Docker installation guide

PaddlePaddle provide the Docker image. Docker is a lightweight container utilities. The performance of PaddlePaddle in Docker container is basically as same as run it in a normal linux. The Docker is a very convenient way to deliver the binary release for linux programs.


The Docker image is the recommended way to run PaddlePaddle

PaddlePaddle Docker images

There are 12 images for PaddlePaddle, and the name is paddle-dev/paddle, tags are:

  normal devel demo
CPU cpu-latest cpu-devel-latest cpu-demo-latest
GPU gpu-latest gpu-devel-latest gpu-demo-latest
CPU WITHOUT AVX cpu-noavx-latest cpu-devel-noavx-latest cpu-demo-noavx-latest
GPU WITHOUT AVX gpu-noavx-latest gpu-devel-noavx-latest gpu-demo-noavx-latest

And the three columns are:

  • normal: The docker image only contains binary of PaddlePaddle.
  • devel: The docker image contains PaddlePaddle binary, source code and essential build environment.
  • demo: The docker image contains the dependencies to run PaddlePaddle demo.

And the four rows are:

  • CPU: CPU Version. Support CPU which has AVX instructions.
  • GPU: GPU Version. Support GPU, and cpu has AVX instructions.
  • CPU WITHOUT AVX: CPU Version, which support most CPU even doesn’t have AVX instructions.
  • GPU WITHOUT AVX: GPU Version, which support most CPU even doesn’t have AVX instructions.

User can choose any version depends on machine. The following script can help you to detect your CPU support AVX or not.

if cat /proc/cpuinfo | grep -q avx ; then echo "Support AVX"; else echo "Not support AVX"; fi

If the output is Support AVX, then you can choose the AVX version of PaddlePaddle, otherwise, you need select noavx version of PaddlePaddle. For example, the CPU develop version of PaddlePaddle is paddle-dev/paddle:cpu-devel-latest.

The PaddlePaddle images don’t contain any entry command. You need to write your entry command to use this image. See Remote Access part or just use following command to run a bash

docker run -it paddledev/paddle:cpu-latest /bin/bash

Download and Run Docker images

You have to install Docker in your machine which has linux kernel version 3.10+ first. You can refer to the official guide for further information.

You can use docker pull ` to download images first, or just launch a container with :code:`docker run :

docker run -it paddledev/paddle:cpu-latest

If you want to launch container with GPU support, you need to set some environment variables at the same time:

export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest

Some notes for docker


Since Docker is based on the lightweight virtual containers, the CPU computing performance maintains well. And GPU driver and equipments are all mapped to the container, so the GPU computing performance would not be seriously affected.

If you use high performance nic, such as RDMA(RoCE 40GbE or IB 56GbE), Ethernet(10GbE), it is recommended to use config “-net = host”.

Remote access

If you want to enable ssh access background, you need to build an image by yourself. Please refer to official guide for further information.

Following is a simple Dockerfile with ssh:

FROM paddledev/paddle:cpu-latest

MAINTAINER PaddlePaddle dev team <>

RUN apt-get update
RUN apt-get install -y openssh-server
RUN mkdir /var/run/sshd
RUN echo 'root:root' | chpasswd

RUN sed -ri 's/^PermitRootLogin\s+.*/PermitRootLogin yes/' /etc/ssh/sshd_config
RUN sed -ri 's/UsePAM yes/#UsePAM yes/g' /etc/ssh/sshd_config


CMD    ["/usr/sbin/sshd", "-D"]

Then you can build an image with Dockerfile and launch a container:

# cd into Dockerfile directory
docker build . -t paddle_ssh
# run container, and map host machine port 8022 to container port 22
docker run -d -p 8022:22 --name paddle_ssh_machine paddle_ssh

Now, you can ssh on port 8022 to access the container, username is root, password is also root:

ssh -p 8022 root@YOUR_HOST_MACHINE

You can stop and delete the container as following:

# stop
docker stop paddle_ssh_machine
# delete
docker rm paddle_ssh_machine