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ALAE | Adversarial Latent Autoencoders | Machine Learning library

 by   podgorskiy Python Version: Current License: No License

 by   podgorskiy Python Version: Current License: No License

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kandi X-RAY | ALAE Summary

ALAE is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Generative adversarial networks applications. ALAE has no bugs, it has no vulnerabilities, it has build file available and it has medium support. You can download it from GitHub.
Adversarial Latent Autoencoders Stanislav Pidhorskyi, Donald Adjeroh, Gianfranco Doretto Abstract: Autoencoder networks are unsupervised approaches aiming at combining generative and representational properties by learning simultaneously an encoder-generator map. Although studied extensively, the issues of whether they have the same generative power of GANs, or learn disentangled representations, have not been fully addressed. We introduce an autoencoder that tackles these issues jointly, which we call Adversarial Latent Autoencoder (ALAE). It is a general architecture that can leverage recent improvements on GAN training procedures. We designed two autoencoders: one based on a MLP encoder, and another based on a StyleGAN generator, which we call StyleALAE. We verify the disentanglement properties of both architectures. We show that StyleALAE can not only generate 1024x1024 face images with comparable quality of StyleGAN, but at the same resolution can also produce face reconstructions and manipulations based on real images. This makes ALAE the first autoencoder able to compare with, and go beyond the capabilities of a generator-only type of architecture.
Support
Support
Quality
Quality
Security
Security
License
License
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kandi-support Support

  • ALAE has a medium active ecosystem.
  • It has 3096 star(s) with 505 fork(s). There are 83 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 30 open issues and 35 have been closed. On average issues are closed in 72 days. There are 4 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of ALAE is current.
ALAE Support
Best in #Machine Learning
Average in #Machine Learning
ALAE Support
Best in #Machine Learning
Average in #Machine Learning

quality kandi Quality

  • ALAE has no bugs reported.
ALAE Quality
Best in #Machine Learning
Average in #Machine Learning
ALAE Quality
Best in #Machine Learning
Average in #Machine Learning

securitySecurity

  • ALAE has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
ALAE Security
Best in #Machine Learning
Average in #Machine Learning
ALAE Security
Best in #Machine Learning
Average in #Machine Learning

license License

  • ALAE 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.
ALAE License
Best in #Machine Learning
Average in #Machine Learning
ALAE License
Best in #Machine Learning
Average in #Machine Learning

buildReuse

  • ALAE 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.
  • Installation instructions are not available. Examples and code snippets are available.
ALAE Reuse
Best in #Machine Learning
Average in #Machine Learning
ALAE Reuse
Best in #Machine Learning
Average in #Machine Learning
Top functions reviewed by kandi - BETA

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

  • Train the model .
  • Prepare the dataset for the ensemble .
  • Main function .
  • Align landmarks .
  • Prepare the training image .
  • Sample from the model .
  • Prepare the MNIST dataset .
  • Run torch .
  • Save a single sample .
  • Parse arguments .

ALAE Key Features

[CVPR2020] Adversarial Latent Autoencoders

Citation

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@InProceedings{pidhorskyi2020adversarial,
 author   = {Pidhorskyi, Stanislav and Adjeroh, Donald A and Doretto, Gianfranco},
 booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
 title    = {Adversarial Latent Autoencoders},
 year     = {2020},
 note     = {[to appear]},
}

To run the demo

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pip install -r requirements.txt

Repository organization

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$ cd ~/ALAE
$ export PYTHONPATH=$PYTHONPATH:$(pwd)

Generating figures

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python style_mixing/stylemix.py -c <config>

Training

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pip install -r requirements.txt

Running metrics

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pip install tensorflow-gpu==1.10

How to get Pull Request Message Body

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curl https://api.github.com/repos/:owner/:repo/pulls/:pull_number | jq '.body'
curl https://api.github.com/repos/:owner/:repo/issues/:pull_number/comments | jq '. [] | .body'
-----------------------
curl https://api.github.com/repos/:owner/:repo/pulls/:pull_number | jq '.body'
curl https://api.github.com/repos/:owner/:repo/issues/:pull_number/comments | jq '. [] | .body'

Community Discussions

Trending Discussions on ALAE
  • How to get Pull Request Message Body
Trending Discussions on ALAE

QUESTION

How to get Pull Request Message Body

Asked 2020-May-04 at 06:01

With git log command I can successfully get a Github Pull Request number. Now, with the Pull Request number known, I would like to go ahead and query the message (a comment) posted with the PR (the PR message is displayed under the Conversation tab). Here is an example of PR with a message posted:

enter image description here

https://github.com/podgorskiy/ALAE/pull/11

How to query the PR message (aka PR comment) from a command line (with curl or git or something else)?

ANSWER

Answered 2020-May-04 at 06:01

To get the PR message using curl

curl https://api.github.com/repos/:owner/:repo/pulls/:pull_number | jq '.body'

To get the PR comments using curl use Issue Comments API as per the docs :

The Pull Request API allows you to list, view, edit, create, and even merge pull requests. Comments on pull requests can be managed via the Issue Comments API.

curl https://api.github.com/repos/:owner/:repo/issues/:pull_number/comments | jq '. [] | .body'

Note: You can process the JSON data received from the curl request using jq, a command-line JSON processor.

Source https://stackoverflow.com/questions/61584664

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

Vulnerabilities

No vulnerabilities reported

Install ALAE

You can download it from GitHub.
You can use ALAE 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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