Self-Attention-GAN | Pytorch implementation of Self-Attention Generative | Machine Learning library

by heykeetae Python Version: Current License: No License

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Self-Attention-GAN Summary

Self-Attention-GAN is a Python library typically used in Artificial Intelligence, Machine Learning, Pytorch, Tensorflow applications. Self-Attention-GAN has no bugs, it has no vulnerabilities and it has medium support. However Self-Attention-GAN build file is not available. You can download it from GitHub.

This repository provides a PyTorch implementation of SAGAN. Both wgan-gp and wgan-hinge loss are ready, but note that wgan-gp is somehow not compatible with the spectral normalization. Remove all the spectral normalization at the model for the adoption of wgan-gp. Self-attentions are applied to later two layers of both discriminator and generator.

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Self-Attention-GAN has a medium active ecosystem.

It has 2346 star(s) with 463 fork(s). There are 35 watchers for this library.

It had no major release in the last 6 months.

There are 41 open issues and 21 have been closed. On average issues are closed in 45 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Self-Attention-GAN is current.

Quality

Self-Attention-GAN has 0 bugs and 0 code smells.

Security

Self-Attention-GAN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Self-Attention-GAN code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Self-Attention-GAN 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.

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Self-Attention-GAN releases are not available. You will need to build from source code and install.

Self-Attention-GAN 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.

Self-Attention-GAN saves you 178 person hours of effort in developing the same functionality from scratch.

It has 440 lines of code, 32 functions and 7 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Train the model
Convert a tensor to a Variable object
Resets gradient
Normalize x
Load data loader
Compiles the image
Load the CelebA dataset
Loads an LSUN dataset
Create the parameters
L2 norm
Get parameters from command line
Save a single image
Make a folder in the given path

Get all kandi verified functions for this library.

Self-Attention-GAN Key Features

No Key Features are available at this moment for Self-Attention-GAN.

Self-Attention-GAN Examples and Code Snippets

RL-GAN-Net

Python

Lines of Code : 7

License : Permissive (MIT)

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@InProceedings{Sarmad_2019_CVPR,
author = {Sarmad, Muhammad and Lee, Hyunjoo Jenny and Kim, Young Min},
title = {RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion},
booktitle = {The IEEE Conf

References

Python

Lines of Code : 6

License : Permissive (Apache-2.0)

Copy

@article{phan2020sasegan,
  title={Self-Attention Generative Adversarial Network for Speech Enhancement},
  author={H. Phan, Hu. L. Nguyen, O. Y. Chén, P. Koch, N. Q. K. Duong, I. McLoughlin, and A. Mertins},
  journal={arXiv preprint arXiv:2010.0913

Community Discussions

Trending Discussions on Self-Attention-GAN

Keras.backend.reshape: TypeError: Failed to convert object of type to Tensor. Consider casting elements to a supported type

QUESTION

Keras.backend.reshape: TypeError: Failed to convert object of type to Tensor. Consider casting elements to a supported type

Asked 2020-Mar-25 at 07:29

I'm designing a custom layer for my neural network, but I get an error from my code.

I want to do a attention layer as described in the paper: SAGAN. And the original tf code

...

ANSWER

Answered 2018-Jun-12 at 20:46

You are accessing the tensor's .shape property which gives you Dimension objects and not actually the shape values. You have 2 options:

If you know the shape and it's fixed at layer creation time you can use K.int_shape(x)[0] which will give the value as an integer. It will however return None if the shape is unknown at creation time; for example if the batch_size is unknown.
If shape will be determined at runtime then you can use K.shape(x)[0] which will return a symbolic tensor that will hold the shape value at runtime.

Source https://stackoverflow.com/questions/50825248

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

Vulnerabilities

No vulnerabilities reported

Install Self-Attention-GAN

You can download it from GitHub.
You can use Self-Attention-GAN 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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