benchmarx 0.1.0

Tools for benchmarking optimization methods

Benchmarx

Benchmarx provides a convenient interface for benchmarking optimization methods. This package provides a simple implementation of benchmarking functions for optimization tasks and provides the ability to use standard methods from jaxopt as well as to implement your own method. The results of the experiments are saved in all details in a json file, which can be used to visualize the data in graphs. Refer to the examples for details.

Installation

To install the latest release of Benchmarx, use the following command:

$ pip install benchmarx

Alternatively, it can be installed from sources with the following command:

$ python setup.py install

Examples

Refer to the examples provided in the repository for details on how to use this package.

• Gradient Descent on Quadratic problem

• Gradient Descent with custom Line Search

• Your own custom method

• Stochastic Gradient Descent on Quadratic Problem

• Quadratic Problem based on real data

• Neural Network training

Contribution

Contributions are welcome! If you have any suggestions or issues, feel free to open an issue or submit a pull request.