LightOn technologies for Large scale Machine Learning with Optical Processing Unit
LightOnML is a high level machine learning-oriented API that allows to perform random projections on LightOn’s optical processing units (OPUs). LightOn’s OPUs are available through LightOn’s Cloud service.
- Run large-scale non-linear and linear random projections using LightOn’s Aurora OPUs
- Simulate these projections on any machine without access to an OPU
- Encode input data in a binary form using various encoders, for OPU input
lightonml doesn't require access to an OPU for some functionalities, but for performing
computations on an OPU you'll need one. Otherwise, a simulated OPU can be used.
To install, use
pip install lightonml
Optional dependencies are :
torch, required for the encoder classes, and the PyTorch
scikit-learn, required for using the corresponding
Documentation, examples and help
Main documentation can be found at the API docs website.
Check the examples directory in the repo, if you don't have access to an OPU you can run the code locally with a simulated OPU
For getting help on the LightOn Cloud service check the Community website
For help on the library itself, you can use issues on this repository.
Access to Optical Processing Units
To request access to LightOn Cloud and try our photonic co-processor, please visit: https://cloud.lighton.ai/
For researchers, we also have a LightOn Cloud for Research program, please visit https://cloud.lighton.ai/lighton-research/ for more information.
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