sun-umn/PyGRANSO
PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation
PyGRANSO helps machine learning practitioners solve complex optimization problems where the objective function or constraints are 'nonsmooth' and 'nonconvex' — common challenges in deep learning. It takes your PyTorch-defined model and optimization problem, automatically handles the necessary calculus, and provides an optimized model that respects those difficult constraints. This is for anyone building advanced machine learning models, especially those in deep learning, who need to ensure their models meet specific criteria or performance bounds.
Available on PyPI.
Use this if you are a machine learning engineer or researcher working with PyTorch and need to train models under complex, nonsmooth, and nonconvex constraints, especially in deep learning applications.
Not ideal if your optimization problems are simple, smooth, convex, or if you prefer to manually provide analytical gradients for your optimization solver.
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6
Language
Python
License
AGPL-3.0
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Last pushed
Feb 27, 2026
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