* 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.

* fix eval automl metric bug on val_loss inconsistency

* updating starting point search space to continuous

* shortening notebok

* feature names and importances

* None check

* StackingClassifier has no feature_importances_

* StackingClassifier has no feature_names_in_

* fix ner bug; refactor post processing

* fix too many values to unpack

* supporting id/token label for NER

Add space after comma in 'subscription_id='<azure-subscription-id>',resource_group='myresourcegroup')'

* Added test directory and core file to gitignore.

Closes #601.

* Fixed pipeline fit parameters.

Closes #600.

* Reverted changes to gitignore.

* add zeroshot notebook

* 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

* metric constraint documentation

* update link

* update notebook

* fix a bug in adding 'time_total_s' to result

* use the default multiple factor from config file

* update notebook

* format

* improve test

* revise test budget for macos

* bug fix in adding time_total_s

* increase performance check budget

* revise test

* update notebook

* uncomment test

* remove redundancy

* clear output

* remove n_jobs

* remove constraint in notebook

* increase budget

* revise test

* add python version

* use getattr

* improve code robustness

Co-authored-by: Qingyun Wu <qxw5138@psu.edu>

* fixing bug for ner

* removing global var

* adding class for trial counter

* adding notebook

* adding use_ray dict

* updating documentation for nlp

* update automl.py
- documentation update

* update test_forecast.py

* update model.py

* update automl_time_series_forecast.ipynb

* update time series forecast website examples

Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>

* Prepare for release

Co-authored-by: Moe Kayali <t-moekayali@microsoft.com>

* bug fix

* improve doc and code quality

Co-authored-by: Qingyun Wu

* fix a bug when using ray & update ray on aml
When using with_parameters(), the config argument must be the first argument in the trainable function.
* make training function runnable standalone

* max_iter < 2 -> no search

* use_ray in test

* eval_method in ts example

* check sign of constraints

* test metric constraint sign

* query logged runs

* mlflow log when using ray

* key check for newer version of ray #363

* catch importerror

* log and load AutoML model

* retrain if necessary when ensemble fails

* examples and documentation about how to use azureml + ray

* custom splitter
* NLP
* version number

* Add test_autohf_summarization.py

* adding seq2seq

* Update flaml/nlp/huggingface/trainer.py

* rouge metrics

Co-authored-by: XinZofStevens <xzhao4346@gmail.com>
Co-authored-by: JinzhuoWu <wujinzhuo0105@gmail.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>

A new documentation website. And:

* add actions for doc

* update docstr

* installation instructions for doc dev

* unify README and Getting Started

* rename notebook

* doc about best_model_for_estimator #340

* docstr for keep_search_state #340

* DNN

Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
Co-authored-by: Z.sk <shaokunzhang@psu.edu>