Implement use of formal parameter search to log neatly with MLFlow

bdzyubak / torch-control

A top-level repo for evaluating natively available models

MIT License

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Implement use of formal parameter search to log neatly with MLFlow #24

Closed bdzyubak closed 2 months ago

bdzyubak commented 2 months ago

When a formal parameter search like sklearn.GridSearchCV() is used, mlflow will log the individual runs with hyperparameter variations as children of the parent experiment. This is much neater, especially when using mlflow autologging.

Implement in projects\MachineLearning\energy_use_time_series_forecasting\time_series_forecasting_energy_use.py, and test with CV/LLM when it becomes relevant.

bdzyubak commented 2 months ago

Implemented hyperparameter tuning which is logging successfully to MLflow. Some issues with OOM using GridSearchCV, so I went with nested loops and manual logging for now. Will revisit GridSearchCV or hyperopt in a separate issue.