BigGAN-Pretrained | Pretrained Network

by crypto-code Python Version: 1.0 License: MIT

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

kandi X-RAY | BigGAN-Pretrained Summary

BigGAN-Pretrained is a Python library. BigGAN-Pretrained has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However BigGAN-Pretrained build file is not available. You can download it from GitHub.

Uses a Pretrained Network (using Google's Deepmind) to generate images.

Support

Quality

Security

License

Reuse

Support

BigGAN-Pretrained has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

BigGAN-Pretrained has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of BigGAN-Pretrained is 1.0

Quality

BigGAN-Pretrained has 0 bugs and 0 code smells.

Security

BigGAN-Pretrained has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

BigGAN-Pretrained code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

BigGAN-Pretrained 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

BigGAN-Pretrained releases are available to install and integrate.

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

Installation instructions, examples and code snippets are available.

It has 71 lines of code, 1 functions and 3 files.

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

Top functions reviewed by kandi - BETA

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

Compute the weight of a module .
Apply spectral norm .
Apply spectral normalization .
Remove spectral norm from module .
Calculate the outstanding stats .
Normalize input array .
Calls the function .
Convert a depth array into a space .
Initialize the spectral norm .
Compute the gradient of x .

Get all kandi verified functions for this library.

BigGAN-Pretrained Key Features

No Key Features are available at this moment for BigGAN-Pretrained.

BigGAN-Pretrained Examples and Code Snippets

No Code Snippets are available at this moment for BigGAN-Pretrained.

Community Discussions

No Community Discussions are available at this moment for BigGAN-Pretrained.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install BigGAN-Pretrained

This requires anaconda or miniconda. To create the environement run.
python=3.6
cudatoolkit=10.0
pytorch
torchvision
scipy

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: