To avoid the trouble of environment setup, [running in Docker container](#running-in-docker-container) is highly recommended. Otherwise follow the guidelines below to install the dependencies manually.
There are 3 ways to use the repository. According to the degree of difficulty, the 3 ways can be divided into Easy, Medium and Hard.
## Easy: Get the Basic Funcition Without Your Own Mechine
If you are in touch with PaddleSpeech for the first time and want to experience it easily without your own mechine. We recommand you to go to aistudio to experience the PaddleSpeech project. There is a step-by-step tutorial for PaddleSpeech and you can use the basic function of PaddleSpeech with a free machine.
## Prerequisites for Medium and Hard
## Prerequisites
- Python >= 3.7
- Python >= 3.7
- PaddlePaddle latest version (please refer to the [Installation Guide](https://www.paddlepaddle.org.cn/documentation/docs/en/beginners_guide/index_en.html))
- PaddlePaddle latest version (please refer to the [Installation Guide](https://www.paddlepaddle.org.cn/documentation/docs/en/beginners_guide/index_en.html))
- Only Linux is supported
- Hip: Do not use command `sh` instead of command `bash`
## Medium: Get the Basic Funciton on Your Mechine
## Simple Setup
If you want to install the paddlespeech on your own mechine. There are 3 steps you need to do.
For user who working on `Ubuntu` with `root` privilege.
If you want to use the basic function of the repo, you can use:
### Install the Conda
The first setup is installing the conda. Conda is environment management system. You can go to [minicoda](https://docs.conda.io/en/latest/miniconda.html) to select a version (py>=3.7) and install it by yourself or you can use the scripts below:
Then you can create an conda virtual environment using the script:
```bash
conda create -n py37 python=3.7
```
```
pip install -e .[develop]
Activate the conda virtual environment:
```bash
conda activate py37
```
```
For user who only needs the basic function of paddlespeech, using conda to do installing is recommended.
Intall the conda dependencies
You can go to [minicoda](https://docs.conda.io/en/latest/miniconda.html) to select a version and install it by yourself, or you can use the scripts below to install the last miniconda version.
After installing the conda, run the setup.sh to complete the installing process.
### Install the PaddleSpeech Using PiP
To Install the PaddleSpeech, there are two methods. You can use the script below:
```bash
```bash
bash setup.sh
pip install paddlespeech
```
```
If you install the paddlespeech by pip, you can use it to help you to build your own model. However, you can not use the ready-made examples in paddlespeech.
## Setup (Other Platform)
If you want to use the ready-made examples in paddlespeech, you need to clone the repository and install the paddlespeech package.
- Make sure these libraries or tools in [dependencies](./dependencies.md) installed. More information please see: `setup.py `and ` tools/Makefile`.
```bash
- The version of `swig` should >= 3.0
https://github.com/PaddlePaddle/PaddleSpeech.git
- we will do more to simplify the install process.
## Into the PaddleSpeech
cd PaddleSpeech
pip install .
```
## Hard: Get the Full Funciton on Your Mechine
### Prerequisites
- choice 1: working with `ubuntu` Docker Container.
or
## Running in Docker Container (optional)
- choice 2: working on `Ubuntu` with `root` privilege.
To avoid the trouble of environment setup, [running in Docker container](#running-in-docker-container) is highly recommended. Otherwise If you work on `Ubuntu` with `root` privilege, you can skip the next step.
### Choice 1: Running in Docker Container (Recommand)
Docker is an open source tool to build, ship, and run distributed applications in an isolated environment. A Docker image for this project has been provided in [hub.docker.com](https://hub.docker.com) with all the dependencies installed. This Docker image requires the support of NVIDIA GPU, so please make sure its availiability and the [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) has been installed.
Docker is an open source tool to build, ship, and run distributed applications in an isolated environment. A Docker image for this project has been provided in [hub.docker.com](https://hub.docker.com) with all the dependencies installed. This Docker image requires the support of NVIDIA GPU, so please make sure its availiability and the [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) has been installed.
@ -55,22 +103,22 @@ Take several steps to launch the Docker image: