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PaddleSpeech/docs/install.md

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Installation

To avoid the trouble of environment setup, running in Docker container is highly recommended. Otherwise follow the guidelines below to install the dependencies manually.

Prerequisites

Setup

  • Make sure these libraries or tools installed: pkg-config, flac, ogg, vorbis, boost and swig, e.g. installing them via apt-get:
sudo apt-get install -y pkg-config libflac-dev libogg-dev libvorbis-dev libboost-dev swig python3-dev

or, installing them via yum:

sudo yum install pkgconfig libogg-devel libvorbis-devel boost-devel python3-devel
wget https://ftp.osuosl.org/pub/xiph/releases/flac/flac-1.3.1.tar.xz
xz -d flac-1.3.1.tar.xz
tar -xvf flac-1.3.1.tar
cd flac-1.3.1
./configure
make
make install
  • Run the setup script for the remaining dependencies
git clone https://github.com/PaddlePaddle/DeepSpeech.git
cd DeepSpeech
pushd tools; make; popd
source tools/venv/bin/activate
bash setup.sh
  • Source venv before do experiment.
source tools/venv/bin/activate

Running in Docker Container

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 with all the dependencies installed, including the pre-built PaddlePaddle, CTC decoders, and other necessary Python and third-party packages. This Docker image requires the support of NVIDIA GPU, so please make sure its availiability and the nvidia-docker has been installed.

Take several steps to launch the Docker image:

  • Download the Docker image

For example, pull paddle 2.0.0 image:

nvidia-docker pull registry.baidubce.com/paddlepaddle/paddle:2.0.0-gpu-cuda10.1-cudnn7
  • Clone this repository
git clone https://github.com/PaddlePaddle/DeepSpeech.git
  • Run the Docker image
sudo nvidia-docker run --rm -it -v $(pwd)/DeepSpeech:/DeepSpeech registry.baidubce.com/paddlepaddle/paddle:2.0.0-gpu-cuda10.1-cudnn7 /bin/bash

Now you can execute training, inference and hyper-parameters tuning in the Docker container.

  • Install PaddlePaddle

For example, for CUDA 10.1, CuDNN7.5 install paddle 2.0.0:

python3 -m pip install paddlepaddle-gpu==2.0.0