
Clean implementations in TF2 of recent generative models – by Sarus Tech - ngrislain
https://github.com/sarus-tech/tf2-published-models
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ngrislain
# Sarus published models

Sarus implementation of classical ML models. The models are implemented using
the Keras API of tensorflow 2. Vizualization are implemented and can be seen
in tensorboard.

The required packages are managed with pipenv and can be installed using
pipenv install. Please see the pipenv documentation for more information.

## Philosophy

These models' implementations are intended to be easy to read and to adapt by
making use of the latest Tensorflow 2 library and Keras API.

## Basic usage

To install and train a model.

pipenv install pipenv shell python train.py

To visualize losses and reconstructions.

tensorboard --logdir ./logs/

## Available models

\- Simple Autoencoder \- Variational Autoencoder (VAE) \- Vector Quantized
Autoencoder (VQ-VAE) \- PixelCNN \- Gated PixelCNN \- PixelCNN++ \-
Conditional Neural Processes \- PixelSNAIL

