Registry / ai-ml / cuequivariance-ops-torch-cu12

cuequivariance-ops-torch-cu12

library0.10.0pypypiunverified

GPU-accelerated PyTorch extensions for equivariant primitives using CUDA 12. Part of the cuEquivariance ecosystem, providing high-performance implementations for e3nn and similar libraries. Version 0.10.0, actively developed.

ai-ml aws

pip install cuequivariance-ops-torch-cu12

package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · CUEQUIVARIANCE-OPS

cuequivariance-ops-torch-cu12

ai-mlpythonv0.10.0

Install

20.9s avg

Import

—

Disk

1434MB

Pass rate

4/ 10

Env Coverage4 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.10.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✕ build_error

✓ 22.2s

py 3.11

✕ build_error

✓ 22.1s

py 3.12

✕ build_error

✓ 18.5s

py 3.13

✕ build_error

✓ 20.6s

py 3.9

✕ build_error

1434MB installed

● package 1434MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

cuEquivarOps

✓ from cuequivariance_ops_torch import cuEquivarOps

✗ from cuequivariance_ops import cuEquivarOps

Package name includes '_torch' suffix

set_irreps

✓ from cuequivariance_ops_torch import set_irreps

Direct import from ops module

Initialize cuEquivarOps for given irreps and apply forward pass.

import torch from cuequivariance_ops_torch import cuEquivarOps # Define a simple irreducible representation irreps = '0e + 1o' ops = cuEquivarOps(irreps, math_dtype=torch.float32) # Create random input signal x = torch.randn(4, 3) # batch=4, vector size 3 output = ops.forward(x) print(output.shape)

Debug

Known issues

breakingVersion 0.10.0 may have breaking changes from 0.9.x. Check migration guide for changes in API signatures (e.g., renaming of 'set_irreps' to 'cuEquivarOps' constructor argument).

fix

Review changelog; update imports and method calls accordingly.

affects: <0.10.0

gotchaThe package is specific to CUDA 12. Install the correct variant: cuequivariance-ops-torch-cu12 (CUDA 12), cuequivariance-ops-torch-cu11 (CUDA 11), or CPU-only version (cuEquivariance-ops-torch). Mixing versions leads to runtime errors.

fix

Match package name to your CUDA version: pip install cuequivariance-ops-torch-cu12 for CUDA 12.

affects: all

gotchaRequires PyTorch compiled with CUDA. If PyTorch was installed from CPU-only wheel, cuEquivariance ops will fail at runtime.

fix

Install PyTorch with CUDA support: pip install torch --index-url https://download.pytorch.org/whl/cu121 (adjust CUDA version).

affects: all

Upgrade

Version history

0.10.0latest on PyPI · released Apr 22, 2026

Audit

Dependencies

torchrequiredRequired runtime dependency

cuequivariancerequiredCore library for equivariance definitions

Agent activity

26 hits · last 30 days

node

OpenAI (training)

Resources

packagehttps://pypi.org/project/cuequivariance-ops-torch-cu12/ ↗

homepagehttps://developer.nvidia.com/cuequivariance ↗

docshttps://docs.nvidia.com/cuda/cuequivariance/ ↗