v0.3.1 Release

• Bump required Botorch version to v0.8.3
• Pin typeguard to version 2.13.3 while we investigate best course of action for dealing with backwards incompatible changes introduced in v3.0.0

v0.3.0 Release

• Bump required botorch version to 0.8.2
• Pinned sqlalchemy version to <2.0. We will update Ax to be compatible with the newly released sqlalchemy 2.0 in the near future
• Changes to Modular Botorch Model allow for heterogeneous modeling (i.e. many surrogates, one acquisition function). A tutorial jupyter notebook will be posted on ax.dev soon.
  • Added optional argument surrogate_specs to BoTorchModel: an Optional Mapping of names onto SurrogateSpecs, which specify how to initialize specific Surrogates to model specific outcomes. If None is provided a single Surrogate will be created and set up automatically based on the data provided.
  • Deprecated ListSurrogate (subsumed functionality into Surrogate)
• Removed Models.MOO_MODULAR (Models.BOTORCH_MODULAR supports multi-objective setups)
• Support partial objective thresholds
• Miscellaneous testing speedups
• Miscellaneous bug fixes

v0.2.10 Release

• Bump required botorch version to 0.8.0
• Enable relative outcome constraints
• Misc bugfixes and improvements
  • Bugfix in BestPointMixin.get_trace
  • Avoid unnecessary model re-fitting in some cases
  • Allow inferred noise in benchmarking via infer_noise flag

v0.2.9 Release

• Revamped Metric API
  • Metrics now return Result type for data fetching methods. This allows metrics to encode exceptions encountered during fetching into their returned value so Ax can defer their raising.
    • Call experiment.fetch_data_results to access these Results (organized by trial index and metric name) on the Experiment level.
      • experiment.fetch_data still returns Data directly by unwrapping the results under the hood for backwards compatibility considerations.
    • To update your existing custom Metrics you must wrap the return value of fetch_trial_data with Ok.
      • See the Scheduler tutorial for an example
• Improvements to Scheduler Exception handling via Results
  • If an Exception is encountered by the Scheduler during data fetching, either mark the trial as FAILED or continue the optimization (while alerting the user) depending on the failed metric’s role in the optimization. See scheduler.py for exact rules.
• SAASBO memory utilization improvements
• Miscellaneous bugfixes

v0.2.8 Release

Bugfix for for compatibility with latests pandas release. Also upgrade to BoTorch v0.7.2

v0.2.7 Release

Bug fixes & improvements. Now using BoTorch v0.7.2.

v0.2.6 Release

Bugfixes and incremental improvements. Now using botorch v0.6.6

v0.2.5 Release

Bugfixes and incremental improvements

v0.2.4 Release

• Bugfixes
• Changes to saving custom Metrics and Runners (see Developer API Tutorial for details)

v0.2.3 Release

• Bugfixes
• SAASBO fixes
• Updates to Scheduler (base class now works standalone, with polling functionality delegated to runner)
• Early-stopping support in Service API