Hygon DCU PaddlePaddle Installation Tutorial

Currently, PaddleX supports Haiguang Z100 series chips. Considering environmental differences, we recommend using the officially released Haiguang DCU development image by PaddlePaddle, which is pre-installed with the Haiguang DCU basic runtime library (DTK).

1. Docker Environment Preparation

Pull the image. Note that this image is only for development environments and does not include pre-compiled PaddlePaddle installation packages.

docker pull registry.baidubce.com/device/paddle-dcu:dtk23.10.1-kylinv10-gcc73-py310

Start the container with the following command as a reference:

docker run -it --name paddle-dcu-dev -v `pwd`:/work \
  -w=/work --shm-size=128G --network=host --privileged  \
  --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
  registry.baidubce.com/device/paddle-dcu:dtk23.10.1-kylinv10-gcc73-py310 /bin/bash

2. Install PaddlePaddle Package

Within the started docker container, download and install the wheel package released by PaddlePaddle's official website. Note: The DCU version of PaddlePaddle framework only supports Hygon C86 architecture.

# Download and install the wheel package
pip install paddlepaddle-rocm -i https://www.paddlepaddle.org.cn/packages/nightly/dcu

After the installation package is installed, run the following command to verify it:

python -c "import paddle; paddle.utils.run_check()"

The expected output is as follows:

PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.

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