ScissionTL | A benchmarking tool for distributing Deep Neural Networks (DNN) in an efficient manner using transfe

by qub-blesson Python Version: Current License: No License

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kandi X-RAY | ScissionTL Summary

ScissionTL is a Python library. ScissionTL has no bugs, it has no vulnerabilities and it has low support. However ScissionTL build file is not available. You can download it from GitHub.

ScissionTL is a benchmarking tool for distributing deep neural networks (DNNs) across multiple resource tiers, such as the device, edge and cloud. ScissionTL is based on Scission that automatically benchmarks DNN models on a target set of the device, edge, and cloud resources for deciding the optimal slicing point for maximizing inference performance.

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Quality

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License

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Support

ScissionTL has a low active ecosystem.

It has 4 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of ScissionTL is current.

Quality

ScissionTL has no bugs reported.

Security

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

License

ScissionTL does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

ScissionTL has no build file. You will be need to create the build yourself to build the component from source.

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ScissionTL Key Features

No Key Features are available at this moment for ScissionTL.

ScissionTL Examples and Code Snippets

No Code Snippets are available at this moment for ScissionTL.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install ScissionTL

You can download it from GitHub.
You can use ScissionTL like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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