LSGAN | Machine Learning library

by xudonmao Python Version: Current License: No License

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

kandi X-RAY | LSGAN Summary

LSGAN is a Python library typically used in Artificial Intelligence, Machine Learning, Tensorflow, Generative adversarial networks applications. LSGAN has no bugs, it has no vulnerabilities and it has low support. However LSGAN build file is not available. You can download it from GitHub.

Code for Least Squares Generative Adversarial Networks and On the Effectiveness of Least Squares Generative Adversarial Networks.

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Quality

Security

License

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LSGAN has a low active ecosystem.

It has 99 star(s) with 26 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 1 have been closed. On average issues are closed in 80 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of LSGAN is current.

Quality

LSGAN has 0 bugs and 0 code smells.

Security

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

LSGAN code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

LSGAN 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

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

LSGAN 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.

LSGAN saves you 1284 person hours of effort in developing the same functionality from scratch.

It has 2885 lines of code, 211 functions and 32 files.

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

Top functions reviewed by kandi - BETA

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

Visualize the data
Merge two images together
Save multiple images
Make a gif from a list of images
Get an image
Read an image file
Transform an image
Center of crop
Converts a file to a TFRecord
Load one character from a file
Load data from a file
Implementation of inference
Define discriminator
A discriminator layer
Summarize activations
Loads images from file
Reads a TFRecord from a file
Generate samples from a multivariate Gaussian distribution
Prints the activation summary for each variable
Convolutional generator
Merge images

Get all kandi verified functions for this library.

LSGAN Key Features

No Key Features are available at this moment for LSGAN.

LSGAN Examples and Code Snippets

No Code Snippets are available at this moment for LSGAN.

Community Discussions

Trending Discussions on LSGAN

pytorch cyclegann gives a Missing key error when testing

QUESTION

pytorch cyclegann gives a Missing key error when testing

Asked 2021-May-26 at 11:04

I have trained a model using the pix2pix pytorch implementation and would like to test it.

However when I test it I get the error

...

ANSWER

Answered 2021-May-26 at 11:04

I think the problem here is some layer the bias=None but in testing the model required this, you should check the code for details.

After I check your config in train and test, the norm is different. For the code in GitHub, the norm difference may set the bias term is True or False.

Source https://stackoverflow.com/questions/67701029

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

Vulnerabilities

No vulnerabilities reported

Install LSGAN

You can download it from GitHub.
You can use LSGAN 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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