Граф коммитов

59 Коммитов

Автор SHA1 Сообщение Дата
Chi Wang fbea1d06dd
stratified group kfold splitter (#899)
* stratified group kfold splitter

* exclude catboost

---------

Co-authored-by: Shaokun <shaokunzhang529@gmail.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
2023-02-05 18:26:14 -05:00
Li Jiang 9fde27e536
fix #871: call check_spark only when necessary (#872)
Co-authored-by: Li Jiang <lijiang1@microsoft.com>
2023-01-07 07:41:35 -08:00
Antoni Baum 5f67c0ab8a
Do not persist entire AutoMLState in Searcher (#870)
* Do not persist entire AutoMLState in Searcher

Signed-off-by: Antoni Baum <antoni.baum@protonmail.com>

* Fix tests

Signed-off-by: Antoni Baum <antoni.baum@protonmail.com>

Signed-off-by: Antoni Baum <antoni.baum@protonmail.com>
2023-01-05 18:00:05 -08:00
Li Jiang da2cd7ca89
Add supporting using Spark as the backend of parallel training (#846)
* Added spark support for parallel training.

* Added tests and fixed a bug

* Added more tests and updated docs

* Updated setup.py and docs

* Added customize_learner and tests

* Update spark tests and setup.py

* Update docs and verbose

* Update logging, fix issue in cloud notebook

* Update github workflow for spark tests

* Update github workflow

* Remove hack of handling _choice_

* Allow for failures

* Fix tests, update docs

* Update setup.py

* Update Dockerfile for Spark

* Update tests, remove some warnings

* Add test for notebooks, update utils

* Add performance test for Spark

* Fix lru_cache maxsize

* Fix test failures on some platforms

* Fix coverage report failure

* resovle PR comments

* resovle PR comments 2nd round

* resovle PR comments 3rd round

* fix lint and rename test class

* resovle PR comments 4th round

* refactor customize_learner to broadcast_code
2022-12-23 08:18:49 -08:00
Shaokun 4140fc9022
Format errors on the web. (#855)
* fix_doc

* update

* fix lint

* fix lint

* reformat

Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
2022-12-22 22:36:34 -05:00
Jing Dong b2d51b648c
Added an info reminding user that if no time_budget and no max_iter is specified, then effectively zero-shot AutoML is used (#850)
* Added an info reminding user that if no time_budget and no max_iter is specified, then effectively zero-shot AutoML is used

* moved message to line 2818

* Update flaml/automl/automl.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/automl/automl.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
2022-12-18 12:49:00 -05:00
Chi Wang 232c356a4b
fix bug related to _choice_ (#848)
* fix bug related to _choice_

* remove py 3.6

* sanitize config

* optimize test
2022-12-13 15:48:32 -05:00
Chi Wang dbc2e2d796
Use get to avoid KeyError (#824)
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
Co-authored-by: Kevin Chen <74878789+int-chaos@users.noreply.github.com>
2022-12-07 01:23:45 -05:00
Mark Harley 44ddf9e104
Refactor into automl subpackage (#809)
* Refactor into automl subpackage

Moved some of the packages into an automl subpackage to tidy before the
task-based refactor. This is in response to discussions with the group
and a comment on the first task-based PR.

Only changes here are moving subpackages and modules into the new
automl, fixing imports to work with this structure and fixing some
dependencies in setup.py.

* Fix doc building post automl subpackage refactor

* Fix broken links in website post automl subpackage refactor

* Fix broken links in website post automl subpackage refactor

* Remove vw from test deps as this is breaking the build

* Move default back to the top-level

I'd moved this to automl as that's where it's used internally, but had
missed that this is actually part of the public interface so makes sense
to live where it was.

* Re-add top level modules with deprecation warnings

flaml.data, flaml.ml and flaml.model are re-added to the top level,
being re-exported from flaml.automl for backwards compatability. Adding
a deprecation warning so that we can have a planned removal later.

* Fix model.py line-endings

* Pin pytorch-lightning to less than 1.8.0

We're seeing strange lightning related bugs from pytorch-forecasting
since the release of lightning 1.8.0. Going to try constraining this to
see if we have a fix.

* Fix the lightning version pin

Was optimistic with setting it in the 1.7.x range, but that isn't
compatible with python 3.6

* Remove lightning version pin

* Revert dependency version changes

* Minor change to retrigger the build

* Fix line endings in ml.py and model.py

Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
Co-authored-by: EgorKraevTransferwise <egor.kraev@transferwise.com>
2022-12-06 15:46:08 -05:00