diff --git a/fluid/PaddleSlim/data/pretrain/download_pretrain.sh b/fluid/PaddleSlim/data/pretrain/download_pretrain.sh
deleted file mode 100644
index 92cb48daf16ad0554df726b125ee7b87a794a468..0000000000000000000000000000000000000000
--- a/fluid/PaddleSlim/data/pretrain/download_pretrain.sh
+++ /dev/null
@@ -1,9 +0,0 @@
-root_url="http://paddle-imagenet-models-name.bj.bcebos.com"
-MobileNetV1="MobileNetV1_pretrained.zip"
-ResNet50="ResNet50_pretrained.zip"
-
-wget ${root_url}/${MobileNetV1}
-unzip ${MobileNetV1}
-
-wget ${root_url}/${ResNet50}
-unzip ${ResNet50}
diff --git a/fluid/PaddleSlim/run.sh b/fluid/PaddleSlim/run.sh
index 4fa57cd8eb13a2f16d42712f79602569b2fbe4a7..336d15b206d0f162018ac99cd9ac708575716a19 100644
--- a/fluid/PaddleSlim/run.sh
+++ b/fluid/PaddleSlim/run.sh
@@ -1,3 +1,28 @@
+#!/usr/bin/env bash
+
+# download pretrain model
+root_url="http://paddle-imagenet-models-name.bj.bcebos.com"
+MobileNetV1="MobileNetV1_pretrained.zip"
+ResNet50="ResNet50_pretrained.zip"
+pretrain_dir='./pretrain'
+
+if [ ! -d ${pretrain_dir} ]; then
+  mkdir ${pretrain_dir}
+fi
+
+cd ${pretrain_dir}
+
+if [ ! -f ${MobileNetV1} ]; then
+    wget ${root_url}/${MobileNetV1}
+    unzip ${MobileNetV1}
+fi
+
+if [ ! -f ${ResNet50} ]; then
+    wget ${root_url}/${ResNet50}
+    unzip ${ResNet50}
+fi
+
+cd -
 
 # for distillation
 #--------------------
@@ -5,7 +30,7 @@ export CUDA_VISIBLE_DEVICES=0
 python compress.py \
 --model "MobileNet" \
 --teacher_model "ResNet50" \
---teacher_pretrained_model ./data/pretrain/ResNet50_pretrained \
+--teacher_pretrained_model ./pretrain/ResNet50_pretrained \
 --compress_config ./configs/mobilenetv1_resnet50_distillation.yaml
 
 
@@ -14,7 +39,7 @@ python compress.py \
 #export CUDA_VISIBLE_DEVICES=0
 #python compress.py \
 #--model "MobileNet" \
-#--pretrained_model ./data/pretrain/MobileNetV1_pretrained \
+#--pretrained_model ./pretrain/MobileNetV1_pretrained \
 #--compress_config ./configs/filter_pruning_sen.yaml
 
 # for uniform filter pruning
@@ -22,7 +47,7 @@ python compress.py \
 #export CUDA_VISIBLE_DEVICES=0
 #python compress.py \
 #--model "MobileNet" \
-#--pretrained_model ./data/pretrain/MobileNetV1_pretrained \
+#--pretrained_model ./pretrain/MobileNetV1_pretrained \
 #--compress_config ./configs/filter_pruning_uniform.yaml
 
 # for quantization
@@ -31,6 +56,6 @@ python compress.py \
 #python compress.py \
 #--batch_size 64 \
 #--model "MobileNet" \
-#--pretrained_model ./data/pretrain/MobileNetV1_pretrained \
+#--pretrained_model ./pretrain/MobileNetV1_pretrained \
 #--compress_config ./configs/quantization.yaml