This repo provides the examples codes used in the medium post titled Optuna meets Weights and Biases.
pip install wandb optuna scikit-learn torch torchvision plotlyconda env create -f environment.yml
conda activate optuna-wandbUpdated 🚀 [11-Aug-2022]: Add as_multirun=True example to make part-1 simpler
In forthcoming optuna v3, optuna's wandb callback provides as_multirun option to trace an objective function optimised by iterative way, e.g., stochastic gradient descent. Thanks to this feature, we can combine optuna and wandb more easily.