ProGAN | Progressive Generative Adversarial Network | Machine Learning library

by perplexingpegasus Python Version: Current License: No License

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

kandi X-RAY | ProGAN Summary

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

Implementation of Progressive Generative Adversarial Network based on research done by Tero Karras. The model was trained on landscape images collected from Reddit.

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Quality

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ProGAN has a low active ecosystem.

It has 146 star(s) with 17 fork(s). There are 9 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 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ProGAN is current.

Quality

ProGAN has 0 bugs and 30 code smells.

Security

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

ProGAN code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ProGAN 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

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

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

ProGAN saves you 403 person hours of effort in developing the same functionality from scratch.

It has 958 lines of code, 47 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Create the network
Resizes image files
Minibatch standard deviation
Reparameters
Train the network
Create a batch of data from the current array
Get layer ops
Load the array
Get global variables
Save to a pickle file
Change the res
Generate a random sample of the z - length array
Resize image files
Generate square crops
Transform the image
Generate a video
Generate an array of z_lengths
Generate the image

Get all kandi verified functions for this library.

ProGAN Key Features

No Key Features are available at this moment for ProGAN.

ProGAN Examples and Code Snippets

No Code Snippets are available at this moment for ProGAN.

Community Discussions

Trending Discussions on ProGAN

PyTorch - convert ProGAN agent from pth to onnx

QUESTION

PyTorch - convert ProGAN agent from pth to onnx

Asked 2020-Mar-25 at 12:38

I trained a ProGAN agent using this PyTorch reimplementation, and I saved the agent as a .pth. Now I need to convert the agent into the .onnx format, which I am doing using this scipt:

...

ANSWER

Answered 2020-Mar-25 at 12:38

Files you have there are state_dict, which are simply mappings of layer name to tensor weights biases and a-like (see here for more thorough introduction).

What that means is that you need a model so those saved weights and biases can be mapped upon, but first things first:

1. Model preparation

Clone the repository where model definitions are located and open file /pro_gan_pytorch/pro_gan_pytorch/PRO_GAN.py. We need some modifications in order for it to work with onnx. onnx exporter requires input to be passed as torch.tensor only (or list/dict of those), while Generator class needs int and float arguments).

Simple solution it to slightly modify forward function (line 80 in the file, you can verify it on GitHub) to the following:

Source https://stackoverflow.com/questions/60845222

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

Vulnerabilities

No vulnerabilities reported

Install ProGAN

You can download it from GitHub.
You can use ProGAN 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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