Use Jax functions in Pytorch with DLPack

Related tags

Pytorch Utilitiestorchdeep-learning-frameworkjax
Overview

jax2torch

Use Jax functions in Pytorch with DLPack, as outlined in a gist by @mattjj. The repository was made for the purposes of making this differentiable alignment work interoperable with Pytorch projects.

Install

$ pip install jax2torch

Usage

Open In Colab Quick test

import jax
import torch
from jax2torch import jax2torch

# Jax function

@jax.jit
def jax_pow(x, y = 2):
  return x ** y

# convert to Torch function

torch_pow = jax2torch(jax_pow)

# run it on Torch data!

x = torch.tensor([1., 2., 3.])
y = torch_pow(x, y = 3)
print(y)  # tensor([1., 8., 27.])

# And differentiate!

x = torch.tensor([2., 3.], requires_grad = True)
y = torch.sum(torch_pow(x, y = 3))
y.backward()
print(x.grad) # tensor([12., 27.])
You might also like...
A PyTorch implementation of EfficientNet
A PyTorch implementation of EfficientNet

EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor

Luke Melas-Kyriazi 7.2k Jan 6, 2023
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

Torchmeta A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch. Torchmeta contains popular meta-learning bench

Tristan Deleu 1.7k Jan 6, 2023
PyTorch Extension Library of Optimized Scatter Operations

PyTorch Scatter Documentation This package consists of a small extension library of highly optimized sparse update (scatter and segment) operations fo

Matthias Fey 1.2k Jan 7, 2023
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations

PyTorch Sparse This package consists of a small extension library of optimized sparse matrix operations with autograd support. This package currently

Matthias Fey 757 Jan 4, 2023
Reformer, the efficient Transformer, in Pytorch
Reformer, the efficient Transformer, in Pytorch

Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH

Phil Wang 1.8k Jan 6, 2023
higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.
higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these

Facebook Research 1.5k Jan 3, 2023
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent

DreamQuark 2k Dec 27, 2022
PyTorch extensions for fast R&D prototyping and Kaggle farming

Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What

Eugene Khvedchenya 1.3k Jan 5, 2023
An implementation of Performer, a linear attention-based transformer, in Pytorch
An implementation of Performer, a linear attention-based transformer, in Pytorch

Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random

Phil Wang 900 Dec 22, 2022
Releases(0.0.7)
Owner
Phil Wang
Working with Attention. It's all we need
Phil Wang
GitHub Repository
Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch.

Tez: a simple pytorch trainer NOTE: Currently, we are not accepting any pull requests! All PRs will be closed. If you want a feature or something does

abhishek thakur 1.1k Jan 04, 2023
High-level batteries-included neural network training library for Pytorch

Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st

382 Dec 06, 2022
TorchSSL: A PyTorch-based Toolbox for Semi-Supervised Learning

TorchSSL: A PyTorch-based Toolbox for Semi-Supervised Learning

1k Dec 28, 2022
A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries.

A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries.

878 Dec 30, 2022
higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these

Facebook Research 1.5k Jan 03, 2023
Distiller is an open-source Python package for neural network compression research.

Wiki and tutorials | Documentation | Getting Started | Algorithms | Design | FAQ Distiller is an open-source Python package for neural network compres

Intel Labs 4.1k Dec 28, 2022
A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.

Hugging Face 3.5k Jan 08, 2023
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

Pretrained models for Pytorch (Work in progress) The goal of this repo is: to help to reproduce research papers results (transfer learning setups for

Remi 8.7k Dec 31, 2022
A PyTorch implementation of L-BFGS.

PyTorch-LBFGS: A PyTorch Implementation of L-BFGS Authors: Hao-Jun Michael Shi (Northwestern University) and Dheevatsa Mudigere (Facebook) What is it?

Hao-Jun Michael Shi 478 Dec 27, 2022
pip install antialiased-cnns to improve stability and accuracy

Antialiased CNNs [Project Page] [Paper] [Talk] Making Convolutional Networks Shift-Invariant Again Richard Zhang. In ICML, 2019. Quick & easy start Ru

Adobe, Inc. 1.6k Dec 28, 2022
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

micrograd A tiny Autograd engine (with a bite! :)). Implements backpropagation (reverse-mode autodiff) over a dynamically built DAG and a small neural

Andrej 3.5k Jan 08, 2023
A tiny package to compare two neural networks in PyTorch

Compare neural networks by their feature similarity

Anand Krishnamoorthy 180 Dec 30, 2022
Reformer, the efficient Transformer, in Pytorch

Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH

Phil Wang 1.8k Jan 06, 2023
The goal of this library is to generate more helpful exception messages for numpy/pytorch matrix algebra expressions.

Tensor Sensor See article Clarifying exceptions and visualizing tensor operations in deep learning code. One of the biggest challenges when writing co

Terence Parr 704 Dec 14, 2022
Code snippets created for the PyTorch discussion board

PyTorch misc Collection of code snippets I've written for the PyTorch discussion board. All scripts were testes using the PyTorch 1.0 preview and torc

461 Dec 26, 2022
On the Variance of the Adaptive Learning Rate and Beyond

RAdam On the Variance of the Adaptive Learning Rate and Beyond We are in an early-release beta. Expect some adventures and rough edges. Table of Conte

Liyuan Liu 2.5k Dec 27, 2022
A very simple and small path tracer written in pytorch meant to be run on the GPU

MentisOculi Pytorch Path Tracer A very simple and small path tracer written in pytorch meant to be run on the GPU Why use pytorch and not some other c

Matthew B. Mirman 222 Dec 01, 2022
A simplified framework and utilities for PyTorch

Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne

GRAAL/GRAIL 534 Dec 17, 2022
Implements pytorch code for the Accelerated SGD algorithm.

AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O

205 Jan 02, 2023
A PyTorch implementation of Learning to learn by gradient descent by gradient descent

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

Ilya Kostrikov 300 Dec 11, 2022