* version update post release v1.2.2

* automl option

* import pandas

* remove automl.utils

* default

* test

* type hint and version update

* dependency update

* link to open in colab

* use packging.version to close #725

---------

Co-authored-by: Li Jiang <lijiang1@microsoft.com>
Co-authored-by: Li Jiang <bnujli@gmail.com>

* response filter

* rewrite implement based on the filter

* multi responses

* abs path

* code handling

* option to not use docker

* context

* eval_only -> raise_error

* notebook

* utils

* utils

* separate tests

* test

* test

* test

* test

* test

* test

* test

* test

* **config in test()

* test

* test

* filename

* extract code from text

* solve_problem; request_timeout in config

* improve

* move import statement

* improve code

* generate assertions

* constant

* configs for implement; voting

* doc

* execute code in docker

* success indicator of code executation in docker

* success indicator

* execute code

* strip n

* add cost in generate_code

* add docstr

* filename

* bytes

* check docker version

* print log

* python test

* remove api key address

* rename exit code

* success exit code

* datasets

* exit code

* recover openai tests

* cache and pattern match

* wait

* wait

* cache and test

* timeout test

* python image name and skip macos

* windows image

* docker images

* volume path and yaml

* win path -> posix

* extensions

* path

* path

* path

* path

* path

* path

* path

* path

* path

* path

* path

* skip windows

* path

* timeout in windows

* use_docker

* use_docker

* hot fix from #1000

---------

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

* make context optional

* better error handling and doc

* skip instantiation if no context

* skip test

* news update

* doc update

* avoid KeyError

* bump version to 1.2.1

* handle empty responses

* typo

* eval function

* math utils in autogen

* cleanup

* code utils

* remove check function from code response

* comment out test

* GPT-4

* increase request timeout

* name

* logging and error handling

* better doc

* doc

* codegen optimized

* GPT series

* text

* no demo example

* math

* import openai

* import openai

* azure model name

* azure model name

* openai version

* generate assertion if necessary

* condition to generate assertions

* init region key

* rename

* comments about budget

* prompt

---------

Co-authored-by: Susan Xueqing Liu <liususan091219@users.noreply.github.com>

* improve max_valid_n and doc

* Update README.md

Co-authored-by: Li Jiang <lijiang1@microsoft.com>

* add support for chatgpt

* notebook

* newline at end of file

* chatgpt notebook

* ChatGPT in Azure

* doc

* math

* warning, timeout, log file name

* handle import error

* doc update; default value

* paper

* doc

* docstr

* eval_func

* add a test func in completion

* update notebook

* update math notebook

* improve notebok

* lint and handle exception

* flake8

* exception in test

* add agg_method

* NameError

* refactor

* Update flaml/integrations/oai/completion.py

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

* Update flaml/integrations/oai/completion.py

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

* add example

* merge files from oai_eval_test

* Revert "merge files from oai_eval_test"
This reverts commit 1e6a550f91.

* merge

* save results to notebook_output

* update version and cache

* update doc

* save nb cell results to file

* fix typo in model name

* code improvements

* improve docstr

* docstr

* docstr on the Returns of test

---------

Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Li Jiang <lijiang1@microsoft.com>
Co-authored-by: Susan Xueqing Liu <liususan091219@users.noreply.github.com>

* workflow; model str; timeout

* voting

* notebook

* pull request

* recover workflow

* voted answer

* aoai

* ignore None answer

* default config

* note

* gpt-4

* n=5

* cleanup

* config name

* introduction

* readme

* avoid None

* add output/ to gitignore

* openai version

* invalid var

* comment long running cells

* improve max_valid_n and doc

* Update README.md

Co-authored-by: Li Jiang <lijiang1@microsoft.com>

* add support for chatgpt

* notebook

* newline at end of file

* chatgpt notebook

* ChatGPT in Azure

* doc

* math

* warning, timeout, log file name

* handle import error

* doc update; default value

* paper

* doc

* docstr

* eval_func

* prompt and messages

* remove confusing words

* notebook name

---------

Co-authored-by: Li Jiang <lijiang1@microsoft.com>
Co-authored-by: Susan Xueqing Liu <liususan091219@users.noreply.github.com>

* improve max_valid_n and doc

* Update README.md

Co-authored-by: Li Jiang <lijiang1@microsoft.com>

* newline at end of file

* doc

---------

Co-authored-by: Li Jiang <lijiang1@microsoft.com>
Co-authored-by: Susan Xueqing Liu <liususan091219@users.noreply.github.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>

* adding openai documentation

* adding openai documentation

* Update website/docs/Examples/Integrate - OpenAI.md

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

* Update website/docs/Examples/Integrate - OpenAI.md

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

* Update website/docs/Examples/Integrate - OpenAI.md

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

* Update website/docs/Examples/Integrate - OpenAI.md

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

* Update website/docs/Examples/Integrate - OpenAI.md

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

* addressing comments

* Update website/docs/Examples/Integrate - OpenAI.md

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

* Update website/docs/Examples/Integrate - OpenAI.md

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

* adding Azure

* rerun

* addressing comments about Azure

---------

Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>

* precommit: end-of-file-fixer

* exclude .gitignore

* apply

---------

Co-authored-by: Shaokun <shaokunzhang529@gmail.com>

checkpoint path may be named dir_or_data instead of value

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

* 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>

* 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>

* added hyperlink to github of example code

* 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