RR-GCN | Code for R-GCN : The R Could Stand for Random
kandi X-RAY | RR-GCN Summary
kandi X-RAY | RR-GCN Summary
RR-GCN is a Python library. RR-GCN has no bugs, it has no vulnerabilities, it has build file available and it has low support. However RR-GCN has a Non-SPDX License. You can install using 'pip install RR-GCN' or download it from GitHub, PyPI.
Code for "R-GCN: The R Could Stand for Random"
Code for "R-GCN: The R Could Stand for Random"
Support
Quality
Security
License
Reuse
Support
RR-GCN has a low active ecosystem.
It has 16 star(s) with 1 fork(s). There are 3 watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 1 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of RR-GCN is current.
Quality
RR-GCN has no bugs reported.
Security
RR-GCN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
RR-GCN has a Non-SPDX License.
Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
Reuse
RR-GCN releases are not available. You will need to build from source code and install.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of RR-GCN
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of RR-GCN
RR-GCN Key Features
No Key Features are available at this moment for RR-GCN.
RR-GCN Examples and Code Snippets
No Code Snippets are available at this moment for RR-GCN.
Community Discussions
No Community Discussions are available at this moment for RR-GCN.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install RR-GCN
After installing the correct PyG version for your PyTorch/CUDA installation as documented in their installation instructions, install the RR-GCN package using:.
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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