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Ascend NPU PaddlePaddle Installation Tutorial

Currently, PaddleX supports the Ascend 910B chip (more models are under support. If you have a related need for other models, please submit an issue to inform us). The Ascend driver version is 23.0.3. Considering the differences in environments, we recommend using the Ascend development image provided by PaddlePaddle to complete the environment preparation.

1. Docker Environment Preparation

  • Pull the image. This image is only for the development environment and does not contain a pre-compiled PaddlePaddle installation package. The image has CANN-8.0.RC2, the Ascend operator library, installed by default. 
    # For X86 architecture
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80RC2-ubuntu20-npu-base-x86_64-gcc84
# For Aarch64 architecture
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80RC2-ubuntu20-npu-base-aarch64-gcc84
  • Start the container with the following command. ASCEND_RT_VISIBLE_DEVICES specifies the visible NPU card numbers. 
    docker run -it --name paddle-npu-dev -v $(pwd):/work \
    --privileged --network=host --shm-size=128G -w=/work \
    -v /usr/local/Ascend/driver:/usr/local/Ascend/driver \
    -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
    -v /usr/local/dcmi:/usr/local/dcmi \
    -e ASCEND_RT_VISIBLE_DEVICES="0,1,2,3,4,5,6,7" \
    ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80RC2-ubuntu20-$(uname -m)-gcc84 /bin/bash

2. Install Paddle Package

  • Download and install the Python wheel installation package 
    # Note: You need to install the CPU version of PaddlePaddle first
python -m pip install paddlepaddle -i https://www.paddlepaddle.org.cn/packages/nightly/cpu
python -m pip install paddle-custom-npu -i https://www.paddlepaddle.org.cn/packages/nightly/npu
  • CANN-8.0.RC2 does not support some versions of numpy and opencv, it is recommended to install the specified versions. 
    python -m pip install numpy==1.26.4
python -m pip install opencv-python==3.4.18.65
  • Set environment variables on the arm machine (not required for x86 environment) 
    # Solve the error reported by libgomp on the arm machine
# "libgomp cannot allocate memory in static TLS block"
export LD_PRELOAD=/usr/lib/aarch64-linux-gnu/libgomp.so.1:$LD_PRELOAD
  • After verifying that the installation package is installed, run the following command 
    python -c "import paddle; paddle.utils.run_check()"
    The expected output is as follows
Running verify PaddlePaddle program ...
PaddlePaddle works well on 1 npu.
PaddlePaddle works well on 8 npus.
PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.

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