torchimize contains implementations of the Gradient Descent, Gauss-Newton and Levenberg-Marquardt optimization algorithms using the PyTorch library. The main motivation for this project is to enable convex optimization on GPUs based on the torch.Tensor class, which (as of 2022) is widely used in the deep learning field. This package features the capability to minimize several least-squares optimization problems at each loop iteration in parallel.
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Optimization Algorithms using Pytorch
We found that torchimize demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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