gan-intro

by AYLIEN Python Version: Current License: No License

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

kandi X-RAY | gan-intro Summary

gan-intro is a Python library. gan-intro has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

gan-intro

Support

Quality

Security

License

Reuse

Support

gan-intro has a low active ecosystem.

It has 383 star(s) with 197 fork(s). There are 22 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 4 have been closed. On average issues are closed in 145 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of gan-intro is current.

Quality

gan-intro has 0 bugs and 3 code smells.

Security

gan-intro has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

gan-intro code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

gan-intro 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

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

Build file is available. You can build the component from source.

gan-intro saves you 94 person hours of effort in developing the same functionality from scratch.

It has 240 lines of code, 19 functions and 1 files.

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

Top functions reviewed by kandi - BETA

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

Train model
Generate random samples
Save an animation
Plots the distribution of the distribution
Compute the discriminator
Compute a tensor
Minibatch layer
Parse command line arguments
Generate tensorflow

Get all kandi verified functions for this library.

gan-intro Key Features

No Key Features are available at this moment for gan-intro.

gan-intro Examples and Code Snippets

No Code Snippets are available at this moment for gan-intro.

Community Discussions

Trending Discussions on gan-intro

Tensorflow GAN discriminator loss NaN since negativ discriminator output

QUESTION

Tensorflow GAN discriminator loss NaN since negativ discriminator output

Asked 2018-Feb-10 at 18:20

In my implementation of a GAN network the output of the discriminator is something like 2.05145e+07 which leads to 1 - disc_output -> 1-2.05145e+07=-2.05145e+07 (a negativ number) therefore log(1-2.05145e+07) leads to NaN.

I am not the first one with this kind of problem. One solution is to only allow positive values inside the log like done here.

Does anyone knows any better solution to this?
maybe some different loss function ?

...

ANSWER

Answered 2017-Aug-04 at 14:05

Because discriminator returns a probability value, its output must be between 0 and 1. Try using sigmoid ( https://www.tensorflow.org/api_docs/python/tf/sigmoid) before using discriminator outputs.

Additionally, as others did, I suggest using tf.log(tf.maximum(x, 1e-9)) in case of a numerical instability.

Source https://stackoverflow.com/questions/45506455

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

Vulnerabilities

No vulnerabilities reported

Install gan-intro

You can download it from GitHub.
You can use gan-intro 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 .

Find more information at: