v0.2.0 Release

What’s new?

1. Modular BotAx + tutorial: new flexible setup for combining BoTorch subcomponents into a Model in Ax,
2. Scheduler + tutorial: new standalone configurable manager abstraction to run asynchronous closed-loop experiments with Ax (with or without human-in-the-loop),
3. GenerationStrategy tutorial: walkthrough for optimization algorithms specification in in Ax,
4. Bayesian optimization with categorical kernels exposed in Ax and auto-selected in Service and Loop APIs (via choose_generation_strategy). This eliminates the need to opt for Sobol quasi-random search when a given search space contains predominantly choice (a.k.a. categorical or discrete) parameters,
5. Scalarized outcome constraint support (feature request: #472),
6. Extended exp_to_df utility to conveniently display an Ax Experiment as a dataframe of trials and arms.

Bugfixes

• Abandoned arms and trials exclusion from modeling data (#506),
• Changing a range parameter to fixed (#383).