* 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>
* make performance test reproducible
* fix test error
* Doc update and disable logging
* document random_state and version
* remove hardcoded budget
* fix test error and dependency; close#777
* iloc
* install editable package in codespace
* fix test error in test_forecast
* fix test error in test_space
* openml version
* break tests; pre-commit
* skip on py10+win32
* install mlflow in test
* install mlflow in [test]
* skip test in windows
* import
* handle PermissionError
* skip test in windows
* skip test in windows
* skip test in windows
* skip test in windows
* remove ts_forecast_panel from doc
* Small docstring change for clarity
* Added tentative changes to docs
* Update website/docs/Use-Cases/Task-Oriented-AutoML.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/model.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Updated model.py to reflect `n_jobs = None` suggestion
* Updated tutorial to reflect `n_jobs=None` suggestion
* Update model.py
Improved string
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* categorical choice can be ordered or unordered
* ordered -> order
* move choice into utils
* version comparison
* packaging -> setuptools
* import version
* version_parse
* test order for choice
* time series forecasting with panel datasets
- integrate Temporal Fusion Transformer as a learner based on pytorchforecasting
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py and test_forecast.py
- remove blank lines
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py to prevent errors
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py and data.py
- change forecast task name
- update documentation for fit() method
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
- add performance test
- use 'fit_kwargs_by_estimator'
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* add time index function
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py performance test
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update data.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update data.py to prevent type error
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update for pytorch forecasting tft on panel datasets
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py documentations
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* - rename estimator
- add 'gpu_per_trial' for tft estimator
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* include ts panel forecasting as an example
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update documentations
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl_time_series_forecast.ipynb
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update documentations
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* "weights_summary" argument deprecated and removed for pl.Trainer()
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py tft estimator prediction method
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update `fit_kwargs` documentation
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* support latest xgboost version
* Update test_classification.py
* Update
Exists problems when installing xgb1.6.1 in py3.6
* cleanup
* xgboost version
* remove time_budget_s in test
* remove redundancy
* stop support of python 3.6
Co-authored-by: zsk <shaokunzhang529@gmail.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* init value type match
* bump version to 1.0.6
* add a note about flaml version in notebook
* add note about mismatched ITER_HP
* catch SSLError when accessing OpenML data
* catch errors in autovw test
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* refactoring TransformersEstimator to support default and custom_hp
* handling starting_points not in search space
* addressing starting point more than max_iter
* fixing upper < lower bug
* update model.py
- change upper bound for "lags" hyperparameter
* update test_forecast.py
- add a test for a large dataset
* update sample.py
- pre-commit changes
* changed signature of automl.predict and automl.predict_proba to X
* XGBoostEstimator
* changed signature of Prophet predict to X
* changed signature of ARIMA predict to X
* changed signature of TS_SKLearn_Regressor predict to X
* add sklearn regressors as learners for ts_forecast task
* add direct forecasting strategy
warnings and errors for duplicate rows and missing values
- add preprocess for sklearn time series forecast
update automl.py
update test/test_forecast.py
* update model.py and test_forecast.py for cv eval_method
* add "hcrystalball" dependency in setup.py
* update automl.py
- add _validate_ts_data function for abstraction
- include xgb_limitdepth as a learner
* update model.py
- update search space for sklearn ts regressors
* update automl.py and test_forecast.py for numpy array inputs
* add documentations to model.py
* add documentation for removing catboost regressor
* update automl.py
- _validate_ts_data() function
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
