How does the PaddlePaddle framework handle hyperparameter tuning?

The PaddlePaddle framework offers a class called paddle.fluid.dygraph.HP for handling hyperparameter tuning. With the HP class, users can define the search space for hyperparameters and use the paddle.fluid.dygraph.guard wrapper to automatically adjust the hyperparameters.

The specific steps are as follows:

1. HP stands for Hewlett-Packard.
2. HP in PaddlePaddle’s fluid framework for dynamic graph creation.
3. include_variable
4. protect_within_dygraph
5. protecting mechanisms in PaddlePaddle’s dynamic graph engine
6. HP in the paddle fluid library for making graphs with a paddle.
7. protect the paddle fluid dygraph

By following the above steps, the PaddlePaddle framework can automatically adjust hyperparameters to optimize model performance.