpn_1x_coco_bs2_fp32_MultiP_DP.sh
@@ -4,7 +4,7 @@ fp_item=fp32
 run_process_type=MultiP
 run_mode=DP
 device_num=N1C8
-max_iter=500
+max_iter=100
 num_workers=2
 
 # get data
diff --git a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/prepare.sh b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/prepare.sh
index e5a7024d41b3799f56ab850ec4ffba9c3a33fd60..f2325a10799319ff3293aeb97d5c00c18fd1a8e0 100644
--- a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/prepare.sh
+++ b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/prepare.sh
@@ -2,14 +2,13 @@
 # 执行路径在模型库的根目录下
 ################################# 安装框架 如:
 echo "*******prepare benchmark start ***********"
-pip install -U pip -i https://pypi.tuna.tsinghua.edu.cn/simple
+pip install -U pip
 echo `pip --version`
-pip install Cython -i https://pypi.tuna.tsinghua.edu.cn/simple
-python -m pip install paddlepaddle-gpu==2.2.2.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
-pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+pip install Cython
+pip install -r requirements.txt
 
 ################################# 准备训练数据 如:
-wget -nc -P static/data/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar
-cd ./static/data/coco/ && tar -xf coco_benchmark.tar && mv -u coco_benchmark/* .
+wget -nc -P static/dataset/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar
+cd ./static/dataset/coco/ && tar -xf coco_benchmark.tar && mv -u coco_benchmark/* .
 rm -rf coco_benchmark/ && cd ../../../
 echo "*******prepare benchmark end***********"
diff --git a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/run_benchmark.sh b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/run_benchmark.sh
index 520af4d4c09563382dbfbfbab6f8d25dc0b842fe..d3a5bbb9984a697cc6d164dcf080d861b1b7d8a0 100644
--- a/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/run_benchmark.sh
+++ b/test_tipc/static/mask_rcnn_r50_fpn_1x_coco/benchmark_common/run_benchmark.sh
@@ -14,7 +14,7 @@ function _set_params(){
     skip_steps=10                  # (必选)解析日志，跳过模型前几个性能不稳定的step
     keyword="ips:"                 # (必选)解析日志，筛选出性能数据所在行的关键字
     convergence_key="loss:"        # (可选)解析日志，筛选出收敛数据所在行的关键字 如：convergence_key="loss:"
-    max_iter=${7:-"500"}           # （可选）需保证模型执行时间在5分钟内，需要修改代码提前中断的直接提PR 合入套件；或使用max_epoch参数
+    max_iter=${7:-"100"}           # （可选）需保证模型执行时间在5分钟内，需要修改代码提前中断的直接提PR 合入套件；或使用max_epoch参数
     num_workers=${8:-"8"}                  # (可选)
 #   以下为通用执行命令，无特殊可不用修改
     model_name=${model_item}_bs${base_batch_size}_${fp_item}_${run_process_type}_${run_mode}  # (必填) 且格式不要改动,与竞品名称对齐
@@ -48,9 +48,9 @@ function _train(){
     fi
 
     train_cmd="-c configs/mask_rcnn_r50_fpn_1x.yml -o LearningRate.base_lr=0.001 snapshot_iter=100000 \
-         TrainReader.batch_size==${batch_size} \
+         TrainReader.batch_size=${batch_size} \
          max_iters=${max_iter} log_iter=1 \
-         TrainReader.worker_num==${num_workers} ${use_fp16_cmd} \
+         TrainReader.worker_num=${num_workers} ${use_fp16_cmd} \
          --is_profiler=${is_profiler} "
 #   以下为通用执行命令，无特殊可不用修改
     case ${run_mode} in
@@ -84,5 +84,5 @@ function _train(){
 }
 source ${BENCHMARK_ROOT}/scripts/run_model.sh   # 在该脚本中会对符合benchmark规范的log使用analysis.py 脚本进行性能数据解析;如果不联调只想要产出训练log可以注掉本行,提交时需打开
 _set_params $@
-_train       # 如果只产出训练log,不解析,可取消注释
+#_train       # 如果只产出训练log,不解析,可取消注释
 _run     # 该函数在run_model.sh中,执行时会调用_train; 如果不联调只产出训练log可以注掉本行,提交时需打开
diff --git a/test_tipc/static/yolov3_darknet53_270e_coco/N1C1/yolov3_darknet53_270e_coco_bs8_fp32_SingleP_DP.sh b/test_tipc/static/yolov3_darknet53_270e_coco/N1C1/yolov3_darknet53_270e_coco_bs8_fp32_SingleP_DP.sh
index db222b9738bac9ad59fe995f11d8e7f434f0ac9b..d30a34bcbb686554dcafe470a0ef1cda163cafeb 100644
--- a/test_tipc/static/yolov3_darknet53_270e_coco/N1C1/yolov3_darknet53_270e_coco_bs8_fp32_SingleP_DP.sh
+++ b/test_tipc/static/yolov3_darknet53_270e_coco/N1C1/yolov3_darknet53_270e_coco_bs8_fp32_SingleP_DP.sh
@@ -4,7 +4,7 @@ fp_item=fp32
 run_process_type=SingleP
 run_mode=DP
 device_num=N1C1
-max_iter=500
+max_iter=100
 num_workers=8
 
 # get data
@@ -14,4 +14,4 @@ bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_it
 # run profiling
 sleep 10;
 export PROFILING=true
-bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_process_type} ${run_mode} ${device_num} ${max_iter} ${num_workers} 2>&1;
+bash test_tipc/static/${model_item}/benchmark_common/run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_process_type} ${run_mode} ${device_num} 11 ${num_workers} 2>&1;
diff --git a/test_tipc/static/yolov3_darknet53_270e_coco/N1C8/yolov3_darknet53_270e_coco_bs8_fp32_MultiP_DP.sh b/test_tipc/static/yolov3_darknet53_270e_coco/N1C8/yolov3_darknet53_270e_coco_bs8_fp32_MultiP_DP.sh
index 80c80fe974dbfcde85daa09c0cb491679d38c92d..8081990254812ffff24296b1fa97faa3df638727 100644
--- a/test_tipc/static/yolov3_darknet53_270e_coco/N1C8/yolov3_darknet53_270e_coco_bs8_fp32_MultiP_DP.sh
+++ b/test_tipc/static/yolov3_darknet53_270e_coco/N1C8/yolov3_darknet53_270e_coco_bs8_fp32_MultiP_DP.sh
@@ -4,7 +4,7 @@ fp_item=fp32
 run_process_type=MultiP
 run_mode=DP
 device_num=N1C8
-max_iter=500
+max_iter=100
 num_workers=8
 
 # get data
diff --git a/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/prepare.sh b/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/prepare.sh
index e5a7024d41b3799f56ab850ec4ffba9c3a33fd60..f2325a10799319ff3293aeb97d5c00c18fd1a8e0 100644
--- a/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/prepare.sh
+++ b/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/prepare.sh
@@ -2,14 +2,13 @@
 # 执行路径在模型库的根目录下
 ################################# 安装框架 如:
 echo "*******prepare benchmark start ***********"
-pip install -U pip -i https://pypi.tuna.tsinghua.edu.cn/simple
+pip install -U pip
 echo `pip --version`
-pip install Cython -i https://pypi.tuna.tsinghua.edu.cn/simple
-python -m pip install paddlepaddle-gpu==2.2.2.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
-pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+pip install Cython
+pip install -r requirements.txt
 
 ################################# 准备训练数据 如:
-wget -nc -P static/data/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar
-cd ./static/data/coco/ && tar -xf coco_benchmark.tar && mv -u coco_benchmark/* .
+wget -nc -P static/dataset/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar
+cd ./static/dataset/coco/ && tar -xf coco_benchmark.tar && mv -u coco_benchmark/* .
 rm -rf coco_benchmark/ && cd ../../../
 echo "*******prepare benchmark end***********"
diff --git a/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/run_benchmark.sh b/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/run_benchmark.sh
index fcd55431b54362ce8777428b230b4792442ea8fa..8a75a75b8033221a19cb2d816bcc8d317be57d27 100644
--- a/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/run_benchmark.sh
+++ b/test_tipc/static/yolov3_darknet53_270e_coco/benchmark_common/run_benchmark.sh
@@ -14,7 +14,7 @@ function _set_params(){
     skip_steps=10                  # (必选)解析日志，跳过模型前几个性能不稳定的step
     keyword="ips:"                 # (必选)解析日志，筛选出性能数据所在行的关键字
     convergence_key="loss:"        # (可选)解析日志，筛选出收敛数据所在行的关键字 如：convergence_key="loss:"
-    max_iter=${7:-"500"}           # （可选）需保证模型执行时间在5分钟内，需要修改代码提前中断的直接提PR 合入套件；或使用max_epoch参数
+    max_iter=${7:-"100"}           # （可选）需保证模型执行时间在5分钟内，需要修改代码提前中断的直接提PR 合入套件；或使用max_epoch参数
     num_workers=${8:-"8"}                  # (可选)
 #   以下为通用执行命令，无特殊可不用修改
     model_name=${model_item}_bs${base_batch_size}_${fp_item}_${run_process_type}_${run_mode}  # (必填) 且格式不要改动,与竞品名称对齐
@@ -48,9 +48,9 @@ function _train(){
     fi
 
     train_cmd="-c configs/yolov3_darknet.yml -o LearningRate.base_lr=0.002 snapshot_iter=100000 \
-         TrainReader.batch_size==${batch_size} \
+         TrainReader.batch_size=${batch_size} \
          max_iters=${max_iter} log_iter=1 \
-         TrainReader.worker_num==${num_workers} ${use_fp16_cmd} \
+         TrainReader.worker_num=${num_workers} ${use_fp16_cmd} \
          --is_profiler=${is_profiler} "
 #   以下为通用执行命令，无特殊可不用修改
     case ${run_mode} in
@@ -84,5 +84,5 @@ function _train(){
 }
 source ${BENCHMARK_ROOT}/scripts/run_model.sh   # 在该脚本中会对符合benchmark规范的log使用analysis.py 脚本进行性能数据解析;如果不联调只想要产出训练log可以注掉本行,提交时需打开
 _set_params $@
-_train       # 如果只产出训练log,不解析,可取消注释
+#_train       # 如果只产出训练log,不解析,可取消注释
 _run     # 该函数在run_model.sh中,执行时会调用_train; 如果不联调只产出训练log可以注掉本行,提交时需打开