deep-compression | Compress neural network with pruning and quantization | Compression library

by wojciechmo Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | deep-compression Summary

deep-compression is a Python library typically used in Utilities, Compression, Deep Learning, Tensorflow applications. deep-compression has no bugs, it has no vulnerabilities and it has low support. However deep-compression build file is not available. You can download it from GitHub.

TensorFlow implementation of paper: Song Han, Huizi Mao, William J. Dally. Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding. The goal is to compress the neural network using weights pruning and quantization with no loss of accuracy.

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deep-compression has a low active ecosystem.

It has 88 star(s) with 24 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of deep-compression is current.

Quality

deep-compression has no bugs reported.

Security

deep-compression has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

deep-compression 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

deep-compression releases are not available. You will need to build from source code and install.

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

Top functions reviewed by kandi - BETA

kandi has reviewed deep-compression and discovered the below as its top functions. This is intended to give you an instant insight into deep-compression implemented functionality, and help decide if they suit your requirements.

Convert a tensor .
Calculate centroids based on weights .
Initialize layer .
Matrix multiplication .
Quantize the centroids
Performs forward multiplication .
Load weights and prune mask .
Make directory .

Get all kandi verified functions for this library.

deep-compression Key Features

No Key Features are available at this moment for deep-compression.

deep-compression Examples and Code Snippets

No Code Snippets are available at this moment for deep-compression.

Community Discussions

Trending Discussions on deep-compression

What is a .net file in caffe?

QUESTION

What is a .net file in caffe?

Asked 2017-Jan-22 at 07:54

I want to reduce the size of my .caffemodel file.

I came across Deep Compression (songhan/Deep-Compression-AlexNet).

This creates a .net file. How do I use it for predictions? Or how to I convert it to a .caffemodel file?

...

ANSWER

Answered 2017-Jan-22 at 07:54

See the Usage section in the git repository you are using:

Source https://stackoverflow.com/questions/41788319

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

Vulnerabilities

No vulnerabilities reported

Install deep-compression

You can download it from GitHub.
You can use deep-compression 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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