Flowpp
Code for reproducing Flow ++ experiments
Install / Use
/learn @aravindsrinivas/FlowppREADME
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
This repository contains Tensorflow implementation of experiments from the paper Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design - Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel
Dependencies
- python3.6
- Tensorflow v1.10.1
- horovod v0.14.1
Horovod GPU setup instructions
Usage Instructions
We trained our models using 8 GPUs with data-parallelism using Horovod.
CIFAR 10
mpiexec -n 8 python3.6 run_cifar.py
Imagenet
Data for Imagenet Experiments:
Script to create dataset here
Imagenet 32x32
mpiexec -n 8 python3.6 -m flows_imagenet.launchers.imagenet32_official
Imagenet 64x64
mpiexec -n 6 python3.6 -m flows_imagenet.launchers.imagenet64_official
mpiexec -n 6 python3.6 -m flows_imagenet.launchers.imagenet64_5bit_official
CelebA-HQ 64x64
Data:
Download links in README
mpiexec -n 8 python3.6 -m flows_celeba.launchers.celeba64_5bit_official
mpiexec -n 8 python3.6 -m flows_celeba.launchers.celeba64_3bit_official
Contact
Please open an issue
Credits
flowpp was originally developed by Jonathan Ho (UC Berkeley), Peter Chen (UC Berkeley / covariant.ai), Aravind Srinivas (UC Berkeley), Yan Duan (covariant.ai), and Pieter Abbeel (UC Berkeley / covariant.ai).
Related Skills
proje
Interactive vocabulary learning platform with smart flashcards and spaced repetition for effective language acquisition.
YC-Killer
2.7kA library of enterprise-grade AI agents designed to democratize artificial intelligence and provide free, open-source alternatives to overvalued Y Combinator startups. If you are excited about democratizing AI access & AI agents, please star ⭐️ this repository and use the link in the readme to join our open source AI research team.
best-practices-researcher
The most comprehensive Claude Code skills registry | Web Search: https://skills-registry-web.vercel.app
groundhog
401Groundhog's primary purpose is to teach people how Cursor and all these other coding agents work under the hood. If you understand how these coding assistants work from first principles, then you can drive these tools harder (or perhaps make your own!).
