This is a repository for some researcher to build some Generative models using Tensorflow 2.x.
I NEED YOUR HELP(please let me know about formula, implementation and anything you worried)
We don't want to need flexible architectures.
We need strict definitions for shapes, parameters, and formulas.
We should Implement correct codes with well-documented(tested).
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pipenv
pipenv install TFGENZOO==1.2.5
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pip
pip install TFGENZOO==1.2.5
- clone this repository (If you want to do it, I will push this repository to PYPI)
- build this repository
docker-compose build
- run the environment
sh run_script.sh
- connect it via VSCode or Emacs or vi or anything.
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Simple Tutorials
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The tutorial about Flow-based Model
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How to add conditional input into Flow-based Model for the image generation.
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https://mokkemeguru.github.io/TFGENZOO/
- Flow-based Model Architecture (RealNVP, Glow)
- i-ResNet Model Architecture (i-ResNet, i-RevNet)
- GANs Model Architecture (GANs)
Whole backlog is here
New training results Oxford-flower102 with only 8 hours! (Quadro P6000 x 1)
data | NLL(test) | epoch | pretrained |
---|---|---|---|
Oxford-flower102 | 4.590211391448975 | 1024 | --- |
see more detail, you can see my internship’s report (Japanese only, if you need translated version, please contact me.)
Add some tutorial into ./tutorial
I wrote the master's paper about japanese text style transfer. "AutoEncoder に基づく半教師あり和文スタ イル変換" https://drive.google.com/file/d/1KtkLZi6PUvL7msAqbg_KRdEC0pmmpbhf/view?usp=sharing
MokkeMeguru (@MokkeMeguru): DM or Mention Please (in Any language).