3.8 KiB
MindQuantum
- What is MindQuantum
- Installation
- Verifying Successful Installation
- Note
- Quick Start
- Docs
- Community
- Contributing
- License
What is MindQuantum
MindQuantum is a quantum machine learning framework developed by MindSpore and HiQ, that can be used to build and train different quantum neural networks. Thanks to the powerful algorithm of quantum software group of Huawei and High-performance automatic differentiation ability of MindSpore, MindQuantum can efficiently handle problems such as quantum chemical simulation and quantum approximation optimization with TOP1 performance, which provides an efficient platform for researchers, teachers and students to quickly design and verify quantum machine learning algorithms.
Installation
Confirming System Environment Information
- The hardware platform should be Linux CPU with avx supported.
- Refer to MindQuantum Installation Guide, install MindSpore, version 1.2.0 or later is required.
- See setup.py for the remaining dependencies.
Install by Source Code
1.Download Source Code from Gitee
cd ~
git clone https://gitee.com/mindspore/mindquantum.git
2.Compiling MindQuantum
cd ~/mindquantum
python setup.py install --user
Install by pip
pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.2.0-rc1/MindQuantum/ubuntu_x86/mindquantum-0.1.0-py3-none-any.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple
- When the network is connected, dependency items are automatically downloaded during .whl package installation. (For details about other dependency items, see setup.py). In other cases, you need to manually install dependency items.
Verifying Successful Installation
Successfully installed, if there is no error message such as No module named 'mindquantum' when execute the following command:
python -c 'import mindquantum'
Note
Please set the parallel core number before runing MindQuantum scripts. For example, if you want to set the parallel core number to 4, please run the command below:
export OMP_NUM_THREADS=4
For large servers, please set the number of parallel kernels appropriately according to the size of the model to achieve optimal results.
Quick Start
For more details about how to build a parameterized quantum circuit and a quantum neural network and how to train these models, see the MindQuantum Tutorial.
Docs
More details about installation guide, tutorials and APIs, please see the User Documentation.
Community
Governance
Check out how MindSpore Open Governance works.
Contributing
Welcome contributions. See our Contributor Wiki for more details.