Merge pull request #1362 from TeslaZhao/develop

House cleaning

python/examples/bert/README.md

@@ -45,22 +45,22 @@ this script will download Chinese Dictionary File vocab.txt and Chinese Sample D
 ### Inference Service(Support BRPC-Client、GRPC-Client、Http-Client)
 start cpu inference service,Run
 ```
-python -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292  #cpu inference service
+python3 -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292  #cpu inference service
 ```
 Or,start gpu inference service,Run
 ```
-python -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292 --gpu_ids 0 #launch gpu inference service at GPU 0
+python3 -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292 --gpu_ids 0 #launch gpu inference service at GPU 0
 ```
 
 ### BRPC-Client Inference
 
 before prediction we should install paddle_serving_app. This module provides data preprocessing for BERT model.
 ```
-pip install paddle_serving_app
+pip3 install paddle_serving_app
 ```
 Run
 ```
-head data-c.txt | python bert_client.py --model bert_seq128_client/serving_client_conf.prototxt
+head data-c.txt | python3 bert_client.py --model bert_seq128_client/serving_client_conf.prototxt
 ```
 
 the client reads data from data-c.txt and send prediction request, the prediction is given by word vector. (Due to massive data in the word vector, we do not print it).
@@ -68,7 +68,7 @@ the client reads data from data-c.txt and send prediction request, the predictio
 #### GRPC-Client/HTTP-Client
 Run
 ```
-head data-c.txt | python bert_httpclient.py --model bert_seq128_client/serving_client_conf.prototxt
+head data-c.txt | python3 bert_httpclient.py --model bert_seq128_client/serving_client_conf.prototxt
 
 ```
 

python/examples/bert/README_CN.md

@@ -43,12 +43,12 @@ sh get_data.sh
 ### 启动预测服务（支持BRPC-Client、GRPC-Client、HTTP-Client三种方式访问）
 启动cpu预测服务，执行
 ```
-python -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292  #启动cpu预测服务
+python3 -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292  #启动cpu预测服务
 
 ```
 或者，启动gpu预测服务，执行
 ```
-python -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292 --gpu_ids 0 #在gpu 0上启动gpu预测服务
+python3 -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292 --gpu_ids 0 #在gpu 0上启动gpu预测服务
 
 ```
 
@@ -56,13 +56,13 @@ python -m paddle_serving_server.serve --model bert_seq128_model/ --port 9292 --g
 
 执行预测前需要安装paddle_serving_app，模块中提供了BERT模型的数据预处理方法。
 ```
-pip install paddle_serving_app
+pip3 install paddle_serving_app
 ```
 
 #### BRPC-Client
 执行
 ```
-head data-c.txt | python bert_client.py --model bert_seq128_client/serving_client_conf.prototxt
+head data-c.txt | python3 bert_client.py --model bert_seq128_client/serving_client_conf.prototxt
 
 ```
 启动client读取data-c.txt中的数据进行预测，预测结果为文本的向量表示（由于数据较多，脚本中没有将输出进行打印），server端的地址在脚本中修改。
@@ -70,7 +70,7 @@ head data-c.txt | python bert_client.py --model bert_seq128_client/serving_clien
 #### GRPC-Client/HTTP-Client
 执行
 ```
-head data-c.txt | python bert_httpclient.py --model bert_seq128_client/serving_client_conf.prototxt
+head data-c.txt | python3 bert_httpclient.py --model bert_seq128_client/serving_client_conf.prototxt
 
 ```
 

python/examples/blazeface/README.md

@@ -2,7 +2,7 @@
 
 ## Get Model
 ```
-python -m paddle_serving_app.package --get_model blazeface
+python3 -m paddle_serving_app.package --get_model blazeface
 tar -xf blazeface.tar.gz
 ```
 
@@ -11,13 +11,13 @@ tar -xf blazeface.tar.gz
 ### Start Service
 
 ```
-python -m paddle_serving_server.serve --model serving_server --port 9494
+python3 -m paddle_serving_server.serve --model serving_server --port 9494
 ```
 
 ### Client Prediction
 
 ```
-python test_client.py serving_client/serving_client_conf.prototxt test.jpg
+python3 test_client.py serving_client/serving_client_conf.prototxt test.jpg
 ```
 
 the result is in `output` folder, including a json file and image file with bounding boxes.

python/examples/cascade_rcnn/README.md

@@ -10,12 +10,12 @@ If you want to have more detection models, please refer to [Paddle Detection Mod
 
 ### Start the service
 ```
-python -m paddle_serving_server.serve --model serving_server --port 9292 --gpu_id 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9292 --gpu_id 0
 ```
 
 ### Perform prediction
 ```
-python test_client.py 
+python3 test_client.py 
 ```
 
 Image with bounding boxes and json result would be saved in `output` folder.

python/examples/cascade_rcnn/README_CN.md

@@ -10,12 +10,12 @@ sh get_data.sh
 
 ### 启动服务
 ```
-python -m paddle_serving_server.serve --model serving_server --port 9292 --gpu_id 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9292 --gpu_id 0
 ```
 
 ### 执行预测
 ```
-python test_client.py
+python3 test_client.py
 ```
 
 客户端已经为图片做好了后处理，在`output`文件夹下存放各个框的json格式信息还有后处理结果图片。

python/examples/criteo_ctr/README.md

@@ -19,13 +19,13 @@ the directories like `ctr_serving_model` and `ctr_client_conf` will appear.
 ### Start RPC Inference Service
 
 ```
-python -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 #CPU RPC Service
-python -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 --gpu_ids 0 #RPC Service on GPU 0
+python3 -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 #CPU RPC Service
+python3 -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 --gpu_ids 0 #RPC Service on GPU 0
 ```
 
 ### RPC Infer
 
 ```
-python test_client.py ctr_client_conf/serving_client_conf.prototxt raw_data/part-0
+python3 test_client.py ctr_client_conf/serving_client_conf.prototxt raw_data/part-0
 ```
 the latency will display in the end.

python/examples/criteo_ctr/README_CN.md

@@ -19,13 +19,13 @@ mv models/ctr_serving_model .
 ### 启动RPC预测服务
 
 ```
-python -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 #启动CPU预测服务
-python -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 --gpu_ids 0 #在GPU 0上启动预测服务
+python3 -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 #启动CPU预测服务
+python3 -m paddle_serving_server.serve --model ctr_serving_model/ --port 9292 --gpu_ids 0 #在GPU 0上启动预测服务
 ```
 
 ### 执行预测
 
 ```
-python test_client.py ctr_client_conf/serving_client_conf.prototxt raw_data/part-0
+python3 test_client.py ctr_client_conf/serving_client_conf.prototxt raw_data/part-0
 ```
 预测完毕会输出预测过程的耗时。

python/examples/criteo_ctr_with_cube/README.md

@@ -32,13 +32,13 @@ Here, the sparse parameter is loaded by cube sparse parameter indexing service C
 ### Start RPC Predictor, the number of serving thread is 4（configurable in test_server.py）
 
 ```
-python test_server.py ctr_serving_model_kv 
+python3 test_server.py ctr_serving_model_kv 
 ```
 
 ### Run Prediction
 
 ```
-python test_client.py ctr_client_conf/serving_client_conf.prototxt ./raw_data
+python3 test_client.py ctr_client_conf/serving_client_conf.prototxt ./raw_data
 ```
 
 ### Benchmark

python/examples/criteo_ctr_with_cube/README_CN.md

@@ -30,13 +30,13 @@ sh cube_prepare.sh &
 ### 启动RPC预测服务，服务端线程数为4（可在test_server.py配置）
 
 ```
-python test_server.py ctr_serving_model_kv 
+python3 test_server.py ctr_serving_model_kv 
 ```
 
 ### 执行预测
 
 ```
-python test_client.py ctr_client_conf/serving_client_conf.prototxt ./raw_data
+python3 test_client.py ctr_client_conf/serving_client_conf.prototxt ./raw_data
 ```
 
 ### Benchmark

python/examples/deeplabv3/README.md

@@ -3,7 +3,7 @@
 ## Get Model
 
 ```
-python -m paddle_serving_app.package --get_model deeplabv3
+python3 -m paddle_serving_app.package --get_model deeplabv3
 tar -xzvf deeplabv3.tar.gz
 ```
 
@@ -12,11 +12,11 @@ tar -xzvf deeplabv3.tar.gz
 ### Start Service
 
 ```
-python -m paddle_serving_server.serve --model deeplabv3_server --gpu_ids 0 --port 9494
+python3 -m paddle_serving_server.serve --model deeplabv3_server --gpu_ids 0 --port 9494
 ```
 
 ### Client Prediction
 
 ```
-python deeplabv3_client.py
+python3 deeplabv3_client.py
 ```

python/examples/deeplabv3/README_CN.md

@@ -3,7 +3,7 @@
 ## 获取模型
 
 ```
-python -m paddle_serving_app.package --get_model deeplabv3
+python3 -m paddle_serving_app.package --get_model deeplabv3
 tar -xzvf deeplabv3.tar.gz
 ```
 
@@ -12,10 +12,10 @@ tar -xzvf deeplabv3.tar.gz
 ### 启动服务端
 
 ```
-python -m paddle_serving_server.serve --model deeplabv3_server --gpu_ids 0 --port 9494
+python3 -m paddle_serving_server.serve --model deeplabv3_server --gpu_ids 0 --port 9494
 ```
 
 ### 客户端预测
 
 ```
-python deeplabv3_client.py
+python3 deeplabv3_client.py

python/examples/detection/faster_rcnn_hrnetv2p_w18_1x/README.md

@@ -10,7 +10,7 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf faster_rcnn_hrnetv2p_w18_1x.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 This model support TensorRT, if you want a faster inference, please use `--use_trt`. But you need to do some extra work.
@@ -19,5 +19,5 @@ Please reference to https://github.com/PaddlePaddle/Paddle-Inference-Demo/blob/m
 
 ### Prediction
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```

python/examples/detection/faster_rcnn_hrnetv2p_w18_1x/README_CN.md

@@ -11,12 +11,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### 启动服务
 ```
 tar xf faster_rcnn_hrnetv2p_w18_1x.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 该模型支持TensorRT，如果想要更快的预测速度，可以开启`--use_trt`选项,但此时需要额外设置子图的TRT变长最大最小最优shape.
 请参考https://github.com/PaddlePaddle/Paddle-Inference-Demo/blob/master/c%2B%2B/paddle-trt/trt_dynamic_shape_test.cc#L40
 
 ### 执行预测
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```

python/examples/detection/faster_rcnn_r50_fpn_1x_coco/README.md

@@ -10,7 +10,7 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf faster_rcnn_r50_fpn_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 This model support TensorRT, if you want a faster inference, please use `--use_trt`. But you need to do some extra work.
@@ -19,7 +19,7 @@ Please reference to https://github.com/PaddlePaddle/Paddle-Inference-Demo/blob/m
 
 ### Perform prediction
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
 
 ## 3. Result analysis

python/examples/detection/faster_rcnn_r50_fpn_1x_coco/README_CN.md

@@ -11,14 +11,14 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### 启动服务
 ```
 tar xf faster_rcnn_r50_fpn_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 该模型支持TensorRT，如果想要更快的预测速度，可以开启`--use_trt`选项,但此时需要额外设置子图的TRT变长最大最小最优shape.
 请参考https://github.com/PaddlePaddle/Paddle-Inference-Demo/blob/master/c%2B%2B/paddle-trt/trt_dynamic_shape_test.cc#L40
 
 ### 执行预测
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
 
 ## 3. 结果分析

python/examples/detection/fcos_dcn_r50_fpn_1x_coco/README.md

@@ -10,11 +10,11 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf fcos_dcn_r50_fpn_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 This model support TensorRT, if you want a faster inference, please use `--use_trt`.
 
 ### Perform prediction
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```

python/examples/detection/fcos_dcn_r50_fpn_1x_coco/README_CN.md

@@ -11,12 +11,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### 启动服务
 ```
 tar xf fcos_dcn_r50_fpn_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 该模型支持TensorRT，如果想要更快的预测速度，可以开启`--use_trt`选项。
 
 ### 执行预测
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```

python/examples/detection/ppyolo_r50vd_dcn_1x_coco/README.md

@@ -10,13 +10,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf ppyolo_r50vd_dcn_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 This model support TensorRT, if you want a faster inference, please use `--use_trt`.
 
 ### Perform prediction
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
-

python/examples/detection/ppyolo_r50vd_dcn_1x_coco/README_CN.md

@@ -11,13 +11,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### 启动服务
 ```
 tar xf ppyolo_r50vd_dcn_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 该模型支持TensorRT，如果想要更快的预测速度，可以开启`--use_trt`选项。
 
 ### 执行预测
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
-

python/examples/detection/ssd_vgg16_300_240e_voc/README.md

@@ -10,11 +10,11 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf ssd_vgg16_300_240e_voc.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 This model support TensorRT, if you want a faster inference, please use `--use_trt`.
 
 ### Perform prediction
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```

python/examples/detection/ssd_vgg16_300_240e_voc/README_CN.md

@@ -11,12 +11,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### 启动服务
 ```
 tar xf ssd_vgg16_300_240e_voc.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 该模型支持TensorRT，如果想要更快的预测速度，可以开启`--use_trt`选项。
 
 ### 执行预测
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```

python/examples/detection/ttfnet_darknet53_1x_coco/README.md

@@ -10,12 +10,11 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf ttfnet_darknet53_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 This model support TensorRT, if you want a faster inference, please use `--use_trt`.
 
 ### Perform prediction
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
-

python/examples/detection/ttfnet_darknet53_1x_coco/README_CN.md

@@ -11,13 +11,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### 启动服务
 ```
 tar xf ttfnet_darknet53_1x_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 该模型支持TensorRT，如果想要更快的预测速度，可以开启`--use_trt`选项。
 
 ### 执行预测
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
-

python/examples/detection/yolov3_darknet53_270e_coco/README.md

@@ -10,13 +10,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf yolov3_darknet53_270e_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 This model support TensorRT, if you want a faster inference, please use `--use_trt`.
 
 ### Perform prediction
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
-

python/examples/detection/yolov3_darknet53_270e_coco/README_CN.md

@@ -11,13 +11,12 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### 启动服务
 ```
 tar xf yolov3_darknet53_270e_coco.tar
-python -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model serving_server --port 9494 --gpu_ids 0
 ```
 
 该模型支持TensorRT，如果想要更快的预测速度，可以开启`--use_trt`选项。
 
 ### 执行预测
 ```
-python test_client.py 000000570688.jpg
+python3 test_client.py 000000570688.jpg
 ```
-

python/examples/encryption/README.md

@@ -12,9 +12,9 @@ sh get_data.sh
 
 ## Encrypt Model
 
-The `paddlepaddle` package is used in this example, you may need to download the corresponding package(`pip install paddlepaddle`).
+The `paddlepaddle` package is used in this example, you may need to download the corresponding package(`pip3 install paddlepaddle`).
 
-[python encrypt.py](./encrypt.py)
+[python3 encrypt.py](./encrypt.py)
 
 [//file]:#encrypt.py
 ``` python
@@ -35,14 +35,14 @@ client-side configuration file are stored in the `encrypt_client` directory.
 ## Start Encryption Service
 CPU Service
 ```
-python -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model
+python3 -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model
 ```
 GPU Service
 ```
-python -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model --gpu_ids 0
+python3 -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model --gpu_ids 0
 ```
 
 ## Prediction
 ```
-python test_client.py encrypt_client/serving_client_conf.prototxt
+python3 test_client.py encrypt_client/serving_client_conf.prototxt
 ```

python/examples/encryption/README_CN.md

@@ -11,9 +11,9 @@ sh get_data.sh
 ```
 
 ## 模型加密
-本示例中使用了`paddlepaddle`包中的模块，需要进行下载（`pip install paddlepaddle`）。
+本示例中使用了`paddlepaddle`包中的模块，需要进行下载（`pip3 install paddlepaddle`）。
 
-运行[python encrypt.py](./encrypt.py)进行模型加密
+运行[python3 encrypt.py](./encrypt.py)进行模型加密
 
 [//file]:#encrypt.py
 ``` python
@@ -36,14 +36,14 @@ def serving_encryption():
 ## 启动加密预测服务
 CPU预测服务
 ```
-python -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model
+python3 -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model
 ```
 GPU预测服务
 ```
-python -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model --gpu_ids 0
+python3 -m paddle_serving_server.serve --model encrypt_server/ --port 9393 --use_encryption_model --gpu_ids 0
 ```
 
 ## 预测
 ```
-python test_client.py encrypt_client/serving_client_conf.prototxt
+python3 test_client.py encrypt_client/serving_client_conf.prototxt
 ```

python/examples/fit_a_line/README.md

@@ -15,22 +15,22 @@ sh get_data.sh
 ### Start server
 
 ```shell
-python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9393
+python3 -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9393
 ```
 
 ## Client prediction
 
 ### RPC Client
-The `paddlepaddle` package is used in `test_client.py`, and you may need to download the corresponding package(`pip install paddlepaddle`).
+The `paddlepaddle` package is used in `test_client.py`, and you may need to download the corresponding package(`pip3 install paddlepaddle`).
 
 ``` shell
-python test_client.py uci_housing_client/serving_client_conf.prototxt
+python3 test_client.py uci_housing_client/serving_client_conf.prototxt
 ```
 
 ### Http Client
 
 ``` shell
-python test_httpclient.py uci_housing_client/serving_client_conf.prototxt
+python3 test_httpclient.py uci_housing_client/serving_client_conf.prototxt
 ```
 
 

python/examples/fit_a_line/README_CN.md

@@ -12,23 +12,23 @@ sh get_data.sh
 ## 开启服务端（支持BRPC-Client/GRPC Client/Http-Client）
 
 ```shell
-python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9393
+python3 -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9393
 ```
 
 ## 客户端预测
 
 ### BRPC-Client
 
-`test_client.py`中使用了`paddlepaddle`包，需要进行下载（`pip install paddlepaddle`）。
+`test_client.py`中使用了`paddlepaddle`包，需要进行下载（`pip3 install paddlepaddle`）。
 
 ``` shell
-python test_client.py uci_housing_client/serving_client_conf.prototxt
+python3 test_client.py uci_housing_client/serving_client_conf.prototxt
 ```
 
 ### GRPC-Client/Http-Client
 
 ``` shell
-python test_httpclient.py uci_housing_client/serving_client_conf.prototxt
+python3 test_httpclient.py uci_housing_client/serving_client_conf.prototxt
 ```
 
 

python/examples/imagenet/README.md

@@ -12,7 +12,7 @@ sh get_model.sh
 ### Install preprocess module
 
 ```
-pip install paddle_serving_app
+pip3 install paddle_serving_app
 ```
 
 
@@ -20,22 +20,22 @@ pip install paddle_serving_app
 
 launch server side
 ```
-python -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 #cpu inference service
+python3 -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 #cpu inference service
 ```
 
 ```
-python -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 --gpu_ids 0 #gpu inference service
+python3 -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 --gpu_ids 0 #gpu inference service
 ```
 
 ### BRPC-Client
 client send inference request
 ```
-python resnet50_rpc_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
+python3 resnet50_rpc_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
 ```
 *the port of server side in this example is 9696
 
 ### GRPC-Client/Http-Client
 client send inference request
 ```
-python resnet50_http_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
+python3 resnet50_http_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
 ```

python/examples/imagenet/README_CN.md

@@ -12,24 +12,24 @@ sh get_model.sh
 ### 安装数据预处理模块
 
 ```
-pip install paddle_serving_app
+pip3 install paddle_serving_app
 ```
 
 ### 启动服务端（支持BRPC-Client、GRPC-Client、Http-Client）
 
 启动server端
 ```
-python -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 #cpu预测服务
+python3 -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 #cpu预测服务
 ```
 
 ```
-python -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 --gpu_ids 0 #gpu预测服务
+python3 -m paddle_serving_server.serve --model ResNet50_vd_model --port 9696 --gpu_ids 0 #gpu预测服务
 ```
 
 ### BRPC-Client预测
 client端进行预测
 ```
-python resnet50_rpc_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
+python3 resnet50_rpc_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
 ```
 *server端示例中服务端口为9696端口
 
@@ -37,5 +37,5 @@ python resnet50_rpc_client.py ResNet50_vd_client_config/serving_client_conf.prot
 ### GRPC-Client/Http-Client预测
 client端进行预测
 ```
-python resnet50_http_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
+python3 resnet50_http_client.py ResNet50_vd_client_config/serving_client_conf.prototxt
 ```

python/examples/imdb/README.md

@@ -12,11 +12,11 @@ the package downloaded contains cnn, lstm and bow model config along with their
 ### Start inference service(Support BRPC-Client/GRPC-Client/Http-Client)
 
 ```
-python -m paddle_serving_server.serve --model imdb_cnn_model/ --port 9292
+python3 -m paddle_serving_server.serve --model imdb_cnn_model/ --port 9292
 ```
 ### BRPC-Client Infer
 ```
-head test_data/part-0 | python test_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
+head test_data/part-0 | python3 test_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
 ```
 
 it will get predict results of the first 10 test cases.
@@ -24,5 +24,5 @@ it will get predict results of the first 10 test cases.
 
 ### GRPC-Client/Http-Client Infer
 ```
-head test_data/part-0 | python test_http_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
+head test_data/part-0 | python3 test_http_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
 ```

python/examples/imdb/README_CN.md

@@ -12,15 +12,15 @@ sh get_data.sh
 ### 启动预测服务(支持BRPC-Client/GRPC-Client/Http-Client)
 
 ```
-python -m paddle_serving_server.serve --model imdb_cnn_model/ --port 9292
+python3 -m paddle_serving_server.serve --model imdb_cnn_model/ --port 9292
 ```
 ### BRPC-Client预测
 ```
-head test_data/part-0 | python test_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
+head test_data/part-0 | python3 test_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
 ```
 预测test_data/part-0的前十个样例。
 
 ### BRPC-Client预测
 ```
-head test_data/part-0 | python test_http_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
+head test_data/part-0 | python3 test_http_client.py imdb_cnn_client_conf/serving_client_conf.prototxt imdb.vocab
 ```

python/examples/lac/README.md

@@ -4,23 +4,23 @@
 
 ### Get Model
 ```
-python -m paddle_serving_app.package --get_model lac
+python3 -m paddle_serving_app.package --get_model lac
 tar -xzvf lac.tar.gz
 ```
 
 #### Start inference service(Support BRPC-Client/GRPC-Client/Http-Client)
 
 ```
-python -m paddle_serving_server.serve --model lac_model/ --port 9292
+python3 -m paddle_serving_server.serve --model lac_model/ --port 9292
 ```
 ### BRPC Infer
 ```
-echo "我爱北京天安门" | python lac_client.py lac_client/serving_client_conf.prototxt
+echo "我爱北京天安门" | python3 lac_client.py lac_client/serving_client_conf.prototxt
 ```
 
 It will get the segmentation result. 
 
 ### GRPC/Http Infer
 ```
-echo "我爱北京天安门" | python lac_http_client.py lac_client/serving_client_conf.prototxt
+echo "我爱北京天安门" | python3 lac_http_client.py lac_client/serving_client_conf.prototxt
 ```

python/examples/lac/README_CN.md

@@ -4,23 +4,23 @@
 
 ### 获取模型
 ```
-python -m paddle_serving_app.package --get_model lac
+python3 -m paddle_serving_app.package --get_model lac
 tar -xzvf lac.tar.gz
 ```
 
 #### 开启预测服务(支持BRPC-Client/GRPC-Client/Http-Client)
 
 ```
-python -m paddle_serving_server.serve --model lac_model/ --port 9292
+python3 -m paddle_serving_server.serve --model lac_model/ --port 9292
 ```
 ### 执行BRPC预测
 ```
-echo "我爱北京天安门" | python lac_client.py lac_client/serving_client_conf.prototxt
+echo "我爱北京天安门" | python3 lac_client.py lac_client/serving_client_conf.prototxt
 ```
 
 我们就能得到分词结果
 
 ### 执行GRPC/Http预测
 ```
-echo "我爱北京天安门" | python lac_http_client.py lac_client/serving_client_conf.prototxt
+echo "我爱北京天安门" | python3 lac_http_client.py lac_client/serving_client_conf.prototxt
 ```

python/examples/low_precision/resnet50/README.md

@@ -11,15 +11,15 @@ Firstly, download the [Resnet50 int8 model](https://paddle-inference-dist.bj.bce
 wget https://paddle-inference-dist.bj.bcebos.com/inference_demo/python/resnet50/ResNet50_quant.tar.gz
 tar zxvf ResNet50_quant.tar.gz
 
-python -m paddle_serving_client.convert --dirname ResNet50_quant
+python3 -m paddle_serving_client.convert --dirname ResNet50_quant
 ```
 Start RPC service, specify the GPU id and precision mode
 ```
-python -m paddle_serving_server.serve --model serving_server --port 9393 --gpu_ids 0 --use_trt --precision int8 
+python3 -m paddle_serving_server.serve --model serving_server --port 9393 --gpu_ids 0 --use_trt --precision int8 
 ```
 Request the serving service with Client
 ```
-python resnet50_client.py
+python3 resnet50_client.py
 ```
 
 ## Reference

python/examples/low_precision/resnet50/README_CN.md

@@ -10,15 +10,15 @@
 wget https://paddle-inference-dist.bj.bcebos.com/inference_demo/python/resnet50/ResNet50_quant.tar.gz
 tar zxvf ResNet50_quant.tar.gz
 
-python -m paddle_serving_client.convert --dirname ResNet50_quant
+python3 -m paddle_serving_client.convert --dirname ResNet50_quant
 ```
 启动rpc服务, 设定所选GPU id、部署模型精度
 ```
-python -m paddle_serving_server.serve --model serving_server --port 9393 --gpu_ids 0 --use_trt --precision int8 
+python3 -m paddle_serving_server.serve --model serving_server --port 9393 --gpu_ids 0 --use_trt --precision int8 
 ```
 使用client进行请求
 ```
-python resnet50_client.py
+python3 resnet50_client.py
 ```
 
 ## 参考文档

python/examples/mobilenet/README.md

@@ -3,7 +3,7 @@
 ## Get Model
 
 ```
-python -m paddle_serving_app.package --get_model mobilenet_v2_imagenet
+python3 -m paddle_serving_app.package --get_model mobilenet_v2_imagenet
 tar -xzvf mobilenet_v2_imagenet.tar.gz
 ```
 
@@ -12,11 +12,11 @@ tar -xzvf mobilenet_v2_imagenet.tar.gz
 ### Start Service
 
 ```
-python -m paddle_serving_server.serve --model mobilenet_v2_imagenet_model --gpu_ids 0 --port 9393
+python3 -m paddle_serving_server.serve --model mobilenet_v2_imagenet_model --gpu_ids 0 --port 9393
 ```
 
 ### Client Prediction
 
 ```
-python mobilenet_tutorial.py
+python3 mobilenet_tutorial.py
 ```

python/examples/mobilenet/README_CN.md

@@ -3,7 +3,7 @@
 ## 获取模型
 
 ```
-python -m paddle_serving_app.package --get_model mobilenet_v2_imagenet
+python3 -m paddle_serving_app.package --get_model mobilenet_v2_imagenet
 tar -xzvf mobilenet_v2_imagenet.tar.gz
 ```
 
@@ -12,11 +12,11 @@ tar -xzvf mobilenet_v2_imagenet.tar.gz
 ### 启动服务端
 
 ```
-python -m paddle_serving_server.serve --model mobilenet_v2_imagenet_model --gpu_ids 0 --port 9393
+python3 -m paddle_serving_server.serve --model mobilenet_v2_imagenet_model --gpu_ids 0 --port 9393
 ```
 
 ### 客户端预测
 
 ```
-python mobilenet_tutorial.py
+python3 mobilenet_tutorial.py
 ```

python/examples/ocr/README.md

@@ -4,9 +4,9 @@
 
 ## Get Model
 ```
-python -m paddle_serving_app.package --get_model ocr_rec
+python3 -m paddle_serving_app.package --get_model ocr_rec
 tar -xzvf ocr_rec.tar.gz
-python -m paddle_serving_app.package --get_model ocr_det
+python3 -m paddle_serving_app.package --get_model ocr_det
 tar -xzvf ocr_det.tar.gz
 ```
 
@@ -23,16 +23,16 @@ tar xf test_imgs.tar
 ```
 #choose one of cpu/gpu commands as following
 #for cpu user
-python -m paddle_serving_server.serve --model ocr_det_model --port 9293
-python ocr_web_server.py cpu
+python3 -m paddle_serving_server.serve --model ocr_det_model --port 9293
+python3 ocr_web_server.py cpu
 #for gpu user
-python -m paddle_serving_server.serve --model ocr_det_model --port 9293 --gpu_ids 0
-python ocr_web_server.py gpu
+python3 -m paddle_serving_server.serve --model ocr_det_model --port 9293 --gpu_ids 0
+python3 ocr_web_server.py gpu
 ```
 
 ### Client Prediction
 ```
-python ocr_web_client.py
+python3 ocr_web_client.py
 ```
 If you want a faster web service, please try Web LocalPredictor Service
 
@@ -40,14 +40,14 @@ If you want a faster web service, please try Web LocalPredictor Service
 ```
 #choose one of cpu/gpu commands as following
 #for cpu user
-python ocr_debugger_server.py cpu
+python3 ocr_debugger_server.py cpu
 #for gpu user
-python ocr_debugger_server.py gpu 
+python3 ocr_debugger_server.py gpu 
 ```
 
 ## Web LocalPredictor Client Prediction
 ```
-python ocr_web_client.py
+python3 ocr_web_client.py
 ```
 
 ## Benchmark
@@ -69,34 +69,34 @@ if you are going to detect images not recognize it or directly recognize the wor
 ### Det Server 
 
 ```
-python det_web_server.py cpu #for cpu user
-python det_web_server.py gpu #for gpu user
+python3 det_web_server.py cpu #for cpu user
+python3 det_web_server.py gpu #for gpu user
 #or
-python det_debugger_server.py cpu #for cpu user
-python det_debugger_server.py gpu #for gpu user
+python3 det_debugger_server.py cpu #for cpu user
+python3 det_debugger_server.py gpu #for gpu user
 ```
 
 ### Det Client
 
 ```
 # also use ocr_web_client.py
-python ocr_web_client.py
+python3 ocr_web_client.py
 ```
 
 ### Rec Server
 
 ```
-python rec_web_server.py cpu #for cpu user
-python rec_web_server.py gpu #for gpu user
+python3 rec_web_server.py cpu #for cpu user
+python3 rec_web_server.py gpu #for gpu user
 #or
-python rec_debugger_server.py cpu #for cpu user
-python rec_debugger_server.py gpu #for gpu user
+python3 rec_debugger_server.py cpu #for cpu user
+python3 rec_debugger_server.py gpu #for gpu user
 ```
 
 ### Rec Client
 
 ```
-python rec_web_client.py
+python3 rec_web_client.py
 ```
 
 ## C++ OCR Service
@@ -109,9 +109,9 @@ Select a startup mode according to CPU / GPU device
 After the -- model parameter, the folder path of multiple model files is passed in to start the prediction service of multiple model concatenation.
 ```
 #for cpu user
-python -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293
+python3 -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293
 #for gpu user
-python -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293 --gpu_ids 0
 ```
 
 ### Client Prediction
@@ -123,5 +123,5 @@ for this case, `feed_type` should be 3(which means the data type is string),`sha
 
 By passing in multiple client folder paths, the client can be started for multi model prediction.
 ```
-python ocr_cpp_client.py ocr_det_client ocr_rec_client
+python3 ocr_cpp_client.py ocr_det_client ocr_rec_client
 ```

python/examples/ocr/README_CN.md

@@ -4,9 +4,9 @@
 
 ## 获取模型
 ```
-python -m paddle_serving_app.package --get_model ocr_rec
+python3 -m paddle_serving_app.package --get_model ocr_rec
 tar -xzvf ocr_rec.tar.gz
-python -m paddle_serving_app.package --get_model ocr_det
+python3 -m paddle_serving_app.package --get_model ocr_det
 tar -xzvf ocr_det.tar.gz
 ```
 ## 获取数据集（可选）
@@ -22,16 +22,16 @@ tar xf test_imgs.tar
 ```
 #根据CPU/GPU设备选择一种启动方式
 #for cpu user
-python -m paddle_serving_server.serve --model ocr_det_model --port 9293
-python ocr_web_server.py cpu
+python3 -m paddle_serving_server.serve --model ocr_det_model --port 9293
+python3 ocr_web_server.py cpu
 #for gpu user
-python -m paddle_serving_server.serve --model ocr_det_model --port 9293 --gpu_ids 0
-python ocr_web_server.py gpu
+python3 -m paddle_serving_server.serve --model ocr_det_model --port 9293 --gpu_ids 0
+python3 ocr_web_server.py gpu
 ```
 
 ### 启动客户端
 ```
-python ocr_web_client.py
+python3 ocr_web_client.py
 ```
 
 如果用户需要更快的执行速度，请尝试LocalPredictor版Web服务
@@ -39,14 +39,14 @@ python ocr_web_client.py
 ```
 #根据CPU/GPU设备选择一种启动方式
 #for cpu user
-python ocr_debugger_server.py cpu
+python3 ocr_debugger_server.py cpu
 #for gpu user
-python ocr_debugger_server.py gpu
+python3 ocr_debugger_server.py gpu
 ```
 
 ## 启动客户端
 ```
-python ocr_web_client.py
+python3 ocr_web_client.py
 ```
 
 ## 性能指标
@@ -69,34 +69,34 @@ GPU: Nvidia Tesla V100单卡
 ### 启动检测服务
 
 ```
-python det_web_server.py cpu #for cpu user
-python det_web_server.py gpu #for gpu user
+python3 det_web_server.py cpu #for cpu user
+python3 det_web_server.py gpu #for gpu user
 #or
-python det_debugger_server.py cpu #for cpu user
-python det_debugger_server.py gpu #for gpu user
+python3 det_debugger_server.py cpu #for cpu user
+python3 det_debugger_server.py gpu #for gpu user
 ```
 
 ### 检测服务客户端
 
 ```
 # also use ocr_web_client.py
-python ocr_web_client.py
+python3 ocr_web_client.py
 ```
 
 ### 启动识别服务
 
 ```
-python rec_web_server.py cpu #for cpu user
-python rec_web_server.py gpu #for gpu user
+python3 rec_web_server.py cpu #for cpu user
+python3 rec_web_server.py gpu #for gpu user
 #or
-python rec_debugger_server.py cpu #for cpu user
-python rec_debugger_server.py gpu #for gpu user
+python3 rec_debugger_server.py cpu #for cpu user
+python3 rec_debugger_server.py gpu #for gpu user
 ```
 
 ### 识别服务客户端
 
 ```
-python rec_web_client.py
+python3 rec_web_client.py
 ```
 ## C++ OCR Service服务
 
@@ -108,9 +108,9 @@ python rec_web_client.py
 通过--model后，指定多个模型文件的文件夹路径来启动多模型串联的预测服务。
 ```
 #for cpu user
-python -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293
+python3 -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293
 #for gpu user
-python -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293 --gpu_ids 0
+python3 -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port 9293 --gpu_ids 0
 ```
 
 ### 启动客户端
@@ -122,5 +122,5 @@ python -m paddle_serving_server.serve --model ocr_det_model ocr_rec_model --port
 
 通过在客户端启动后加入多个client模型的client配置文件夹路径，启动client进行预测。
 ```
-python ocr_cpp_client.py ocr_det_client ocr_rec_client
+python3 ocr_cpp_client.py ocr_det_client ocr_rec_client
 ```

python/examples/pipeline/PaddleClas/DarkNet53/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/DarkNet53/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/DarkNet53/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/DarkNet53/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/HRNet_W18_C/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/HRNet_W18_C/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/HRNet_W18_C/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/HRNet_W18_C/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/HRNet_W18_C/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/MobileNetV1/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/MobileNetV1/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/MobileNetV1/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/MobileNetV1/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/MobileNetV1/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/MobileNetV2/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/MobileNetV2/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/MobileNetV2/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/MobileNetV2/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/MobileNetV2/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/MobileNetV3_large_x1_0/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/MobileNetV3_large_x1_0/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/MobileNetV3_large_x1_0/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/MobileNetV3_large_x1_0/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/MobileNetV3_large_x1_0/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/ResNeXt101_vd_64x4d/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/ResNeXt101_vd_64x4d/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/ResNeXt101_vd_64x4d/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/ResNeXt101_vd_64x4d/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/ResNeXt101_vd_64x4d/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/ResNet50_vd/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/ResNet50_vd/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/ResNet50_vd/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/ResNet50_vd/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/ResNet50_vd/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/ResNet50_vd_FPGM/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/ResNet50_vd_FPGM/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/ResNet50_vd_FPGM/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/ResNet50_vd_FPGM/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/ResNet50_vd_FPGM/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/ResNet50_vd_KL/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/ResNet50_vd_KL/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/ResNet50_vd_KL/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/ResNet50_vd_KL/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/ResNet50_vd_KL/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/ResNet50_vd_PACT/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/ResNet50_vd_PACT/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/ResNet50_vd_PACT/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/ResNet50_vd_PACT/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/ResNet50_vd_PACT/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleClas/ResNet_V2_50/README.md

@@ -4,17 +4,17 @@ This document will takes Imagenet service as an example to introduce how to use
 
 ## Get model
 ```
-python -m paddle_serving_app.package --get_model resnet_v2_50_imagenet
+python3 -m paddle_serving_app.package --get_model resnet_v2_50_imagenet
 tar -xzvf resnet_v2_50_imagenet.tar.gz
 ```
 
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/ResNet_V2_50/README_CN.md

@@ -4,18 +4,17 @@
 
 ## 获取模型
 ```
-python -m paddle_serving_app.package --get_model resnet_v2_50_imagenet
+python3 -m paddle_serving_app.package --get_model resnet_v2_50_imagenet
 tar -xzvf resnet_v2_50_imagenet.tar.gz
 ```
 
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/ResNet_V2_50/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18000/imagenet/prediction"    
+    url = "http://127.0.0.1:18000/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/ResNet_V2_50/pipeline_rpc_client.py

@@ -11,10 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/ShuffleNetV2_x1_0/README.md

@@ -10,10 +10,10 @@ sh get_model.sh
 ## Start server
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## RPC test
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```

python/examples/pipeline/PaddleClas/ShuffleNetV2_x1_0/README_CN.md

@@ -10,11 +10,10 @@ sh get_model.sh
 ## 启动服务
 
 ```
-python resnet50_web_service.py &>log.txt &
+python3 resnet50_web_service.py &>log.txt &
 ```
 
 ## 测试
 ```
-python pipeline_rpc_client.py
+python3 pipeline_rpc_client.py
 ```
-

python/examples/pipeline/PaddleClas/ShuffleNetV2_x1_0/benchmark.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import os
 import base64
@@ -5,13 +19,13 @@ import yaml
 import requests
 import time
 import json
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 from paddle_serving_client.utils import MultiThreadRunner
 from paddle_serving_client.utils import benchmark_args, show_latency
+
+
 def parse_benchmark(filein, fileout):
     with open(filein, "r") as fin:
         res = yaml.load(fin)
@@ -24,6 +38,7 @@ def parse_benchmark(filein, fileout):
     with open(fileout, "w") as fout:
         yaml.dump(res, fout, default_flow_style=False)
 
+
 def gen_yml(device, gpu_id):
     fin = open("config.yml", "r")
     config = yaml.load(fin)
@@ -34,15 +49,17 @@ def gen_yml(device, gpu_id):
         config["op"]["imagenet"]["local_service_conf"]["devices"] = gpu_id
     else:
         config["op"]["imagenet"]["local_service_conf"]["device_type"] = 0
-    with open("config2.yml", "w") as fout: 
+    with open("config2.yml", "w") as fout:
         yaml.dump(config, fout, default_flow_style=False)
 
+
 def cv2_to_base64(image):
     return base64.b64encode(image).decode('utf8')
 
+
 def run_http(idx, batch_size):
     print("start thread ({})".format(idx))
-    url = "http://127.0.0.1:18080/imagenet/prediction"    
+    url = "http://127.0.0.1:18080/imagenet/prediction"
     start = time.time()
 
     with open(os.path.join(".", "daisy.jpg"), 'rb') as file:
@@ -68,6 +85,7 @@ def run_http(idx, batch_size):
     end = time.time()
     return [[end - start], latency_list, [total_num]]
 
+
 def multithread_http(thread, batch_size):
     multi_thread_runner = MultiThreadRunner()
     start = time.time()
@@ -87,6 +105,7 @@ def multithread_http(thread, batch_size):
                                          total_cost))
     show_latency(result[1])
 
+
 def run_rpc(thread, batch_size):
     client = PipelineClient()
     client.connect(['127.0.0.1:18080'])
@@ -107,11 +126,12 @@ def run_rpc(thread, batch_size):
 
 def multithread_rpc(thraed, batch_size):
     multi_thread_runner = MultiThreadRunner()
-    result = multi_thread_runner.run(run_rpc , thread, batch_size)
+    result = multi_thread_runner.run(run_rpc, thread, batch_size)
+
 
 if __name__ == "__main__":
     if sys.argv[1] == "yaml":
-        mode = sys.argv[2] # brpc/  local predictor
+        mode = sys.argv[2]  # brpc/  local predictor
         thread = int(sys.argv[3])
         device = sys.argv[4]
         if device == "gpu":
@@ -120,7 +140,7 @@ if __name__ == "__main__":
             gpu_id = None
         gen_yml(device, gpu_id)
     elif sys.argv[1] == "run":
-        mode = sys.argv[2] # http/ rpc
+        mode = sys.argv[2]  # http/ rpc
         thread = int(sys.argv[3])
         batch_size = int(sys.argv[4])
         if mode == "http":
@@ -131,4 +151,3 @@ if __name__ == "__main__":
         filein = sys.argv[2]
         fileout = sys.argv[3]
         parse_benchmark(filein, fileout)
-    

python/examples/pipeline/PaddleClas/ShuffleNetV2_x1_0/pipeline_rpc_client.py

@@ -11,10 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-try:
-    from paddle_serving_server_gpu.pipeline import PipelineClient
-except ImportError:
-    from paddle_serving_server.pipeline import PipelineClient
+from paddle_serving_server.pipeline import PipelineClient
 import numpy as np
 import requests
 import json

python/examples/pipeline/PaddleClas/ShuffleNetV2_x1_0/resnet50_web_service.py

@@ -13,10 +13,8 @@
 # limitations under the License.
 import sys
 from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize, Base64ToImage
-try:
-    from paddle_serving_server_gpu.web_service import WebService, Op
-except ImportError:
-    from paddle_serving_server.web_service import WebService, Op
+
+from paddle_serving_server.web_service import WebService, Op
 import logging
 import numpy as np
 import base64, cv2

python/examples/pipeline/PaddleDetection/faster_rcnn/README.md

@@ -8,11 +8,11 @@ wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/
 ### Start the service
 ```
 tar xf faster_rcnn_r50_fpn_1x_coco.tar
-python web_service.py
+python3 web_service.py
 ```
 
 ### Perform prediction
 
 ```
-python pipeline_http_client.py
+python3 pipeline_http_client.py
 ```