Install on Linux via PIP¶
Environmental preparation¶
1.1 PREQUISITES¶
Linux Version (64 bit)
CentOS 6 (GPU Version Supports CUDA 9.0/9.1/9.2/10.0/10.1, only supports single card)**
CentOS 7 (GPUVersion Supports CUDA 9.0/9.1/9.2/10.0/10.1, CUDA 9.1 only supports single card)**
Ubuntu 14.04 (GPUVersion Supports CUDA 10.0/10.1)
Ubuntu 16.04 (GPUVersion Supports CUDA 9.0/9.1/9.2/10.0/10.1)
Ubuntu 18.04 (GPUVersion Supports CUDA 10.0/10.1)
Python Version: 2.7.15+/3.5.1+/3.6/3.7/3.8 (64 bit)
pip or pip3 Version 20.2.2+ (64 bit)
1.2 How to check your environment¶
You can use the following commands to view the local operating system and bit information
uname -m && cat /etc/*release
Confirm that the Python where you need to install PaddlePaddle is your expected location, because your computer may have multiple Python
If you are using Python 2, use the following command to output Python path. Depending on the environment, you may need to replace Python in all command lines in the description with specific Python path
which python
If you are using Python 3, use the following command to output Python path. Depending on your environment, you may need to replace Python 3 in all command lines in the instructions with Python or specific Python path
which python3
You need to confirm whether the version of Python meets the requirements
If you are using Python 2, use the following command to confirm that it is 2.7.15+
python --version
If you are using Python 3, use the following command to confirm that it is 3.5.1+/3.6/3.7/3.8
python3 --version
It is required to confirm whether the version of pip meets the requirements. The version of pip is required to be 20.2.2+
If you are using Python 2
python -m ensurepip
python -m pip --version
If you are using Python 3
python3 -m ensurepip
python3 -m pip --version
You need to confirm that Python and pip are 64bit, and the processor architecture is x86_64(or called x64、Intel 64、AMD64). Currently, paddlepaddle does not support arm64 architecture. The first line below outputs “64bit”, and the second line outputs “x86_64”, “x64” or “AMD64”
If you are using Python 2
python -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
If you are using Python 3
python3 -c "import platform;print(platform.architecture()[0]);print(platform.machine())"
The installation package provided by default requires computer support for MKL
If you do not know the machine environment, please download and useQuick install script, for instructions please refer tohere。
INSTALLATION¶
If you installed Python via Homebrew or the Python website, pip
was installed with it. If you installed Python 3.x, then you will be using the command pip3
.
Choose CPU/GPU¶
If your computer doesn’t have NVIDIA® GPU, please install the CPU Version of PaddlePaddle
If your computer has NVIDIA® GPU, please make sure that the following conditions are met and install the GPU Version of PaddlePaddle
CUDA toolkit 9.0/10.0 with cuDNN v7.6+(for multi card support, NCCL2.3.7 or higher)
CUDA toolkit 10.1/10.2 with cuDNN v7.6+(for multi card support, NCCL2.3.7 or higher)
CUDA toolkit 11.0 with cuDNN v8.0.4(for multi card support, NCCL2.3.7 or higher)
Hardware devices with GPU computing power over 1.0
You can refer to NVIDIA official documents for installation process and configuration method of CUDA and cudnn. Please refer to CUDA,cuDNN
If you need to use a multi-card environment, please make sure that you have installed nccl2 correctly, or install nccl2 according to the following instructions (here are the installation instructions of nccl2 under CUDA9 and cuDNN7. For more version installation information, please refer to NVIDIA Official Website):
Centos system can refer to the following commands
wget http://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
yum update -y
yum install -y libnccl-2.3.7-2+cuda9.0 libnccl-devel-2.3.7-2+cuda9.0 libnccl-static-2.3.7-2+cuda9.0
Ubuntu system can refer to the following commands
wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb
dpkg -i nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb
sudo apt-get install -y libnccl2=2.3.7-1+cuda9.0 libnccl-dev=2.3.7-1+cuda9.0
Installation Step¶
You can choose the following version of PaddlePaddle to start installation:
2.1 CPU Versoion of PaddlePaddle¶
python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
2.2 GPU Version of PaddlePaddle¶
2.2.1 CUDA9.0 PaddlePaddle
python -m pip install paddlepaddle-gpu==2.0.2.post90 -f https://paddlepaddle.org.cn/whl/mkl/stable.html
2.2.2 CUDA10.0 PaddlePaddle
python -m pip install paddlepaddle-gpu==2.0.2.post100 -f https://paddlepaddle.org.cn/whl/mkl/stable.html
2.2.3 CUDA10.1 PaddlePaddle
python -m pip install paddlepaddle-gpu==2.0.2.post101 -f https://paddlepaddle.org.cn/whl/mkl/stable.html
2.2.4 CUDA10.2 PaddlePaddle
python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
2.2.5 CUDA11.0 PaddlePaddle
python -m pip install paddlepaddle-gpu==2.0.2.post110 -f https://paddlepaddle.org.cn/whl/mkl/stable.html
Note:
Please confirm that the Python where you need to install PaddlePaddle is your expected location, because your computer may have multiple Python. Depending on the environment, you may need to replace Python in all command lines in the instructions with Python 3 or specific Python path.
If you want to use the tsinghua pypi, you can use the following command:
python3 -m pip install paddlepaddle-gpu==[Version] -i https://pypi.tuna.tsinghua.edu.cn/simple
If you want to install the Paddle package built with
tensorrt
, you can use the following command:python3 -m pip install paddlepaddle-gpu==[版本号] -f https://paddlepaddle.org.cn/whl/stable/tensorrt.html
If you want to install the Paddle package with
openblas
, you can use the following command:python3 -m pip install paddlepaddle-gpu==[版本号] -f https://paddlepaddle.org.cn/whl/openblas/stable.html
Verify installation¶
After the installation is complete, you can use python
or python3
to enter the Python interpreter and then use import paddle
and paddle.utils.run_check()
If PaddlePaddle is installed successfully!
appears, to verify that the installation was successful.
How to uninstall¶
Please use the following command to uninstall PaddlePaddle:
*CPU version of PaddlePaddle*:
python -m pip uninstall paddlepaddle
orpython3 -m pip uninstall paddlepaddle
*GPU version of PaddlePaddle*:
python -m pip uninstall paddlepaddle-gpu
orpython3 -m pip uninstall paddlepaddle-gpu