CANN:8.1.rc1
HDK:25.2.0
python:3.10.17
torch:2.1.0
torch_npu:2.1.0.post17
scikit-learn:1.1.3

docker run -it  -u root \
--net=host --shm-size=5g \
--device=/dev/davinci_manager \
--device=/dev/hisi_hdc \
--device=/dev/davinci0 \
--device=/dev/davinci1 \
-v /usr/local/dcmi:/usr/local/dcmi \
-v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
-v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
-v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
-v /etc/ascend_install.info:/etc/ascend_install.info \
-v /usr/share/zoneinfo/Asia/Shanghai:/etc/localtime \
-v /home:/home/ \
--name schnet_test \
--entrypoint=/bin/bash \
-it swr.cn-south-1.myhuaweicloud.com/ascendhub/cann:8.1.rc1-910b-openeuler24.03-py3.10

wget https://download.pytorch.org/whl/cpu/torch-2.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
https://gitcode.com/Ascend/pytorch/releases/download/v7.2.0-pytorch2.1.0/torch_npu-2.1.0.post17-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

pip3 install torch-2.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
pip3 install torch_npu-2.1.0.post17-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

yum install -y gcc gcc-c++ libstdc++-devel libstdc++ make cmake openblas-devel openblas-static util-linux

pip3 install torch_cluster torch_geometric --no-build-isolation
pip3 install ase

git clone 
cd SchNet
export CPLUS_INCLUDE_PATH=/usr/include/c++/12/:$CPLUS_INCLUDE_PATH
bash install.sh -v Ascend910B3
cd CustomOp/build_out
./custom_opp_openEuler_aarch64.run
cd ../../CppExtensionInvocation/
bash build_and_run.sh

source /usr/local/Ascend/ascend-toolkit/set_env.sh
cd ../ && python3 QM9.py