Pytorch implementation of Generative Models as Distributions of Functions
Generative Models as Distributions of Functions
This repo contains code to reproduce all experiments in Generative Models as Distributions of Functions.
Requirements
Requirements for training the models can be installed using pip install -r requirements.txt. All experiments were run using python 3.8.10.
Training a model
To train a model on CelebAHQ64, run
python main.py configs/config_celebahq64.json
Example configs to reproduce the results in the paper are provided in the configs folder. Note that you will have to provide a path to the data you wish to train on in the config.
Downloading datasets
The shapenet voxels and point cloud datasets can be downloaded at this link. The CelebAHQ datasets can be downloaded from here.
Loading trained models
All