Smac

Breaking Changes
* `BOHB4HPO` facade has been renamed to `SMAC4MF` facade (738)
* Require `scipy` >= 1.7 (729)
* Require `emcee` >= 3.0.0 (723)

Major Changes
* Drop support for Python 3.6 (726)
* Added Colab to try SMAC in your browser! (697)

Minor Changes
* Added gradient boosting example, removed random forest example (722)
* `lazy_import` dependency dropped (741)
* Replaced `pyDOE` requirement with `scipy` for LHD design (735)
* Uses scrambled Sobol Sequence (733)
* Moved to Github actions (715)
* Improved testing (720, 723, 739, 743)
* Added option `save_results_instantly` in scenario object to save results instantly (728)
* Changed level of intensification messages to debug (724)

Bug Fixes
* Github badges updated (732)
* Fixed memory limit issue for `pynisher` (717)
* More robust multiprocessing (709, 712)
* Fixed serialization with runhistory entries (706)
* Separated evaluation from get next challengers in intensification (734)
* Doc fixes (727, 714)

Minor Changes
* Improve error message for first run crashed (694).
* Experimental: add callback mechanism (703).

Bug fixes
* Fix a bug which could make successive halving fail if run in parallel (695).
* Fix a bug which could cause hyperband to ignore the lowest budget (701).

Major Changes
* Separated evaluation from get next challengers in intensification (663)
* Implemented parallel SMAC using dask (675, 677, 681, 685, 686)
* Drop support for Python 3.5

Minor Changes
* Update Readme
* Remove runhistory from TAE (663)
* Store SMAC's internal config id in the configuration object (679)
* Introduce Status Type STOP (690)

Bug Fixes
* Only validate restriction of Sobol Sequence when choosing Sobol Sequence (664)
* Fix wrong initialization of list in local search (680)
* Fix setting random seed with a too small range in Latin Hypercube design (688)

Minor Changes

* Use Scipy's Sobol sequence for the initial design instead of a 3rd-party package (600)
* Store start and end time of function evaluation (647)

Bug Fixes

* Fixes an issue in the Bayesian optimization facade which triggered an exception when tuning categorical
hyperparameters (666)
* Fixes an issue in the Gaussian process MCMC which resulted in reduced execution speed and reduced performance (666)

Bug Fixes

* Fixes the docstring of SMAC's default acquisition function optimizer (653)
* Correctly attributes the configurations' origin if using the `FixedSet` acquisition function optimizer (653)
* Fixes an infinite loop which could occur if using only a single configuration per iteration (654)
* Fixes a bug in the kernel construction of the `BOFacade` (655)

Minor Changes

* Upgrade the minimal scikit-learn dependency to 0.22.X.
* Make GP predictions faster (638)
* Allow passing `tae_runner_kwargs` to `ROAR`.
* Add a new StatusType `DONOTADVANCE` for runs that would not benefit from a higher budgets. Such runs are always used
to build a model for SH/HB (632)
* Add facades/examples for HB/SH (610)
* Compute acquisition function only if necessary (627,629)

Bug Fixes
* Fixes a bug which caused SH/HB to consider TIMEOUTS on all budgets for model building (632)
* Fixed a bug in adaptive capping for SH (619,622)