如果看到以上的消息,那就表示编译构建成功了,接下来只要把生成的whl包使用pip进行安装即可:
$ python3 -m pip install ./output/mindspore_gl_gpu-0.1-cp39-cp39-linux_x86_64.whlProcessing ./output/mindspore_gl_gpu-0.1-cp39-cp39-linux_x86_64.whlRequirement already satisfied: Cython in /home/dechin/.local/lib/python3.9/site-packages (from mindspore-gl-gpu==0.1) (0.29.32)Requirement already satisfied: astpretty in /home/dechin/.local/lib/python3.9/site-packages (from mindspore-gl-gpu==0.1) (3.0.0)Requirement already satisfied: ast-decompiler>=0.3.2 in /home/dechin/.local/lib/python3.9/site-packages (from mindspore-gl-gpu==0.1) (0.7.0)Requirement already satisfied: scikit-learn>=0.24.2 in /home/dechin/.local/lib/python3.9/site-packages (from mindspore-gl-gpu==0.1) (1.1.3)Requirement already satisfied: threadpoolctl>=2.0.0 in /home/dechin/.local/lib/python3.9/site-packages (from scikit-learn>=0.24.2->mindspore-gl-gpu==0.1) (3.1.0)Requirement already satisfied: joblib>=1.0.0 in /home/dechin/.local/lib/python3.9/site-packages (from scikit-learn>=0.24.2->mindspore-gl-gpu==0.1) (1.2.0)Requirement already satisfied: scipy>=1.3.2 in /home/dechin/anaconda3/envs/mindspore16/lib/python3.9/site-packages (from scikit-learn>=0.24.2->mindspore-gl-gpu==0.1) (1.5.3)Requirement already satisfied: numpy>=1.17.3 in /home/dechin/anaconda3/envs/mindspore16/lib/python3.9/site-packages (from scikit-learn>=0.24.2->mindspore-gl-gpu==0.1) (1.23.2)Installing collected packages: mindspore-gl-gpuSuccessfully installed mindspore-gl-gpu-0.1
我们可以用如下指令验证一下mindspore-gl是否安装成功(后面的告警信息是MindSpore产生的,不是mindspore-gl产生的,一般情况下,我们可以忽视掉):
$ python3 -c 'import mindspore_gl'[WARNING] ME(3662914:140594637309120,MainProcess):2022-11-09-17:22:29.348.03 [mindspore/run_check/_check_version.py:189] Cuda ['10.1', '11.1'] version(need by mindspore-gpu) is not found, please confirm that the path of cuda is set to the env LD_LIBRARY_PATH, please refer to the installation guidelines: https://www.mindspore.cn/install[WARNING] ME(3662914:140594637309120,MainProcess):2022-11-09-17:22:29.350.73 [mindspore/run_check/_check_version.py:189] Cuda ['10.1', '11.1'] version(need by mindspore-gpu) is not found, please confirm that the path of cuda is set to the env LD_LIBRARY_PATH, please refer to the installation guidelines: https://www.mindspore.cn/install[WARNING] ME(3662914:140594637309120,MainProcess):2022-11-09-17:22:29.351.54 [mindspore/run_check/_check_version.py:189] Cuda ['10.1', '11.1'] version(need by mindspore-gpu) is not found, please confirm that the path of cuda is set to the env LD_LIBRARY_PATH, please refer to the installation guidelines: https://www.mindspore.cn/install[WARNING] ME(3662914:140594637309120,MainProcess):2022-11-09-17:22:29.352.40 [mindspore/run_check/_check_version.py:189] Cuda ['10.1', '11.1'] version(need by mindspore-gpu) is not found, please confirm that the path of cuda is set to the env LD_LIBRARY_PATH, please refer to the installation guidelines: https://www.mindspore.cn/install[WARNING] ME(3662914:140594637309120,MainProcess):2022-11-09-17:22:29.352.94 [mindspore/run_check/_check_version.py:189] Cuda ['10.1', '11.1'] version(need by mindspore-gpu) is not found, please confirm that the path of cuda is set to the env LD_LIBRARY_PATH, please refer to the installation guidelines: https://www.mindspore.cn/install[WARNING] ME(3662914:140594637309120,MainProcess):2022-11-09-17:22:29.353.43 [mindspore/run_check/_check_version.py:189] Cuda ['10.1', '11.1'] version(need by mindspore-gpu) is not found, please confirm that the path of cuda is set to the env LD_LIBRARY_PATH, please refer to the installation guidelines: https://www.mindspore.cn/install[WARNING] ME(3662914:140594637309120,MainProcess):2022-11-09-17:22:29.353.91 [mindspore/run_check/_check_version.py:189] Cuda ['10.1', '11.1'] version(need by mindspore-gpu) is not found, please confirm that the path of cuda is set to the env LD_LIBRARY_PATH, please refer to the installation guidelines: https://www.mindspore.cn/install
经验总结扩展阅读
- PGL Paddle Graph Learning 关于图计算&图学习的基础知识概览:前置知识点学习
- 论文笔记 - GRAD-MATCH: A Gradient Matching Based Data Subset Selection For Efficient Learning
- 论文笔记 - SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios
- 谣言检测《Rumor Detection with Self-supervised Learning on Texts and Social Graph》
- RDCL 谣言检测——《Towards Robust False Information Detection on Social Networks with Contrastive Learning》
- Learning Records JavaScript进阶
- GLA 论文解读《Label-invariant Augmentation for Semi-Supervised Graph Classification》
- GGD 论文解读《Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination》
- Learning Records 计算机网络
- Nebula Graph介绍和SpringBoot环境连接和查询