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add the paddlenlp server
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‎applications/text_classification/hierarchical/deploy/SimpleServing/README.md‎

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# 基于PaddleNLP SimpleServing 的服务化部署
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## 目录
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- [环境准备](#环境准备)
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- [Server启动服务](#Server服务启动)
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- [其他参数设置](#其他参数设置)
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## 环境准备
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使用有SimpleServing功能的PaddleNLP版本
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```shell
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pip install paddlenlp --upgrade
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```
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## Server服务启动
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### 分类任务启动
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#### 启动 分类 Server 服务
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```bash
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paddlenlp server server:app --host 0.0.0.0 --port 8189
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```
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#### 分类任务发送服务
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```bash
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python client.py
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```
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## 其他参数设置
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可以在client端设置 `max_seq_len`, `batch_size`, `prob_limit` 参数
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```python
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data = {
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'data': {
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'text': texts,
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},
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'parameters': {
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'max_seq_len': args.max_seq_len,
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'batch_size': args.batch_size,
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'prob_limit': args.prob_limit
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}
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}
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```

‎applications/text_classification/hierarchical/deploy/SimpleServing/client.py‎

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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import requests
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import json
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# yapf: disable
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parser = argparse.ArgumentParser()
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parser.add_argument("--max_seq_len", default=128, type=int, help="The maximum total input sequence length after tokenization.")
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parser.add_argument("--batch_size", default=1, type=int, help="Batch size per GPU/CPU for predicting.")
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parser.add_argument("--prob_limit", default=0.5, type=float, help="The limitation of probability for the label.")
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args = parser.parse_args()
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# yapf: enable
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url = "http://0.0.0.0:8189/models/cls_hierarchical"
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headers = {"Content-Type": "application/json"}
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if __name__ == "__main__":
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texts = [
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'请问木竭胶囊能同高血压药、氨糖同时服吗？', '低压100*高压140*头涨，想吃点降压药。谢谢！', '脑穿通畸形易发人群有哪些',
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'幼儿乱吃丙硫氧嘧啶片怎么办，我也不知道她吃了几片', '如果是可以降血糖的话,血糖值7点多的大概需要吃几个疗程?'
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]
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data = {
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'data': {
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'text': texts,
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},
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'parameters': {
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'max_seq_len': args.max_seq_len,
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'batch_size': args.batch_size,
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'prob_limit': args.prob_limit
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}
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}
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r = requests.post(url=url, headers=headers, data=json.dumps(data))
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print(r.text)

‎applications/text_classification/hierarchical/deploy/SimpleServing/server.py‎

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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from paddlenlp import SimpleServer
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from paddlenlp.server import CustomModelHandler, MultiLabelClassificationPostHandler
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app = SimpleServer()
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app.register('cls_hierarchical',
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model_path="../../export",
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tokenizer_name='ernie-3.0-medium-zh',
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model_handler=CustomModelHandler,
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post_handler=MultiLabelClassificationPostHandler)

‎applications/text_classification/multi_class/deploy/SimpleServing/README.md‎

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# 基于PaddleNLP SimpleServing 的服务化部署
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## 目录
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- [环境准备](#环境准备)
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- [Server启动服务](#Server服务启动)
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- [其他参数设置](#其他参数设置)
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## 环境准备
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使用有SimpleServing功能的PaddleNLP版本
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```shell
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pip install paddlenlp >= 2.4.4
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```
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## Server服务启动
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### 分类任务启动
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#### 启动分类 Server 服务
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```bash
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paddlenlp server server:app --host 0.0.0.0 --port 8189
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```
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#### 启动分类 Client 服务
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```bash
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python client.py
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```
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## 其他参数设置
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可以在client端设置 `max_seq_len`, `batch_size` 参数
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```python
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data = {
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'data': {
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'text': texts,
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'text_pair': text_pairs if len(text_pairs) > 0 else None
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},
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'parameters': {
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'max_seq_len': args.max_seq_len,
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'batch_size': args.batch_size
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}
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}
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```

‎applications/text_classification/multi_class/deploy/SimpleServing/client.py‎

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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import requests
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import json
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# yapf: disable
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parser = argparse.ArgumentParser()
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parser.add_argument("--max_seq_len", default=128, type=int, help="The maximum total input sequence length after tokenization.")
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parser.add_argument("--batch_size", default=1, type=int, help="Batch size per GPU/CPU for predicting.")
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args = parser.parse_args()
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# yapf: enable
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url = "http://0.0.0.0:8189/models/cls_multi_class"
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headers = {"Content-Type": "application/json"}
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if __name__ == "__main__":
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texts = [
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'黑苦荞茶的功效与作用及食用方法', '交界痣会凸起吗', '检查是否能怀孕挂什么科', '鱼油怎么吃咬破吃还是直接咽下去',
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'幼儿挑食的生理原因是'
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]
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data = {
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'data': {
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'text': texts,
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},
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'parameters': {
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'max_seq_len': args.max_seq_len,
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'batch_size': args.batch_size
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}
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}
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r = requests.post(url=url, headers=headers, data=json.dumps(data))
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result_json = json.loads(r.text)
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print(result_json)

‎applications/text_classification/multi_class/deploy/SimpleServing/server.py‎

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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from paddlenlp import SimpleServer
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from paddlenlp.server import CustomModelHandler, MultiClassificationPostHandler
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app = SimpleServer()
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app.register('cls_multi_class',
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model_path="../../export",
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tokenizer_name='ernie-3.0-medium-zh',
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model_handler=CustomModelHandler,
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post_handler=MultiClassificationPostHandler)

‎applications/text_classification/multi_label/deploy/SimpleServing/README.md‎

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# 基于PaddleNLP SimpleServing 的服务化部署
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## 目录
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- [环境准备](#环境准备)
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- [Server启动服务](#Server服务启动)
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- [其他参数设置](#其他参数设置)
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## 环境准备
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使用有SimpleServing功能的PaddleNLP版本
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```shell
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pip install paddlenlp --upgrade
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```
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## Server服务启动
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### 分类任务启动
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#### 启动 分类 Server 服务
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```bash
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paddlenlp server server:app --host 0.0.0.0 --port 8189
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```
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#### 分类任务发送服务
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```bash
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python client.py
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```
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## 其他参数设置
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可以在client端设置 `max_seq_len`, `batch_size`, `prob_limit` 参数
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```python
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data = {
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'data': {
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'text': texts,
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},
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'parameters': {
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'max_seq_len': args.max_seq_len,
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'batch_size': args.batch_size,
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'prob_limit': args.prob_limit
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}
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}
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```

‎applications/text_classification/multi_label/deploy/SimpleServing/client.py‎

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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import requests
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import json
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# yapf: disable
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parser = argparse.ArgumentParser()
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parser.add_argument("--max_seq_len", default=128, type=int, help="The maximum total input sequence length after tokenization.")
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parser.add_argument("--batch_size", default=1, type=int, help="Batch size per GPU/CPU for predicting.")
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parser.add_argument("--prob_limit", default=0.5, type=float, help="The limitation of probability for the label.")
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args = parser.parse_args()
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# yapf: enable
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url = "http://0.0.0.0:8189/models/cls_multi_label"
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headers = {"Content-Type": "application/json"}
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if __name__ == "__main__":
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texts = [
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'原、被告另购置橱柜、碗架、电磁炉、电饭锅各一个归原告王某某所有。',
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'于是原告到儿子就读的幼儿园进行探望，被告碰见后对原告破口大骂，还不让儿子叫原告妈妈，而叫被告现在的妻子做妈妈。',
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'由我全额出资购买的联想台式电脑，我均依次放弃。'
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]
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data = {
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'data': {
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'text': texts,
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},
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'parameters': {
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'max_seq_len': args.max_seq_len,
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'batch_size': args.batch_size,
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'prob_limit': args.prob_limit
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}
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}
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r = requests.post(url=url, headers=headers, data=json.dumps(data))
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print(json.loads(r.text))

‎applications/text_classification/multi_label/deploy/SimpleServing/server.py‎

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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from paddlenlp import SimpleServer
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from paddlenlp.server import CustomModelHandler, MultiLabelClassificationPostHandler
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app = SimpleServer()
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app.register('cls_multi_label',
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model_path="../../export",
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tokenizer_name='ernie-3.0-medium-zh',
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model_handler=CustomModelHandler,
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post_handler=MultiLabelClassificationPostHandler)

‎model_zoo/ernie-health/cblue/README.md‎

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@@ -108,11 +108,22 @@ $ python train_spo.py --batch_size 12 --max_seq_length 300 --learning_rate 6e-5
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使用动态图训练结束之后，还可以将动态图参数导出成静态图参数，用于部署推理等，具体代码见export_model.py。静态图参数保存在`output_path`指定路径中。
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运行方式：
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1. 分类任务静态图模型导出
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```shell
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python export_model.py --train_dataset CHIP-CDN-2C --params_path=./checkpoint/model_900/ --output_path=./export
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```
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2. SPO任务静态图模型导出
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```shell
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python export_model.py --train_dataset CMeIE --params_path=./checkpoint/model_900/ --output_path=./export
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```
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3. NER任务静态图模型导出
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```shell
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python export_model.py --train_dataset CMeEE --params_path=./checkpoint/model_1500/ --output_path=./export
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```
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**NOTICE**: train_dataset分类任务选择填上训练数据集名称，params_path选择最好参数的模型的路径。
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[1] CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark [pdf](https://arxiv.org/abs/2106.08087) [git](https://github.com/CBLUEbenchmark/CBLUE) [web](https://tianchi.aliyun.com/specials/promotion/2021chinesemedicalnlpleaderboardchallenge)
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