cuequivariance-ops-torch - GPU Accelerated Torch Extensions for Equivariant Primitives
Project description
cuequivariance-ops-torch
Introduction
cuequivariance_ops_torch provides CUDA kernels for the
cuEquivariance project's PyTorch
components. As such, it contains pytorch bindings to optimized kernels that
cuEquivariance's operations map down to. In general, we advice that you access
those kernels through cuEquivariance, but you may also find them useful on
their own.
Installation
Please install using either pip install cuequivariance-ops-torch-cu12 or
pip install cuequivariance-ops-torch-cu13 (depending on the CUDA toolkit
you wish to use).
Documentation
For detailed usage information of the kernels, please refer to the doc-strings in their respective modules. For higher-level documentations, refer to cuEquivariance.
Usage
You can import the library from python:
import cuequivariance_ops_torch
Kernels are primarily exposed as torch.nn.Module, but also provide a lower-level
interface as torch.library operators. Generally, the module is responsible
for proper input transformation and initialization, and the operator execute the
kernel.
This allows you to export models using this operations using torch.export,
and running inference on them using TensorRT.
Support and Feedback
Please contact the cuEquivariance developers for any issues you might encounter.
Project details
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