* Added test directory and core file to gitignore.

Closes #601.

* Fixed pipeline fit parameters.

Closes #600.

* Reverted changes to gitignore.

* 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>

* Update Installation.md

* Update website/docs/FAQ.md

* add zeroshot notebook

* Update Task-Oriented-AutoML.md

* update doc about scheduler exception

* remove assert

* Update website/docs/FAQ.md

* use zeroshot when no budget is given; custom_hp

* update Getting-Started

* protobuf version

* X_val

Added one more use case of tune.

* add bs restore test

* use default metric when not provided

* update documentation

* remove print

* period

* remove bs restore test

* Update website/docs/Use-Cases/Task-Oriented-AutoML.md

* handle non-flaml scheduler in flaml.tune

* revise time budget

* Update website/docs/Use-Cases/Tune-User-Defined-Function.md

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

* Update website/docs/Use-Cases/Tune-User-Defined-Function.md

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

* Update flaml/tune/tune.py

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

* add docstr

* remove random seed

* StopIteration

* StopIteration format

* format

* Update flaml/tune/tune.py

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

* revise docstr

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

* 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>

* version number

* add missing tasks in documentation

* update node-forge version

* 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

Solving issue #456 related to a typo on the webpage.

* 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

Fix for #445

Fix for issue #444

Fix Typo for issue 443

* data in csv

* support ray ObjectRef #365

* use object store to store data when using ray

* make lgbm tuning example a test

* homepage title

* homepage update

* update README

* max_iter < 2 -> no search

* use_ray in test

* eval_method in ts example

* check sign of constraints

* test metric constraint sign

* console log handler

* version update

* doc

* skippable steps

* notebook update

* constraint sign

* doc for constraints

* bug fix: define-by-run and unflatten_hierarchical

* const

* handle nested space in indexof()

* test grid search

* test suggestion

* model test

* >1 ckpts

* always increase iter count

* log total # iterations

* security patch

* make iter_per_learner consistent

* 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

update some examples for consistencies with others.

* simplify lgbm examples

* provide link to lgbm example script.

* simply lgbm example in the example script.

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

* examples and documentation about how to use azureml + ray

* custom splitter
* NLP
* version number

* reproducibility for random sampling #236

* doc update

* 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>