Code Recipes

In this guide we discuss the most common advanced uses cases of PyHopper.

• Array parameters
• Tracking sampled hyperparameters
• Discontinuing unpromising candidates during evaluation
• Dealing with NaNs and exceptions
• Tracking with Tensorboard
• Tracking with MLflow and Weights & Biases
• Multiple validation splits
• Custom sampling strategies
• Custom parameter types
• Custom Callbacks