import lightning.pytorch as pl
python main.py fit --print_config > config.yaml
python main.py --config config_1.yaml --config config_2.yaml fit
config_2
will take higher precedence than config_1
Shorts: fewer updates recently
Optuna - A hyperparameter optimization framework
# <https://optuna.readthedocs.io/en/stable/tutorial/10_key_features/003_efficient_optimization_algorithms.html>
print(f"Sampler is {study.sampler.__class__.__name__}")
# <https://optuna.readthedocs.io/en/stable/reference/generated/optuna.integration.TorchDistributedTrial.html#optuna.integration.TorchDistributedTrial>
https://github.com/facebookresearch/hydra
https://github.com/mlflow/mlflow/blob/master/examples/pytorch/AxHyperOptimizationPTL/ax_hpo_iris.py