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ai-ml / cuequivariance-ops-cu13
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
py 3.10
✕ build_error
✓ 11.3s
py 3.11
✕ build_error
✓ 10.1s
py 3.12
✕ build_error
✓ 8.6s
py 3.13
✕ build_error
✓ 11.3s
py 3.9
✕ build_error
✕ build_error
809MB installed
● package 809MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
EquivariantOp
✓ from cuequivariance_ops_cu13 import EquivariantOp
✗ from cuequivariance.ops import EquivariantOp
The subpackage name differs between versions; older code may use 'cuequivariance.ops'.
SO3_linear
✓ from cuequivariance_ops_cu13 import SO3_linear
✗ from cuequivariance import SO3_linear
SO3_linear and other ops are in the ops subpackage, not directly in cuequivariance.
Basic import and usage example for cuequivariance-ops-cu13. Ensure torch is installed and CUDA 13 is available.
import torch
from cuequivariance_ops_cu13 import EquivariantOp, SO3_linear
# Create a simple equivariant linear layer
batch = 4
irreps_in = 5
irreps_out = 3
x = torch.randn(batch, irreps_in * 2) # shape (batch, 2*irreps_in) for complex representations
# Note: Actual usage may require specific shapes and irrep specs.
# The following is an example of calling a function.
# For real usage, see the documentation.
print('cuequivariance-ops-cu13 imported successfully')
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Version history
0.10.0latest on PyPI · released Apr 22, 2026
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Dependencies
cuequivariancerequiredCore library for equivariant operations; cuequivariance-ops depends on it.
torchrequiredPyTorch is required for tensor operations and GPU execution.
numpyoptionalUsed for numerical computations and data handling.