Merge pull request #1170 from zhangjun/xpu-fix

[doc] fix doc for xpu example

python/examples/low_precision/resnet50/resnet50_client.py

@@ -19,7 +19,7 @@ from paddle_serving_app.reader import RGB2BGR, Transpose, Div, Normalize
 client = Client()
 client.load_client_config(
     "serving_client/serving_client_conf.prototxt")
-client.connect(["127.0.0.1:9303"])
+client.connect(["127.0.0.1:9393"])
 
 seq = Sequential([
     File2Image(), Resize(256), CenterCrop(224), RGB2BGR(), Transpose((2, 0, 1)),

python/examples/xpu/bert/README.md

 
 ## Prepare
+### download model and extract
+```
+wget https://paddle-inference-dist.cdn.bcebos.com/PaddleLite/models_and_data_for_unittests/bert_base_chinese.tar.gz
+tar zxvf bert_base_chinese.tar.gz
+```
 ### convert model
 ```
-python -m paddle_serving_client.convert --dirname infer_bert-base-chinese_ft_model_4000.pdparams
+python3 -m paddle_serving_client.convert --dirname bert_base_chinese --model_filename bert_base_chinese/model.pdmodel --params_filename bert_base_chinese/model.pdiparams
+```
+### or, you can get the serving saved model directly
+```
+wget https://paddle-serving.bj.bcebos.com/models/xpu/bert.tar.gz
+tar zxvf bert.tar.gz 
+```
+### Getting Dict and Sample Dataset
+
+```
+sh get_data.sh
 ```
+this script will download Chinese Dictionary File vocab.txt and Chinese Sample Data data-c.txt
 
 ## RPC Service
 
 ### Start Service
 
 ```
-pytyon bert_web_service.py serving_server 7703
+python3 bert_web_service.py serving_server 7703
 ```
 
 ### Client Prediction
 
 ```
-python bert_client.py
+head data-c.txt | python3 bert_client.py --model serving_client/serving_client_conf.prototxt
 ```

python/examples/xpu/bert/get_data.sh

+wget https://paddle-serving.bj.bcebos.com/bert_example/data-c.txt --no-check-certificate
+wget https://paddle-serving.bj.bcebos.com/bert_example/vocab.txt --no-check-certificate

python/examples/xpu/ernie/README.md

 
 ## Prepare
+### download model and extract
+```
+wget https://paddle-inference-dist.cdn.bcebos.com/PaddleLite/models_and_data_for_unittests/ernie.tar.gz
+tar zxvf ernie.tar.gz
+```
 ### convert model
 ```
-python3 -m paddle_serving_client.convert --dirname erine
+python3 -m paddle_serving_client.convert --dirname ernie
+```
+### or, you can get the serving saved model directly
+```
+wget https://paddle-serving.bj.bcebos.com/models/xpu/ernie.tar.gz
+tar zxvf ernie.tar.gz 
+```
+### Getting Dict and Sample Dataset
+
+```
+sh get_data.sh
 ```
+this script will download Chinese Dictionary File vocab.txt and Chinese Sample Data data-c.txt
 
 ## RPC Service
 

python/examples/xpu/ernie/ernie_client.py

@@ -23,7 +23,7 @@ args = benchmark_args()
 
 reader = ChineseErnieReader({"max_seq_len": 128})
 fetch = ["save_infer_model/scale_0"]
-endpoint_list = ['127.0.0.1:7704']
+endpoint_list = ['127.0.0.1:12000']
 client = Client()
 client.load_client_config(args.model)
 client.connect(endpoint_list)

python/examples/xpu/ernie/get_data.sh

+wget https://paddle-serving.bj.bcebos.com/bert_example/data-c.txt --no-check-certificate
+wget https://paddle-serving.bj.bcebos.com/bert_example/vocab.txt --no-check-certificate

python/examples/xpu/fit_a_line_xpu/README.md

@@ -8,15 +8,10 @@
 sh get_data.sh
 ```
 
-
-
 ## RPC service
 
 ### Start server
-``` shell
-python test_server.py uci_housing_model/
-```
-You can alse use the following code to start the RPC service 
+You can use the following code to start the RPC service 
 ```shell
 python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9393 --use_lite --use_xpu --ir_optim
 ```
@@ -29,19 +24,17 @@ The `paddlepaddle` package is used in `test_client.py`, and you may need to down
 python test_client.py uci_housing_client/serving_client_conf.prototxt
 ```
 
-
-
 ## HTTP service
 
 ### Start server
 
 Start a web service with default web service hosting modules:
 ``` shell
-python test_server.py
+python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9393 --use_lite --use_xpu --ir_optim --name uci
 ```
 
 ### Client prediction
 
 ``` shell
-curl -H "Content-Type:application/json" -X POST -d '{"feed":[{"x": [0.0137, -0.1136, 0.2553, -0.0692, 0.0582, -0.0727, -0.1583, -0.0584, 0.6283, 0.4919, 0.1856, 0.0795, -0.0332]}], "fetch":["price"]}' http://127.0.0.1:9292/uci/prediction
+curl -H "Content-Type:application/json" -X POST -d '{"feed":[{"x": [0.0137, -0.1136, 0.2553, -0.0692, 0.0582, -0.0727, -0.1583, -0.0584, 0.6283, 0.4919, 0.1856, 0.0795, -0.0332]}], "fetch":["price"]}' http://127.0.0.1:9393/uci/prediction
 ```

python/examples/xpu/fit_a_line_xpu/README_CN.md

@@ -32,8 +32,6 @@ python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --po
 python test_client.py uci_housing_client/serving_client_conf.prototxt
 ```
 
-
-
 ## HTTP服务
 
 ### 开启服务端
@@ -41,11 +39,11 @@ python test_client.py uci_housing_client/serving_client_conf.prototxt
 通过下面的一行代码开启默认web服务：
 
 ``` shell
-python test_server.py
+python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9393 --use_lite --use_xpu --ir_optim --name uci
 ```
 
 ### 客户端预测
 
 ``` shell
-curl -H "Content-Type:application/json" -X POST -d '{"feed":[{"x": [0.0137, -0.1136, 0.2553, -0.0692, 0.0582, -0.0727, -0.1583, -0.0584, 0.6283, 0.4919, 0.1856, 0.0795, -0.0332]}], "fetch":["price"]}' http://127.0.0.1:9292/uci/prediction
+curl -H "Content-Type:application/json" -X POST -d '{"feed":[{"x": [0.0137, -0.1136, 0.2553, -0.0692, 0.0582, -0.0727, -0.1583, -0.0584, 0.6283, 0.4919, 0.1856, 0.0795, -0.0332]}], "fetch":["price"]}' http://127.0.0.1:9393/uci/prediction
 ```

python/examples/xpu/fit_a_line_xpu/test_multi_process_client.py

-# Copyright (c) 2020 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.
-
-from paddle_serving_client import Client
-from paddle_serving_client.utils import MultiThreadRunner
-import paddle
-import numpy as np
-
-
-def single_func(idx, resource):
-    client = Client()
-    client.load_client_config(
-        "./uci_housing_client/serving_client_conf.prototxt")
-    client.connect(["127.0.0.1:9293", "127.0.0.1:9292"])
-    x = [
-        0.0137, -0.1136, 0.2553, -0.0692, 0.0582, -0.0727, -0.1583, -0.0584,
-        0.6283, 0.4919, 0.1856, 0.0795, -0.0332
-    ]
-    x = np.array(x)
-    for i in range(1000):
-        fetch_map = client.predict(feed={"x": x}, fetch=["price"])
-        if fetch_map is None:
-            return [[None]]
-    return [[0]]
-
-
-multi_thread_runner = MultiThreadRunner()
-thread_num = 4
-result = multi_thread_runner.run(single_func, thread_num, {})
-if None in result[0]:
-    exit(1)

python/examples/xpu/fit_a_line_xpu/test_server.py

-# Copyright (c) 2020 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.
-# pylint: disable=doc-string-missing
-
-from paddle_serving_server.web_service import WebService
-import numpy as np
-
-
-class UciService(WebService):
-    def preprocess(self, feed=[], fetch=[]):
-        feed_batch = []
-        is_batch = True
-        new_data = np.zeros((len(feed), 1, 13)).astype("float32")
-        for i, ins in enumerate(feed):
-            nums = np.array(ins["x"]).reshape(1, 1, 13)
-            new_data[i] = nums
-        feed = {"x": new_data}
-        return feed, fetch, is_batch
-
-
-uci_service = UciService(name="uci")
-uci_service.load_model_config("uci_housing_model")
-uci_service.prepare_server(
-    workdir="workdir", port=9393, use_lite=True, use_xpu=True, ir_optim=True)
-uci_service.run_rpc_service()
-uci_service.run_web_service()

python/examples/xpu/vgg19/README.md

 
 ## Prepare
+### download model and extract
+```
+wget https://paddle-inference-dist.bj.bcebos.com/PaddleLite/models_and_data_for_unittests/VGG19.tar.gz
+tar zxvf VGG19.tar.gz
+```
 ### convert model
 ```
-python -m paddle_serving_client.convert --dirname VGG19
+python3 -m paddle_serving_client.convert --dirname VGG19
+```
+### or, you can get the serving saved model directly
+```
+wget https://paddle-serving.bj.bcebos.com/models/xpu/vgg19.tar.gz
+tar zxvf vgg19.tar.gz 
 ```
 
 ## RPC Service
@@ -10,7 +20,7 @@ python -m paddle_serving_client.convert --dirname VGG19
 ### Start Service
 
 ```
-python -m paddle_serving_server.serve --model serving_server --port 7702 --use_lite --use_xpu --ir_optim
+python3 -m paddle_serving_server.serve --model serving_server --port 7702 --use_lite --use_xpu --ir_optim
 ```
 
 ### Client Prediction