v0.2.2 Release

Bugfixes + support for Pareto frontier extraction in Ax Service API

v0.2.1: Release

What’s new?

1. Support Multi-Objective Optimizations for the Service API.
2. Deprecation of SimpleExperiment
3. Several minor tutorial and documentation corrections.
4. Documentation is no longer released with errors in tutorials.

Bugfixes

• IndexError when only using a subset of fields in raw data (#652)

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).

v0.1.20

Compatibility: Requires botorch == 0.4.0

Major changes

• Switching from Travis CI to Github Actions for continuous integration and deployment
• New tutorial for using BoTorchModel, which makes it easier to create custom BoTorch models in Ax (88c4a3f)
• Fixed the Raytune and MultiTask tutorials
• Multiple bug fixes (e.g. #501, #471)

v0.1.19

Compatibility: Requires botorch >= 0.3.3

Major changes

• Support for new Botorch features, including Contextual Bayes Opt, Input Warping, etc. See the latest Botorch release for more information: https://github.com/pytorch/botorch/releases/tag/v0.3.3
• Improvements to storage-related performance by aligning SQLAlchemy and Ax classes better (e.g. #422)

v0.1.18

• Support and new tutorial for Multi-Objective Optimization (MOO)

v0.1.17 Release

Fixed re-release of v0.1.15 and v0.1.16 that were deployed incorrectly.

v0.1.16 Release

Minor version bump to resolve some bugs with the last release (#390, #391, #387)

v0.1.15 Release

Modular Botorch

• Introduces a new set of abstractions for Botorch models to support customizable, storage-friendly botorch components (e.g. Surrogate, Acquisition).
• See #374 for more information
• A draft tutorial is available at: https://github.com/facebook/Ax/blob/master/tutorials/botorch_modular.ipynb

Logger redesign

• Our logger APIs have been refactored to use a new naming scheme (module name, via getLogger(__name__)) and use a different handler/propagation scheme (1 root handler instead of N+1 child handlers). These changes play nicely with core features of Python's logging API and enable use cases such as #316.

MultiObjective API Improvements

• Introduces some new MOO modeling APIs such as MultiObjectiveTorchModelBridge to support our growing list of MOO features. See 272b6dd

Misc Fixes
#351, #382

v0.1.14 Release

• Minor bug fixes (storage of function kwargs to BoTorch models, etc.),
• Additional documentation on the website.