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PaddlePaddle Local Installation Tutorial

When installing PaddlePaddle, you can choose to install it via Docker or pip.

Installing PaddlePaddle via Docker

If you choose to install via Docker, please refer to the following commands to use the official Docker image of the PaddlePaddle framework to create a container named paddlex and map the current working directory to the /paddle directory inside the container:

If your Docker version >= 19.03, please use:

# For CPU users:
docker run --name paddlex -v $PWD:/paddle --shm-size=8G --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:3.0.0 /bin/bash

# For GPU users:
# gpu，requires GPU driver version ≥450.80.02 (Linux) or ≥452.39 (Windows)
docker run --gpus all --name paddlex -v $PWD:/paddle --shm-size=8G --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:3.0.0-gpu-cuda11.8-cudnn8.9-trt8.6 /bin/bash

# gpu，requires GPU driver version ≥550.54.14 (Linux) or ≥550.54.14 (Windows)
docker run --gpus all --name paddlex -v $PWD:/paddle  --shm-size=8G --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:3.0.0-gpu-cuda12.6-cudnn9.5-trt10.5 /bin/bash
  • If your Docker version <= 19.03 and >= 17.06, please use:
Click Here 
# For CPU users:
docker run --name paddlex -v $PWD:/paddle --shm-size=8G --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:3.0.0 /bin/bash

# For GPU users:
# CUDA 11.8 users
nvidia-docker run --name paddlex -v $PWD:/paddle --shm-size=8G --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:3.0.0-gpu-cuda11.8-cudnn8.9-trt8.6 /bin/bash

# CUDA 12.3 users
nvidia-docker run --name paddlex -v $PWD:/paddle  --shm-size=8G --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:3.0.0-gpu-cuda12.6-cudnn9.5-trt10.5 /bin/bash

  • If your Docker version <= 17.06, please update your Docker.

  • Note: For more official PaddlePaddle Docker images, please refer to the PaddlePaddle official website

To use Paddle Inference TensorRT Subgraph Engine, install TensorRT by executing the following instructions in the 'paddlex' container that has just been started

python -m pip install /usr/local/TensorRT-8.6.1.6/python/tensorrt-8.6.1-cp310-none-linux_x86_64.whl

Installing PaddlePaddle via pip

If you choose to install via pip, please refer to the following commands to install PaddlePaddle in your current environment using pip:

# CPU
python -m pip install paddlepaddle==3.0.0 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/

# gpu，requires GPU driver version ≥450.80.02 (Linux) or ≥452.39 (Windows)
 python -m pip install paddlepaddle-gpu==3.0.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/

# gpu，requires GPU driver version ≥550.54.14 (Linux) or ≥550.54.14 (Windows)
 python -m pip install paddlepaddle-gpu==3.0.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/

Note: For more PaddlePaddle Wheel versions, please refer to the PaddlePaddle official website.

For installing PaddlePaddle on other hardware, please refer to PaddleX Multi-hardware Usage Guide.

After installation, you can verify if PaddlePaddle is successfully installed using the following command:

python -c "import paddle; print(paddle.__version__)"
If the installation is successful, the following content will be output:

3.0.0-rc0

If you want to use the Paddle Inference TensorRT Subgraph Engine, after installing Paddle, you need to refer to the TensorRT Documentation to install the corresponding version of TensorRT:

  • For PaddlePaddle with CUDA 11.8, the compatible TensorRT version is 8.x (where x >= 6). PaddleX has completed compatibility tests of Paddle-TensorRT on TensorRT 8.6.1.6, so it is strongly recommended to install TensorRT 8.6.1.6.
  • For PaddlePaddle with CUDA 12.6, the compatible TensorRT version is 10.x (where x >= 5), and it is recommended to install TensorRT 10.5.0.18.

Below is an example of installing TensorRT 8.6.1.6 using the "Tar File Installation" method in a CUDA 11.8 environment:

# Download TensorRT tar file
wget https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/secure/8.6.1/tars/TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-11.8.tar.gz
# Extract TensorRT tar file
tar xvf TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-11.8.tar.gz
# Install TensorRT wheel package
python -m pip install TensorRT-8.6.1.6/python/tensorrt-8.6.1-cp310-none-linux_x86_64.whl
# Add the absolute path of TensorRT's `lib` directory to LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:TensorRT-8.6.1.6/lib

❗ Note: If you encounter any issues during the installation process, feel free to submit an issue in the Paddle repository.

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