The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
This PR contains very minor changes. First one is the number of epoch for the tpe tests that have been cut by half as well as the number of number of initial random trials (which gives the test an ~50% speed up). Second one moves the new_trial function to the base HyperparamsRepository class, thus removing duplicated code.
This PR contains very minor changes. First one is the number of epoch for the tpe tests that have been cut by half as well as the number of number of initial random trials (which gives the test an ~50% speed up). Second one moves the new_trial function to the base HyperparamsRepository class, thus removing duplicated code.