SciML / Optimization.jl

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
https://docs.sciml.ai/Optimization/stable/
MIT License
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Disassociate batching from the `data` arg to `solve` and remove `data` #776

Open Vaibhavdixit02 opened 2 weeks ago

Vaibhavdixit02 commented 2 weeks ago

The data handling is quite awkward leading to issues like https://github.com/SciML/OptimizationBase.jl/issues/13, without batching data doesn't need to be passed in specially and should be a part of p to avoid global variables and in case of batching the right way would be to have support for stochastic oracles discussed in https://github.com/SciML/OptimizationBase.jl/issues/61.