[Serving]add an serving example of tts

examples/audio/pp-tts/serving/README.md

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+([简体中文](./README_cn.md)|English)
+
+# PP-TTS Streaming Text-to-Speech Serving
+
+## Introduction
+This demo is an implementation of starting the streaming speech synthesis service and accessing the service.
+
+`Server` must be started in the docker, while `Client` does not have to be in the docker.
+
+**The streaming_pp_tts under the path of this article ($PWD) contains the configuration and code of the model, which needs to be mapped to the docker for use.**
+
+## Usage
+### 1. Server
+#### 1.1 Docker
+
+```bash
+docker pull registry.baidubce.com/paddlepaddle/fastdeploy_serving_cpu_only:22.09
+docker run -dit  --net=host --name fastdeploy --shm-size="1g" -v $PWD:/models registry.baidubce.com/paddlepaddle/fastdeploy_serving_cpu_only:22.09
+docker exec -it -u root fastdeploy bash
+```
+
+#### 1.2 Installation (inside the docker)
+```bash
+apt-get install build-essential python3-dev libssl-dev libffi-dev libxml2 libxml2-dev libxslt1-dev zlib1g-dev libsndfile1 language-pack-zh-hans wget zip
+pip3 install paddlespeech
+export LC_ALL="zh_CN.UTF-8"
+export LANG="zh_CN.UTF-8"
+export LANGUAGE="zh_CN:zh:en_US:en"
+```
+
+#### 1.3 Download models (inside the docker)
+```bash
+cd /models/streaming_pp_tts/1
+wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0.zip
+wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_onnx_0.2.0.zip
+unzip fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0.zip
+unzip mb_melgan_csmsc_onnx_0.2.0.zip
+```
+**For the convenience of users, we recommend that you use the command `docker -v` to map $PWD (streaming_pp_tts and the configuration and code of the model contained therein) to the docker path `/models`. You can also use other methods, but regardless of which method you use, the final model directory and structure in the docker are shown in the following figure.**
+
+```
+/models 
+│
+└───streaming_pp_tts                                                #Directory of the entire service model
+    │   config.pbtxt                                                #Configuration file of service model
+    │   stream_client.py                                            #Code of Client
+    │
+    └───1                                                           #Model version number
+        │   model.py                                                #Code to start the model
+        └───fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0       #Model file required by code
+        └───mb_melgan_csmsc_onnx_0.2.0                              #Model file required by code
+
+```
+
+#### 1.4 Start the server (inside the docker)
+
+```bash
+fastdeployserver --model-repository=/models --model-control-mode=explicit --load-model=streaming_pp_tts
+```
+Arguments:
+  - `model-repository`(required): Path of model storage.
+  - `model-control-mode`(required): The mode of loading the model. At present, you can use 'explicit'.
+  - `load-model`(required): Name of the model to be loaded.
+  - `http-port`(optional): Port for http service. Default: `8000`. This is not used in our example.
+  - `grpc-port`(optional): Port for grpc service. Default: `8001`.
+  - `metrics-port`(optional): Port for metrics service. Default: `8002`. This is not used in our example.
+
+### 2. Client
+#### 2.1 Installation
+```bash
+pip3 install tritonclient[all]
+```
+
+#### 2.2 Send request
+```bash
+python3 /models/streaming_pp_tts/stream_client.py
+```

examples/audio/pp-tts/serving/README_cn.md

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+(简体中文|[English](./README.md))
+
+# PP-TTS流式语音合成服务化部署
+
+## 介绍
+本文介绍了使用FastDeploy搭建流式语音合成服务的方法。
+
+服务端必须在docker内启动,而客户端不是必须在docker容器内.
+
+**本文所在路径($PWD)下的streaming_pp_tts里包含模型的配置和代码(服务端会加载模型和代码以启动服务),需要将其映射到docker中使用。**
+
+## 使用
+### 1. 服务端
+#### 1.1 Docker
+```bash
+docker pull registry.baidubce.com/paddlepaddle/fastdeploy_serving_cpu_only:22.09
+docker run -dit  --net=host --name fastdeploy --shm-size="1g" -v $PWD:/models registry.baidubce.com/paddlepaddle/fastdeploy_serving_cpu_only:22.09
+docker exec -it -u root fastdeploy bash
+```
+
+#### 1.2 安装(在docker内)
+```bash
+apt-get install build-essential python3-dev libssl-dev libffi-dev libxml2 libxml2-dev libxslt1-dev zlib1g-dev libsndfile1 language-pack-zh-hans wget zip
+pip3 install paddlespeech
+export LC_ALL="zh_CN.UTF-8"
+export LANG="zh_CN.UTF-8"
+export LANGUAGE="zh_CN:zh:en_US:en"
+```
+
+#### 1.3 下载模型(在docker内)
+```bash
+cd /models/streaming_pp_tts/1
+wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0.zip
+wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_onnx_0.2.0.zip
+unzip fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0.zip
+unzip mb_melgan_csmsc_onnx_0.2.0.zip
+```
+**为了方便用户使用，我们推荐用户使用1.1中的`docker -v`命令将$PWD(streaming_pp_tts及里面包含的模型的配置和代码)映射到了docker内的`/models`路径,用户也可以使用其他办法,但无论使用哪种方法,最终在docker内的模型目录及结构如下图所示。**
+
+```
+/models 
+│
+└───streaming_pp_tts                                              #整个服务模型文件夹
+    │   config.pbtxt                                              #服务模型配置文件
+    │   stream_client.py                                          #客户端代码
+    │
+    └───1                                                         #模型版本号,此处为1
+        │   model.py                                              #模型启动代码
+        └───fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0     #启动代码所需的模型文件
+        └───mb_melgan_csmsc_onnx_0.2.0                            #启动代码所需的模型文件
+
+```
+
+#### 1.4 启动服务端(在docker内)
+```bash
+fastdeployserver --model-repository=/models --model-control-mode=explicit --load-model=streaming_pp_tts
+```
+
+参数:
+  - `model-repository`(required): 整套模型streaming_pp_tts存放的路径.
+  - `model-control-mode`(required): 模型加载的方式,现阶段, 使用'explicit'即可.
+  - `load-model`(required): 需要加载的模型的名称.
+  - `http-port`(optional): HTTP服务的端口号. 默认: `8000`. 本示例中未使用该端口.
+  - `grpc-port`(optional): GRPC服务的端口号. 默认: `8001`.
+  - `metrics-port`(optional): 服务端指标的端口号. 默认: `8002`. 本示例中未使用该端口.
+
+### 2. 客户端
+#### 2.1 安装
+```bash
+pip3 install tritonclient[all]
+```
+
+#### 2.2 发送请求
+```bash
+python3 /models/streaming_pp_tts/stream_client.py
+```