Release v1.1.1

Highlights

• Support passing a list of objectives as the objective argument.
• Raise better error message when the return value of run_trial() or HyperModel.fit() are of wrong type.
• Various bug fixes for BayesianOptimization tuner.
• The trial IDs are changed from hex strings to integers counting from 0.

What's Changed

• Make hyperparameters names visible in Display output by @C-Pro in #634
• Replace import kerastuner with import keras_tuner by @ageron in #640
• Support multi-objective by @haifeng-jin in #641
• reorganize the tests to follow keras best practices by @haifeng-jin in #643
• keep Objective in oracle for backward compatibility by @haifeng-jin in #644
• better error check for returned eval results by @haifeng-jin in #646
• Mitigate the issue of hanging workers after chief already quits when running keras-tuner in distributed tuning mode. by @mtian29 in #645
• Ensure hallucination checks if the Gaussian regressor has been fit be… by @brydon in #650
• Resolves #609: Support for sklearn functions without sample_weight by @brydon in #651
• Resolves #652 and #605: Make human readable trial_id and sync trial numbers between worker Displays by @brydon in #653
• Update tuner.py by @haifeng-jin in #657
• fix(bayesian): scalar optimization result (#655) by @haifeng-jin in #662
• Generalize hallucination checks to avoid racing conditions by @alisterl in #664
• remove scipy from required dependency by @haifeng-jin in #665
• Import scipy.optimize by @haifeng-jin in #667

New Contributors

• @C-Pro made their first contribution in #634
• @ageron made their first contribution in #640
• @mtian29 made their first contribution in #645
• @brydon made their first contribution in #650
• @alisterl made their first contribution in #664

Full Changelog: 1.1.1rc0...1.1.1