Deep-Compression-AlexNet | Deep Compression on AlexNet | Compression library
kandi X-RAY | Deep-Compression-AlexNet Summary
kandi X-RAY | Deep-Compression-AlexNet Summary
Deep-Compression-AlexNet is a Python library typically used in Utilities, Compression, Deep Learning, Pytorch applications. Deep-Compression-AlexNet has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Deep-Compression-AlexNet build file is not available. You can download it from GitHub.
March 15, 2019: for our most updated work on model compression and acceleration, please reference:. ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware (ICLR’19). AMC: AutoML for Model Compression and Acceleration on Mobile Devices (ECCV’18). HAQ: Hardware-Aware Automated Quantization (CVPR’19). Defenstive Quantization: When Efficiency Meet Robustness (ICLR'19).
March 15, 2019: for our most updated work on model compression and acceleration, please reference:. ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware (ICLR’19). AMC: AutoML for Model Compression and Acceleration on Mobile Devices (ECCV’18). HAQ: Hardware-Aware Automated Quantization (CVPR’19). Defenstive Quantization: When Efficiency Meet Robustness (ICLR'19).
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Quality
Security
License
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Support
Deep-Compression-AlexNet has a low active ecosystem.
It has 572 star(s) with 200 fork(s). There are 50 watchers for this library.
It had no major release in the last 6 months.
Deep-Compression-AlexNet has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Deep-Compression-AlexNet is current.
Quality
Deep-Compression-AlexNet has 0 bugs and 0 code smells.
Security
Deep-Compression-AlexNet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Deep-Compression-AlexNet code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Deep-Compression-AlexNet is licensed under the BSD-2-Clause License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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Deep-Compression-AlexNet releases are not available. You will need to build from source code and install.
Deep-Compression-AlexNet has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Deep-Compression-AlexNet saves you 23 person hours of effort in developing the same functionality from scratch.
It has 65 lines of code, 1 functions and 1 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed Deep-Compression-AlexNet and discovered the below as its top functions. This is intended to give you an instant insight into Deep-Compression-AlexNet implemented functionality, and help decide if they suit your requirements.
- Convert binary stream to code .
Get all kandi verified functions for this library.
Deep-Compression-AlexNet Key Features
No Key Features are available at this moment for Deep-Compression-AlexNet.
Deep-Compression-AlexNet Examples and Code Snippets
No Code Snippets are available at this moment for Deep-Compression-AlexNet.
Community Discussions
Trending Discussions on Deep-Compression-AlexNet
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 07:54See the Usage section in the git repository you are using:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Deep-Compression-AlexNet
You can download it from GitHub.
You can use Deep-Compression-AlexNet 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.
You can use Deep-Compression-AlexNet 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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