tf.ZeroOut.gpu | CUDA implementation of the ZeroOut tensorflow custom op | GPU library
kandi X-RAY | tf.ZeroOut.gpu Summary
kandi X-RAY | tf.ZeroOut.gpu Summary
tf.ZeroOut.gpu is a C++ library typically used in Hardware, GPU, Deep Learning, Pytorch, Tensorflow, Numpy applications. tf.ZeroOut.gpu has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.
A CUDA implementation of the example presented in Tensorflow tutorials for custom ops. Sets all elements of the input tensor to 0, except for the very first one that is kept.
A CUDA implementation of the example presented in Tensorflow tutorials for custom ops. Sets all elements of the input tensor to 0, except for the very first one that is kept.
Support
Quality
Security
License
Reuse
Support
tf.ZeroOut.gpu has a low active ecosystem.
It has 11 star(s) with 3 fork(s). There are no watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of tf.ZeroOut.gpu is current.
Quality
tf.ZeroOut.gpu has 0 bugs and 0 code smells.
Security
tf.ZeroOut.gpu has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
tf.ZeroOut.gpu code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
tf.ZeroOut.gpu 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
tf.ZeroOut.gpu releases are not available. You will need to build from source code and install.
Installation instructions are not available. Examples and code snippets are available.
It has 6 lines of code, 0 functions and 1 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tf.ZeroOut.gpu
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tf.ZeroOut.gpu
tf.ZeroOut.gpu Key Features
No Key Features are available at this moment for tf.ZeroOut.gpu.
tf.ZeroOut.gpu Examples and Code Snippets
No Code Snippets are available at this moment for tf.ZeroOut.gpu.
Community Discussions
Trending Discussions on tf.ZeroOut.gpu
QUESTION
Official ZeroOut gradient example error: AttributeError: 'list' object has no attribute 'eval'
Asked 2018-May-05 at 07:22
I followed the official tutorial of the tensorflow website: https://www.tensorflow.org/extend/adding_an_op There is also described how to call the gradient of the example ZeroOut in the tutorial that I want to try in this short code snippet underneath.
I have found the code here: https://github.com/MatteoRagni/tf.ZeroOut.gpu
...ANSWER
Answered 2018-May-05 at 07:22Answer to old question
The implementation
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tf.ZeroOut.gpu
You can download it from GitHub.
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 .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
