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@@ -61,7 +61,6 @@ Dynamic computation graph, automatic gradient computation, fast GPU support, bat | |
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## Installation | ||
```bash | ||
pip install torchquantum | ||
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Hanrui Wang [[email protected]](mailto:[email protected]) | ||
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## Contributors | ||
Hanrui Wang, Jiannan Cao, Jessica Ding, Jiai Gu, Song Han, Zirui Li, Zhiding Liang, Pengyu Liu, Yilian Liu, Mohammadreza Tavasoli | ||
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## Citation | ||
``` | ||
@inproceedings{hanruiwang2022quantumnas, | ||
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from setuptools import setup, find_packages | ||
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setup(name='torchquantum', | ||
version='0.1.4', | ||
description='A PyTorch-centric hybrid classical-quantum dynamic ' | ||
'neural networks framework.', | ||
version='0.1.5', | ||
description='A PyTorch-based framework for differentiable classical simulation of quantum computing', | ||
url='https://github.com/mit-han-lab/torchquantum', | ||
author='Hanrui Wang', | ||
author='Hanrui Wang, Jiannan Cao, Jessica Ding, Jiai Gu, Song Han, Zirui Li, Zhiding Liang, Pengyu Liu, Mohammadreza Tavasoli', | ||
author_email='[email protected]', | ||
license='MIT', | ||
install_requires=[ | ||
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'matplotlib>=3.3.2', | ||
'pathos>=0.2.7', | ||
'pylatexenc>=2.10', | ||
# 'qiskit-nature>=0.4.4' | ||
], | ||
extras_require = { | ||
'doc': [ | ||
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