Metadata-Version: 2.1
Name: deepnpg
Version: 0.0.1
Summary: Python library for building preconditiioner with Graph Neural Network
Home-page: https://github.com/inEXASCALE/deepnpc.git
Author: Xinye Chen
Author-email: xinyechenai@gmail.com
License: MIT License
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: C
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: numpy>=1.17.3
Requires-Dist: scipy>=1.7.0
Requires-Dist: matplotlib>=3.5
Requires-Dist: torch
Requires-Dist: torch_geometric
Requires-Dist: requests

# DeepNPG: Deep Neural Preconditioner with Graph Neural Networks

``DeepNPG`` is a Python library for building preconditiioner with Graph Neural Networks. It provides straightforward interfaces to convert matrix into graph and perform efficient neural network training.

All data (e.g., ``numpy.ndarray``, ``spicpy.sparse.csc/csr/bsr``) will be automatically converted into sparse COOrdinate format (COO format), and then to gemetric data format.
