iSpLib | Sparse Graph Learning Library

by HipGraph Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | iSpLib Summary

iSpLib is a Python library. iSpLib has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

iSpLib is an accelerated sparse kernel library with PyTorch interface. This library has an auto-tuner which generates optimized custom sparse kernels based on the user environment. The goal of this library is to provide efficient sparse operations for Graph Neural Network implementations. Currently it has support for CPU-based efficient Sparse Dense Matrix Multiplication (spmm-sum only) with autograd.

Support

Quality

Security

License

Reuse

Support

iSpLib has a low active ecosystem.

It has 0 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

iSpLib has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of iSpLib is current.

Quality

iSpLib has no bugs reported.

Security

iSpLib has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

iSpLib is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

iSpLib releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

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iSpLib Key Features

No Key Features are available at this moment for iSpLib.

iSpLib Examples and Code Snippets

No Code Snippets are available at this moment for iSpLib.

Community Discussions

No Community Discussions are available at this moment for iSpLib.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install iSpLib

To install the package, run the following commands:.
git clone https://github.com/ICICLE-ai/iSpLib.git: To clone this repository.
./configure: To download and run the auto-tuner. This is a pre-requisite for the installation.
Create a virtualenv as the packages might conflict.
Install the dependencies pip install torch torchvision scikit-learn torch-scatter.
make: To install the library.
Finally install custom version of torch-geometric pip install git+https://github.com/gamparohit/pytorch_geometric.git

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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