neural sampler
Project description
NeuralSampler - Pytorch
Implementation of Neural Sampler.
Install
$ pip install neuralsampler
or install the latest version by
pip install -U git+https://JiahaoYao:{password}@github.com/JiahaoYao/neuralsampler.git@main
Install the jax (follow the official instruction here)
pip install jax jaxlib==0.1.64+[YOUR_CUDA_VERSION] -f https://storage.googleapis.com/jax-releases/jax_releases.html
e.g.
pip install --upgrade jax jaxlib==0.1.64+cuda101 -f https://storage.googleapis.com/jax-releases/jax_releases.html
Usage
import torch
from neuralsampler import neuralsampler
Run the code
python main.py
Run the scripts
python scripts/test_job.py
Demonstrations and tutorials
Ignore me (random things)
this repo is to collect all the random results and reproduce the experiments here
and then jax
i will use jax and flax, like shown here: https://github.com/yang-song/score_sde
there are the templates of building the jax neural networks (quite interesting to try this functional programming )
Todo list
- this library is on the pytorch
- i am also going to prepare the colab notebook
- the dataset is through the gdown: you can download the dataset from the google drive
- plz check the abf-mmd can reproduce the results! I have checked the codes are the same? I guessed the only issue might be just run enough runs! (Sun 09/05/2021 21:06)
- at least lots of things are connected now!
- update the colab module, going to download the dataset from the cloud!
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
neuralsampler-0.0.13.tar.gz
(22.0 kB
view hashes)
Built Distribution
Close
Hashes for neuralsampler-0.0.13-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 48901d1683a533487652635cbb0395ea184c6b8d559b5383b0cef973cb52484d |
|
MD5 | 74b6b9aa410466424e3b0cb4b6bda47e |
|
BLAKE2b-256 | 8d0687ce54edbb3b41ea168f7b3f61b5d6988ab7dba84dc2fc6b57ea4cedefac |