VAEs
Jax | Flux | PyTorch

A collection of Variational AutoEncoders (VAEs) I have implemented in jax/flax, flux and pytorch with particular effort put into readability and reproducibility.

Python

Requirements For Jax

• Python >= 3.8
• jax

Installation

$ git clone https://github.com/BeeGass/Readable-VAEs.git

Usage

$ cd Readable-VAEs/vae-jax
$ python main.py 

Requirements For PyTorch

• PyTorch >= 1.10

Usage

$ cd Readable-VAEs/vae-pytorch
$ python main.py 

Julia

Requirements For Flux

• TODO
• TODO

Usage

$ cd Readable-VAEs/vae-flux
$ # TBA 

---

Config File Template

TBA

Weights And Biases Integration

TBA

---

Results

Model	PyTorch	Jax/Flax	Flux	Config	Paper	Reconstruction	Samples
VAE	☑	☐	☐	☐	Link	TBA	TBA
Beta-VAE	☐	☐	☐	☐	Link	TBA	TBA
Conditional VAE	☐	☐	☐	☐	Link	TBA	TBA
VQ-VAE-2	☐	☐	☐	☐	Link	TBA	TBA

Citation

@software{Gass_Readable-VAEs_2021,
  author = {Gass, B.A., Gass, B.A.},
  doi = {10.5281/zenodo.1234},
  month = {12},
  title = {{Readable-VAEs}},
  url = {https://github.com/BeeGass/Readable-VAEs},
  version = {1.0.0},
  year = {2021}
}