Particle Swarm Optimization using the torch.optim API.
Project description
Torch PSO
Particle Swarm Optimization is an optimization technique that iteratively attempts to improve a list of candidate solutions. Each candidate solution is called a "particle", and collectively they are called a "swarm". In each step of the optimization, each particle moves in a random directly while simultaneously being pulled towards the other particles in the swarm. A simple introduction to the algorithm can be found on its Wikipedia article.
This package implements the Particle Swarm Optimization using the PyTorch Optimizer API, making it compatible with most pre-existing Torch training loops.
Installation
TODO: Write installation instructions for PyPI
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