* 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
* Pending changes exported from your codespace
* Update flaml/automl.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/automl.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/ml.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/ml.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update website/docs/Examples/Integrate - Scikit-learn Pipeline.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* added documentation for new metric
* Update flaml/ml.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* minor notebook changes
* Update Integrate - Scikit-learn Pipeline.md
* Update notebook/automl_classification.ipynb
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update integrate_azureml.ipynb
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* 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>
As described in #777, I had trouble executing the setup using zsh.
Eventually, I noticed that I had to escape the brackets.
My proposed change includes both brackets to be escaped, however for me it was enough to escape the opening one only, since as far as I know a trailing non-escaped closing bracket will then be recognized, accordingly.
* rm classification head in nlp
* rm classification head in nlp
* rm classification head in nlp
* adding test cases for switch classification head
* adding test cases for switch classification head
* Update test/nlp/test_autohf_classificationhead.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* adding test cases for switch classification head
* run each test separately
* skip classification head test on windows
* disabling wandb reporting
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* fix test nlp custom metric
* Update website/docs/Examples/AutoML-NLP.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update website/docs/Examples/AutoML-NLP.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* fix test nlp custom metric
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* add vw version requirement
* vw version
* version range
* add documentation
* vw version range
* skip test on py3.10
* vw version
* rephrase
* don't install vw on py 3.10
* move import location
* remove inherit
* 3.10 in version
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* update forecasting with exogeneous variables example
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update forecasting with exogeneous variables example on website
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* rerun automl_time_series_forecast with new predict function for tft
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* correct spelling error
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* 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>
* add pipeline tuner component and dependencies.
* clean code.
* do not need force rerun.
* replace the resources.
* update metrics retrieving.
* Update test/pipeline_tuning_example/requirements.txt
* Update test/pipeline_tuning_example/train/env.yaml
* Update test/pipeline_tuning_example/tuner/env.yaml
* Update test/pipeline_tuning_example/tuner/tuner_func.py
* Update test/pipeline_tuning_example/data_prep/env.yaml
* fix issues found by lint with flake8.
* add documentation
* add data.
* do not need AML resource for local run.
* AML -> AzureML
* clean code.
* Update website/docs/Examples/Tune-AzureML pipeline.md
* rename and add pip install.
* update figure name.
* align docs with code.
* remove extra line.
