This is the release note of v1.1.0.

New Features

Experimental Hyperband

Hyperband, an extension of the successive halving pruning algorithm, has been introduced as an experimental feature through HyperbandPruner. It is compatible with RandomSampler and TPESampler. See #809.

Breaking Changes

SuccessiveHalvingPruner minimum resource heuristic

When min_resource is omitted, instead of defaulting to 1, the SuccessiveHalvingPruner now uses a heuristic to guess a suitable value. See #812.

Enhancements

• Set pool_pre_ping=True for MySQL to avoid connection errors. (#806)
• Initial implementation of 'auto' for min_resource in SuccessiveHalvingPruner. (#812)
• Update TPESampler to support HyperbandPruner. (#828)
• Fix XGBoostPruningCallback to be compatible with xgboost.cv. (#865, thanks @yutayamazaki!)

Bug Fixes

• Make PyTorchIgnitePruningHandler report correct epoch. (#847)
• Fix LightGBM tuner raises exception when max_depth=-1. (#872)
• Sort intermediate values in plot_intermediate_values. (#889)

Installation

• Update SciPy version. (#838, thanks @yasuyuky!)

Documentation

• Fix KerasPruningCallback pruning example code. (#832, thanks @harupy!)
• Fix docstrings of visualization functions. (#833, thanks @harupy!)
• Update a badge image for Python 3.8. (#836)
• Add a note for JupyterLab users. (#843)
• FAQ documentation bullet list. (#856)
• Add to FAQ dynamically altering search spaces. (#857)
• Elaborate on details of HyperbandPruner. (#875)
• Update FAQ about trials raising exceptions and returning NaN. (#880)
• Add Neptune to the list of external libraries which use Optuna. (#890)
• Add OptGBM to the examples/README.md. (#896)
• Add link to examples. (#897)

Examples

• Add --pruning option to pytorch_lightning_simple.py. (#794, thanks @yutayamazaki!)
• Add FastAI example with FastAIPruningCallback. (#848)
• Fix TensorFlow eager example with TensorFlow 2.X. (#855, thanks @nuka137!)
• Update the PyTorch Lightning example to support pytorch_lightning==0.6.0. (#858)
• Add an example for LightGBM Tuner. (#860, thanks @jinnaiyuu!)
• Convert None to NaN before reporting to MLFlow. (#863)
• Remove description about CLI execution of MLFlow example. (#864)
• Fix TensorFlow estimator example with TensorFlow 2.X. (#868, thanks @nuka137!)
• Fix TensorFlow estimator pruning example with TensorFlow 2.X. (#871)

Code Fixes

• Remove typing external dependency. (#840, thanks @hbredin!)
• RDB storage module level logger. (#866)

Other

• Git ignore .DS_Store. (#829)
• Require torchvision>=0.5.0 with Pillow version fix. (#839, thanks @hugovk!)