Releases: Epistimio/orion
New Executor Backend for Parallelism with Joblib and Dask
🚀 Features
- Add Executor class and CLI arguments for parallelism @bouthilx (#608)
- Orion python api in parallel @donglinjy (#601)
🏗 Enhancements
- Add has_suggested/observed, new test-suite and re-implementation of ASHA @bouthilx (#604)
- Refactor
hunt
command to reuseExperimentClient.workon
@bouthilx (#605)
🐛 Bug Fixes
- Test different type of categorical dims @bouthilx (#609)
- Add has_suggested/observed, new test-suite and re-implementation of ASHA @bouthilx (#604)
📜 Documentation
PickledDB is now the default storage backend
🚀 Features
🏗️ Enhancements
- Add where parameter to Storage.fetch_trials @breuleux (#584)
- Make command
orion db setup
ask for right arguments based on storage backend. @notoraptor (#586) - Change the default database to PickledDB @abergeron (#585)
- Deterministic algorithm benchmark @donglinjy (#567)
🐛 Bug Fixes
- Add context-manager-enabled Trial subclass. @obilaniu (#587)
- Handle cases when trial.status is not reserved anymore locally. @bouthilx (#591)
🧰 Maintenance
Benchmark, Partial dependency plot and Grid Search
🚀 Features
- Add hover to partial deps scatter @bouthilx (#565)
- Make plots use trials in EVC by default @bouthilx (#564)
- Add error bar to LPI @bouthilx (#563)
- Add benchmark support into orion @donglinjy (#513)
- Add partial dependency plot @bouthilx (#544)
- Add grid search algorithm @bouthilx (#539)
🐛 Bug Fixes
📜 Documentation
Minor release: Read/Write/Execution modes for Experiments, branching on orion version, bug fixes
🚀 Features
- Add Read/Write/Execution modes for Experiment @bouthilx (#536)
- Branch if Oríon version changes @bouthilx (#530)
🐛 Bug Fixes
- Detect code change when no CMDLINE passed @bouthilx (#529)
- Support EVC in all algos @bouthilx (#523)
- Test that precision isn't messed up by linearization @bouthilx (#522)
- Ignore non-completed trials when computing LPI @bouthilx (#521)
- Add debugging verbosity @bouthilx (#520, #528)
📜 Documentation
🧰 Maintenance
Minor release: Support for python 3.9, bug fixes, improved CI
Parallel Coordinates & Local Parameter Importance Plots
Detailed list of changes
New features
- Add max_broken in exp configuration (#473)
- Add Parallel Coordinates Plot (#480)
- Add ReshapedSpace and Linearize transformer (#482)
- Add LPI plot (#483)
Bug Fixes
- Add extensive functional testing for configuration (#474)
- Handle rm/add properly in EVC (#475)
- Override fields with set, not update (#479)
- Fix cardinality and integer cast (#481)
Other improvements
Plotting API and Database commands
Important changes
New plotting API
Plotting capability is being added to experiment clients. You can now plot the regret (curve of best objective found during optimization) with simply experiment.plot.regret()
. You can find an example here.
Web API (REST server)
A web API was added for v0.1.9 in order to support the visualization dashboard that is currently under work. See full documentation here.
Database commands rm
& set
Command line helpers have been added to simplify the process of deleting experiments and trials as well as modifying trials in the database. See full documentation for both commands here.
Detailed list of changes
New features
- New plotting API (#400, #426)
- REST server (#437, #438, #441, #446)
- New command orion db rm (#425)
- New command orion db set (#428)
Breaking changes
Bug Fixes
- Fix backward compatibility tests in master - Drop support for orion < 0.1.6 (#420)
- Fix test using 'in' to assert equality (#427)
- Avoid side effects in setup_storage (#444)
- Return onehot interval instead of categorical (#447)
- Adjust OneHotEncoding interval shape (#449)
- Support non existing user script conf files (#452)
- Support load yaml config for dict items (#453)
- Fix fetch_lost_trials (Causing random FailedUpdate when using many workers) (#445)
Other improvements
- Improve CI - Convert functional algo tests to python API (#418)
- Monitor code change between trial execution (#429)
- Add info about working_dir when using orion info CLI (#430)
- Enable
is_broken
for ExperimentView (#432) - Specialized properties for Trials (#433)
- Add
completed
field toinfo
cmd (#435) - Add orion.client.get_experiment() (#439)
- Sort modules and extensions alphabetically (#443)
- Print user friendly err msg if script inexecutable (#445)
- Migrate from Travis to Github-actions (#458, #459, #461)
Documentation improvements
- Add a code of conduct (#353)
- Refresh database documentation (#413)
- Merging Sequential and Service API (#416)
- CLI documentation improvements (#440)
- Remove outdated
branch_from
parameter documentation inexperiment_builder.build()
(#442) - Changed variable name in docs to reflect the correct name (#448)
- Fix config of EvolutionaryES (#451)
Python API and New Algorithms
Important changes
The python API is finally ready for release v0.1.8! 🎉
Python API
An API is now available to run experiments directly from python instead of using the commandline.
from orion.client import create_experiment
experiment = create_experiment(
name='foo',
space=dict(x='uniform(-50,50)'))
trial = experiment.suggest()
# Do something using trial.params['x']
results = [dict(
name='dummy_objective',
type='objective',
value=dummy_objective)]
experiment.observe(trial, results)
Current API provides a simple function workon
for cheap experiments that can be executed by a single worker, and a generic ExperimentClient
(see example above) object for optimization with multiple workers.
See documentation for more details.
New Algorithms
Hyperband
Hyperband extends the Successive Halving algorithm by providing a way to exploit a fixed budget with different number of configurations for SuccessiveHalving algorithm to evaluate. It is especially useful when the trials are expensive to run and cheap noisy evaluations are possible. Think of it as using early evaluation during training to filter out bad candidates.
For more information on the algorithm, see original paper.
TPE
Tree-structured Parzen Estimator (TPE) algorithm is one of Sequential Model-Based Global Optimization (SMBO) algorithms, which will build models to propose new points based on the historical observed trials.
Instead of modeling p(y|x) like other SMBO algorithms, TPE models p(x|y) and p(y), and p(x|y) is modeled by transforming that generative process, replacing the distributions of the configuration prior with non-parametric densities.
TPE has the advantage of scaling particularly well compared to most Model-Based algorithm which are typically sequential. It does not model however dependencies between hyper-parameters, they
are assumed independent.
For more information on the algorithm, see original papers at:
- Algorithms for Hyper-Parameter Optimization
- Making a Science of Model Search: Hyperparameter Optimizationin Hundreds of Dimensions for Vision Architectures
Storage
To support integration with other tools and services such as MLFlow or Weight & Biases we wrapped our previous database backend with a storage backend. The database backends are now available within the Legagy storage backend. In addition, we now have a backend for Track. The latter is planned to serve as a bridge between Oríon and other experiment management platforms
or services. Track package development is on the ice for now, but contributions are very much welcomed. :)
Drop python 3.5, support 3.8
Although Oríon may still be compatible with python 3.5 we do not maintain it's support anymore. Python 3.8 is now officially supported.
Precision of real dimensions
By default Oríon now rounds hyperparameters to 4 decimals (ex 0.00041239123 would become 0.0004124). The rational is that little variations on continuous hyperparameters typically leads
to little variations in the in objective. When sharing hyperparameters (ex: in publications), one can now share the rounded values with the exact corresponding objectives instead of rounding the hyperparameters after the execution and risk sharing unreproducible results.
Rework of documentation
The documentation has been through a major rework.
- The introduction has been updated to better reflect current features.
- A section Getting Started and an Overview was added.
- The plugins documentation was updated with a new cookiecutter template to create algorithm plugins.
- A minimalist example of scikit-learn was added to serve as the simplest tutorial for Oríon.
- Extensive documentation on contributions has been added.
Detailed list of changes
New features
- Storage Backend with Track and Legacy (#289, #302, #316, #318)
- Python API (#297, #299, #300, #305, #307, #311, #312, #355, #399, #401)
- Add option to ignore some commandline options of user's script (#308)
- Add option to ignore code changes in user's script (#310)
- Add trial hash id that does not include fidelifty
(useful to resume across fidelities)(#313, #322) - Customize precision (#331)
- Support commandline call where first argument is not user's script (#333, #338)
- Add support for non-standard -args (#341)
- Add more helper functions for cmdline client (#343)
- Hyperband implementation (#354, #363, #383)
- TPE implementation (#381, #387, #389)
Breaking changes
- Drop python 3.5 support in favor of 3.8 (#303)
- Remove deprecated score_handle (#315)
- Make global, local and cmdline args coherent (#349, #404)
Bug Fixes
- Fix EphemeralDB index update after document deletion (#306)
- Support small fidelity scales for ASHA (#314)
- Algo redefinition should not drop algo config (#319)
- Random algorithm will hang if search space is smaller than specified trials number (#336)
- Inconsistent output in orion status and orion list (#342)
- Use EVC tree trials in producer (#347)
- Update fidelity sample method to honor required n_samples (#351)
- Add max_trials to algorithm.is_done (#360)
- Handle trials with corrupted status (#372)
- Making upper bound inclusive (#373)
- Fix --debug (#374)
- Round ASHA budget properly (#402)
- Update Plugins documentation section (#406)
- Print help when calling
orion
alone (#408)
Other improvements
- improve error message for ASHA (#317)
- Print important information at end of worker (#345)
- Add comprehensive error message for branching err (#346)
- Make global, local and cmdline args coherent (#349, #404)
- Improve tox configuration (#350, #398)
- Generic cardinality check in base algorithm (#352)
- Avoid duplicates in RandomSearch (#361)
- Handle timeout in DBs (PickledDB in particular) (#362)
- Add stress test (#364)
- Remove useless deprecation warnings (#376)
- Ignore test files for code coverage (#377)
- Show proper yaml syntax in resolve_config deprecation warnings containing None (#391)
- Raise exception when no prior is provided (#410)
Documentation improvements
- Add citation section (#301, #379)
- Fix doc for bayesopt's alpha (#309)
- Formatted commands and added a command description (#327)
- Clone via HTTPS instead of SSH (#328)
- Minimalist example with scikit-learn (#339)
- Full configuration documentation (#349)
- Contribution guidelines (#356)
- Update developer documentation (#365, #378)
- Release & Packaging (#371, #411)
- Update the documentation structure (#375)
- Refreshed introduction of Oríon's features (#380, #384)
- Overhaul of the documentation for new comers (#385, #403)
- Add Issue Template (#386)
- Add PR Template (#388)
- Add doc about label categories (#397)
- Update Plugins documentation section (#405)
- Document Windows compatibility (#409)
- General documentation updates (#332, #340, #344, #366, #367, #370)
Bug fix with database upgrade
Important changes
Database upgrade
There was an incompatibility introduced in v0.1.6 that would break pickleddb created with previous versions. This minor release introduces a new command orion db upgrade
to upgrade the database scheme so that databases created with orion<v0.1.6
can still be used in new versions.
Detailed list of changes
New feature
- Add
orion db upgrade
command (#293)
Breaking changes
- Turn test-db into db test (#291)
Bug fixes
- Handle non-existing fields in EphemeralDB (#284)
- Fix deepcopy of Enumerate transform (#290)
- Instantiate adapter even if empty (#295)
Others improvements
Documentation improvements
Auto-resolution and experiment versions
Important changes
Migrated to orion
on PyPi
We finally have orion namespace: pypi/warehouse#4189!!! 🎉 🎊
Auto-resolution and experiment versions
The modification of experiments (code change, search space modification, etc) will now be automatically resolved and will no longer lead to the (confusing) branch resolver prompt. When there is any modification that leads to a branching, the version of the experiment will be incremented (starting at 1). The unique index of the experiments are now (name, version) instead of (name, user).
No more user index
The user name is no longer part of the experiment's index. This means that someone with a username A in one environment may retrieve the same experiments with a username B in another environment without any problem. Previously this would only be possible using the option --user B
to override the default system's username. This was due to the fact that queries on the database was done using the username and it is no longer the case.
Improved ASHA
Interface
The new prior fidelity(low, high, base)
now makes it more convenient to define the fidelity dimension. The different budget for each rungs can now be scaled between low
and high
according to a base
logarithm.
Efficiency
The algorithm will now stop registering trials in the low rungs once the higher rungs are filled. This reduces the waste of resources spend on trials in low rungs that cannot be promoted to higher rungs since the latter will be completed shortly.
Detailed list of changes
New features
- Auto-resolution (#244)
- Add versioning to experiments (#240, #242, #243, #245, #246, #247, #248, #259, #268, #272, #279, #281 )
- Add to algo the ability to opt out (#266)
- Add env-vars to consumer (#280)
Breaking changes
Bug Fixes
- Fix Trial ID mismatch with higher dimension (#237)
- Make Space Sorted instead of Ordered (#257, #263 )
- Fix bug in conda test (#258)
- Handle status --name when empty (#270)
- Fix ASHA termination condition and branching with fidelity() (#274 )
- Avoid branching in
info
(#277)
Other improvements
- Add a global configuration object
orion.core.config
(#239, #251, #265) - Remove direct access to database backend in favor of storage backend (#241)
- Remove generic queries in favor of specific queries in storage backend (#250)
- Add best trial id to
info
command (#260) - Make ASHA opt out when last rungs are filled (#267)
- Migrate to
orion
on PyPi (#271 )