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* add tts example * update example * update use fd engine * add tts python example * add readme * fix comment * change paddle model * fix readme style Co-authored-by: Jason <jiangjiajun@baidu.com>
81 lines
3.7 KiB
Markdown
81 lines
3.7 KiB
Markdown
([简体中文](./README_cn.md)|English)
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# PP-TTS Streaming Text-to-Speech Serving
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## Introduction
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This demo is an implementation of starting the streaming speech synthesis service and accessing the service.
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`Server` must be started in the docker, while `Client` does not have to be in the docker.
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**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.**
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## Usage
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### 1. Server
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#### 1.1 Docker
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```bash
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docker pull registry.baidubce.com/paddlepaddle/fastdeploy_serving_cpu_only:22.09
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docker run -dit --net=host --name fastdeploy --shm-size="1g" -v $PWD:/models registry.baidubce.com/paddlepaddle/fastdeploy_serving_cpu_only:22.09
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docker exec -it -u root fastdeploy bash
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```
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#### 1.2 Installation (inside the docker)
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```bash
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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
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python3 -m pip install --upgrade pip
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pip3 install -U fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
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pip3 install -U paddlespeech paddlepaddle
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export LC_ALL="zh_CN.UTF-8"
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export LANG="zh_CN.UTF-8"
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export LANGUAGE="zh_CN:zh:en_US:en"
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```
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#### 1.3 Download models (inside the docker, skippable)
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The model file will be downloaded and decompressed automatically. If you want to download manually, please use the following command.
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```bash
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cd /models/streaming_pp_tts/1
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wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0.zip
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wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_onnx_0.2.0.zip
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unzip fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0.zip
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unzip mb_melgan_csmsc_onnx_0.2.0.zip
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```
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**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.**
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```
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/models
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│
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└───streaming_pp_tts #Directory of the entire service model
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│ config.pbtxt #Configuration file of service model
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│ stream_client.py #Code of Client
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│
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└───1 #Model version number
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│ model.py #Code to start the model
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└───fastspeech2_cnndecoder_csmsc_streaming_onnx_1.0.0 #Model file required by code
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└───mb_melgan_csmsc_onnx_0.2.0 #Model file required by code
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```
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#### 1.4 Start the server (inside the docker)
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```bash
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fastdeployserver --model-repository=/models --model-control-mode=explicit --load-model=streaming_pp_tts
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```
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Arguments:
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- `model-repository`(required): Path of model storage.
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- `model-control-mode`(required): The mode of loading the model. At present, you can use 'explicit'.
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- `load-model`(required): Name of the model to be loaded.
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- `http-port`(optional): Port for http service. Default: `8000`. This is not used in our example.
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- `grpc-port`(optional): Port for grpc service. Default: `8001`.
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- `metrics-port`(optional): Port for metrics service. Default: `8002`. This is not used in our example.
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### 2. Client
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#### 2.1 Installation
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```bash
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pip3 install tritonclient[all]
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```
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#### 2.2 Send request
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```bash
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python3 /models/streaming_pp_tts/stream_client.py
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```
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