Pytorch VQ-VAE Implementation
Unofficial Pytorch implementation of Neural Discrete Representation Learning (2017)
Based on zalandoresearch/pytorch-vq-vae repository.
Install
$ pip install -r requirements.txt
Usage
You can experiment with CIFAR-10 data by running the following command:
python train.py
In the case of hyperparameters, you can experiment by tuning in config.json
.
Experiments (TBD)
To Do
- VectorQuantize EMA ver.
- Warm Start (Save model & Load pre-trained model)
- Inference (unseen random size image)
- Visualization for Interpretability (Interactive Mode)
Contact
If you have any question about the code, feel free to email me at subinium@gmail.com
.