chore: release v0.5.0 (#620)

Co-authored-by: Matthias Seeger <matthis@amazon.de>

CHANGELOG.md

@@ -4,6 +4,43 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](http://keepachangelog.com/).
 
+<a name="v0.5.0"></a>
+## [v0.5.0] - 2023-04-20
+
+### New Features
+
+- Speculative early checkpoint removal for async multi-fidelity ([#628](https://github.com/awslabs/syne-tune/issues/628))
+- Simple linear scalarization scheduler ([#619](https://github.com/awslabs/syne-tune/issues/619))
+- Automatic termination criterion ([#605](https://github.com/awslabs/syne-tune/issues/605))
+- All schedulers have a is_multiobjective_scheduler function ([#618](https://github.com/awslabs/syne-tune/issues/618))
+- Allow for customized extra results to be written to results.csv.zip ([#612](https://github.com/awslabs/syne-tune/issues/612))
+- Plotting functions to analyse multi-objective experiments. ([#611](https://github.com/awslabs/syne-tune/issues/611))
+- Downsampling of observed data for single-fidelity Bayesian optimization ([#607](https://github.com/awslabs/syne-tune/issues/607))
+
+### Bug Fixes
+- CI failing with `ModuleNotFoundError: No module named 'examples'` error ([#626](https://github.com/awslabs/syne-tune/issues/626))
+- Call init of class ([#584](https://github.com/awslabs/syne-tune/issues/584))
+- Random seed initialisation limited to int32 ([#608](https://github.com/awslabs/syne-tune/issues/608))
+- Make sure that checkpoints in PBT are removed once they are no longer needed ([#600](https://github.com/awslabs/syne-tune/pull/600))
+
+### Code Refactoring
+- Move early checkpoint removal into mixin ([#621](https://github.com/awslabs/syne-tune/issues/621))
+- Keep rung levels sorted in HyperbandScheduler ([#604](https://github.com/awslabs/syne-tune/issues/604))
+- Move utils from benchmarking to syne_tune ([#606](https://github.com/awslabs/syne-tune/pull/606))
+
+### Documentation Updates
+- Update instructions for how to install from source ([#629](https://github.com/awslabs/syne-tune/issues/629))
+- Update README.md ([#615](https://github.com/awslabs/syne-tune/pull/615))
+
+### Maintenance
+- Bump codecov/codecov-action from 3.1.1 to 3.1.2 ([#623](https://github.com/awslabs/syne-tune/issues/623))
+- Bump zgosalvez/github-actions-ensure-sha-pinned-actions from 2.1.0 to 2.1.2 ([#624](https://github.com/awslabs/syne-tune/issues/624))
+- Add release drafter automation ([#568](https://github.com/awslabs/syne-tune/issues/568))
+- Moved scheduler metadata generation ([#617](https://github.com/awslabs/syne-tune/issues/617))
+- Bump tensorflow from 2.11.0 to 2.11.1 in /examples/training_scripts/rl_cartpole ([#609](https://github.com/awslabs/syne-tune/issues/609))
+
+[v0.5.0]: https://github.com/awslabs/syne-tune/compare/v0.4.1...v0.5.0
+
 ## [0.4.1] - 2023-03-16
 
 We release version 0.4.1 which you can install with `pip install syne-tune[extra]`.

benchmarking/nursery/benchmark_dehb/requirements.txt

@@ -1,3 +1,2 @@
 syne-tune[gpsearchers,kde,blackbox-repository,yahpo,aws]
 tqdm
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/benchmark_dyhpo/requirements.txt

@@ -1,3 +1,2 @@
 syne-tune[gpsearchers,blackbox-repository,aws]
 tqdm
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/benchmark_hypertune/requirements.txt

@@ -1,3 +1,2 @@
 syne-tune[gpsearchers,kde,blackbox-repository,aws]
 tqdm
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/benchmark_neuralband/requirements.txt

@@ -1,4 +1,3 @@
 syne-tune[gpsearchers,kde,blackbox-repository,aws]
 tqdm
 botorch
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/benchmark_warping/requirements.txt

@@ -1,3 +1,2 @@
 syne-tune[gpsearchers,blackbox-repository,aws]
 tqdm
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/benchmark_yahpo/requirements.txt

@@ -1,3 +1,2 @@
 syne-tune[gpsearchers,blackbox-repository,yahpo,aws]
 tqdm
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/fine_tuning_transformer_glue/requirements.txt

@@ -1,4 +1,3 @@
 syne-tune[gpsearchers]
 datasets==1.8.0
 transformers
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/launch_local/requirements-synetune.txt

@@ -1,3 +1,2 @@
 syne-tune[gpsearchers,aws]
 tqdm
-sortedcontainers  # Remove in version > 0.4.1

benchmarking/nursery/launch_sagemaker/requirements.txt

@@ -1,3 +1,2 @@
 syne-tune[gpsearchers,aws]
 tqdm
-sortedcontainers  # Remove in version > 0.4.1

docs/source/index.rst

@@ -31,6 +31,21 @@ This package provides state-of-the-art algorithms for hyperparameter optimizatio
 What's New?
 -----------
 
+* Speculative early checkpoint removal for asynchronous multi-fidelity optimization.
+  Retaining all checkpoints often exhausts all available disk space when training
+  large models. With this feature, Syne Tune automatically removes checkpoints
+  that are unlikely to be needed.
+  `Details <faq.html#checkpoints-are-filling-up-my-disk-what-can-i-do>`__.
+* New Multi-Objective Scheduler:
+  :class:`~syne_tune.optimizer.schedulers.multiobjective.LinearScalarizedScheduler`.
+  The method works by taking a multi-objective problem and turning it into a
+  single-objective task by optimizing for a linear combination of all objectives.
+  This wrapper works with all single-objective schedulers. 
+* Support for automatic termination criterion proposed by Makarova et al.
+  Instead of defining a fix number of iterations or wall-clock time limit, we
+  can set a threshold on how much worse we allow the final solution to be
+  compared to the global optima, such that we automatically stop the optimization
+  process once we find a solution that meets this criteria.
 * You can now customize writing out results during an experiment, as shown in
   `examples/launch_height_extra_results.py <examples.html#customize-results-written-during-an-experiment>`__.
 * You can now warp inputs and apply a

syne_tune/version

@@ -1 +1 @@
-0.4.1
+0.5.0