Skip to main content

cuEquivariance

cuEquivariance is an NVIDIA Python library designed to facilitate the construction of high-performance geometric neural networks using segmented polynomials and triangular operations. cuEquivariance provides a comprehensive API for describing segmented polynomials made out of segmented tensor products and optimized CUDA kernels for their execution. Additionally, cuEquivariance offers bindings for both PyTorch and JAX, ensuring broad compatibility and ease of integration.

Equivariance is the mathematical formalization of the concept of "respecting symmetries." Robust physical models exhibit equivariance with respect to rotations and translations in three-dimensional space. Artificial intelligence models that incorporate equivariance are often more data-efficient.

Documentation

Please refer to the project documentation for more information https://docs.nvidia.com/cuda/cuequivariance/.

Installation

# Choose the frontend you want to use
pip install cuequivariance-jax
pip install cuequivariance-torch
pip install cuequivariance  # Installs only the core non-ML components

# CUDA kernels
pip install cuequivariance-ops-jax-cu12   # or -cu13
pip install cuequivariance-ops-torch-cu12 # or -cu13

License

All files hosted in this repository are subject to the Apache 2.0 license.

Disclaimer

cuEquivariance is in a Beta state. Beta products may not be fully functional, may contain errors or design flaws, and may be changed at any time without notice. We appreciate your feedback to improve and iterate on our Beta products.

Metadata

Release files for cuequivariance 0.12.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for cuequivariance 0.12.0
File Size Uploaded
cuequivariance-0.12.0.tar.gz 219.5 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for cuequivariance 0.12.0
File Interpreter ABI Platform
cuequivariance-0.12.0-py3-none-any.whl Python 3 none any Details

Total release size: 470.3 kB

Release files / cuequivariance-0.12.0.tar.gz

Download URL cuequivariance-0.12.0.tar.gz
Size 219.5 kB
Tags Source
SHA-256 checksum
How to use checksums
6e746705817033da8fa3f85d89b5613170f29027dcf85c9ffcf642c9ee377d4f
BLAKE2b-256 checksum
How to use checksums
e6e8a133b9b6d0132f237a1c40b0f6dbb8a955b313629323ab060a782477ef25
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.14.7

Release files / cuequivariance-0.12.0-py3-none-any.whl

Download URL cuequivariance-0.12.0-py3-none-any.whl
Size 250.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
cdca30e8954fb01ac8f724cc4d59fd6e624e393082fb8a18076602f9ef34d281
BLAKE2b-256 checksum
How to use checksums
36e398552be936239da279ffb67b9a5b6504832a8850ad39db2eb2938504e8c8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.14.7

Release history Release notifications | RSS feed

This release

0.12.0 This release

2 release files

0.11.0

2 release files

0.10.0

2 release files

0.9.1

2 release files

0.9.0

2 release files

0.8.1

2 release files

0.8.0

2 release files

0.7.0

2 release files

0.6.1

2 release files

0.6.0

2 release files

0.5.1

2 release files

0.5.0

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.0

2 release files

0.1.0

2 release files

0.0.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page