improved_wgan_training | reproducing experiments in `` Improved Training | Machine Learning library

by igul222 Python Version: Current License: MIT

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

kandi X-RAY | improved_wgan_training Summary

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

Code for reproducing experiments in "Improved Training of Wasserstein GANs"

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Quality

Security

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Reuse

Support

improved_wgan_training has a medium active ecosystem.

It has 2269 star(s) with 673 fork(s). There are 81 watchers for this library.

It had no major release in the last 6 months.

There are 41 open issues and 49 have been closed. On average issues are closed in 78 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of improved_wgan_training is current.

Quality

improved_wgan_training has 0 bugs and 0 code smells.

Security

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

improved_wgan_training code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

improved_wgan_training is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

improved_wgan_training has no build file. You will be need to create the build yourself to build the component from source.

improved_wgan_training saves you 1028 person hours of effort in developing the same functionality from scratch.

It has 2333 lines of code, 125 functions and 22 files.

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

Top functions reviewed by kandi - BETA

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

Load MNIST dataset
Unpickle a pickle file
Generate images from cifar files
Creates a convolutional layer
R Relu layer
Residual network
Bottleneck residual block
Generate DCGAN generator
Normalize input tensor
Residual generator
Residual block
Residual discriminator
Generate training dataset
Multiplicative discriminator
Generate an image
Generate a Multiplicative DCGAN generator
Calculate the exposure score for the given images
Return a tuple of the function and discriminator
Discriminator layer
Generate a generator

Get all kandi verified functions for this library.

improved_wgan_training Key Features

No Key Features are available at this moment for improved_wgan_training.

improved_wgan_training Examples and Code Snippets

First Order Divergence for training GANs,Provided Code

Jupyter Notebook

Lines of Code : 2

License : Permissive (Apache-2.0)

Copy

fid.py /path/to/images /path/to/precalculated_stats.npz

fid.py /path/to/images /path/to/other_images

Community Discussions

Trending Discussions on improved_wgan_training

No module named "tflib"

QUESTION

No module named "tflib"

Asked 2021-Feb-27 at 10:19

On this GitHub page of "Improved WGAN Training", particularly in their Python-Cifar-file, the authors use the Python-module tflib. I installed it via pip (pip install tflib), but when I import it, I still get the error message No module named tflib.

Any hints would be appreciated.

...

ANSWER

Answered 2021-Feb-27 at 10:19

The package on pypi is an unknown package.

If you look closely in the github repository, you will find that the tflib is actually a custom module made by the author and provided in the same repository. Cloning the full repository will help resolve the issue

Source https://stackoverflow.com/questions/66397533

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

Vulnerabilities

No vulnerabilities reported

Install improved_wgan_training

You can download it from GitHub.
You can use improved_wgan_training 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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