* Initial commit.
* Disable LLM response caching.
* Add teachability option to setup.py
* Modify test to use OAI_CONFIG_LIST as suggested in the docs.
* Expand unit test.
* Complete unit test.
* Add filter_dict
* details
* AnalysisAgent
* details
* More documentation and debug output.
* Support retrieval of any number of relevant memos, including zero.
* More robust analysis separator.
* cleanup
* teach_config
* refactoring
* For robustness, allow more flexibility on memo storage and retrieval.
* de-dupe the retrieved memos.
* Simplify AnalysisAgent. The unit tests now pass with gpt-3.5
* comments
* Add a verbosity level to control analyzer messages.
* refactoring
* comments
* Persist memory on disk.
* cleanup
* Use markdown to format retrieved memos.
* Use markdown in TextAnalyzerAgent
* Add another verbosity level.
* clean up logging
* notebook
* minor edits
* cleanup
* linter fixes
* Skip tests that fail to import openai
* Address reviewer feedback.
* lint
* refactoring
* Improve wording
* Improve code coverage.
* lint
* Use llm_config to control caching.
* lowercase notebook name
* Sort out the parameters passed through to ConversableAgent, and supply full docstrings for the others.
* lint
* Allow TextAnalyzerAgent to be given a different llm_config than TeachableAgent.
* documentation
* Modifications to run openai workflow.
* Test on just python 3.10.
Replace agent with agent teachable_agent as recommended.
* Test on python 3.9 instead of 3.10.
* Remove space from name -> teachableagent
---------
Co-authored-by: Li Jiang <bnujli@gmail.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Add group chat and retrieve agent example
* Fix link and models
* Support call rag in a group chat and not init with rag
* Fix n_results logic
* Update notebook
* Fix format
* Improve wording
* Update variable name
* Revert to main
* Update function call
* Update keys
* Update contents
* Update contents
* FORMATTING
* UPDATE - OAI __init__.py
* ruff
* ADD - notebook covering oai API configuration options and their different purposes
* ADD openai util updates so that the function just assumes the same environment variable name for all models, also added functionality for adding API configurations like api_base etc.
* ADD - updates to config_list_from_dotenv and tests for openai_util testing, update example notebook
* UPDATE - added working config_list_from_dotenv() with passing tests, and updated notebook
* UPDATE - code and tests to potentially get around the window build permission error, used different method of producing temporary files
---------
Co-authored-by: Ward <award40@LAMU0CLP74YXVX6.uhc.com>
* UPDATE - Updated retrieve_utils.py to have the ability to parse text from pdf files
* UNDO - change to recursive condition
* UPDATE - updated agentchat_RetrieveChat.ipynb to clarify which file types are accepted to be in the docs path
* ADD - missing import
* UPDATE - setup.py to have PyPDF2 in retrievechat
* RE-ADD - urls
* ADD - tests for retrieve utils, and removed deprecated PyPdf2
* Update agentchat_RetrieveChat.ipynb
* Update retrieve_utils.py
Fix format
* Update retrieve_utils.py
Replace print with logger
* UPDATE - added more specific exception to PDF decryption try/catch
* FIX - typo, return statement at wrong indentation in extract_text_from_pdf
---------
Co-authored-by: Ward <award40@LAMU0CLP74YXVX6.uhc.com>
Co-authored-by: Li Jiang <bnujli@gmail.com>
* Improves clarity and fixes punctuation in README and Multi-agent documentation
* fix broken colab link to agentchat_groupchat_research.ipynb (others are fine)
* fix typos, improves readability
* fix bug for windows
* fix bug for windows
* more clear example
* link to example
* add test
* format
* comment
* fix assertion error
* fix test error and links
---------
Co-authored-by: Chi Wang (MSR) <chiw@microsoft.com>
* group chat for visualization
* show figure
* webpage update
* link update
* example 2
* example 2
---------
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* test
* chart
* plan
* separate
* bump version to 2.0.1
* explain plan and code/lang
* notebook update
* notebook update
* typo
* plan
* match can be None
* max consecutive auto reply
* chess notebook
* link to notebook
* clear history
* filter
* **context -> context
* format str template
* groupchat
* register class specific reply
* groupchat notebook
* move human reply into generate_reply
* arg in config
* colab link
* remove room
* rename
* update colab link
* typo
* upload file instruction
* update system message and notebooks
* update notebooks
* notebook test
* aoai api version and exclusion
* gpt-3.5-turbo
* dict check
* change model for test
* endpoints, cache_path and func description update
* model list
* gitter -> discord
* add funccall example and doc
* revise to comments
* Update website/docs/Use-Cases/Auto-Generation.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* revise
* update
* minor update
* add test notebook
* update
---------
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* update funccall
* code format
* update to comments
* update notebook
* remove test for py3.7
* allow funccall to class functions
* add test and clean up notebook
* revise notebook and test
* update
* update mathagent
* Update flaml/autogen/agent/agent.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/autogen/agent/user_proxy_agent.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* revise to comments
* revise function call design, notebook and test. add doc
* code format
* ad message_to_dict function
* update mathproxyagent
* revise docstr
* update
* Update flaml/autogen/agent/math_user_proxy_agent.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/autogen/agent/math_user_proxy_agent.py
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* Update flaml/autogen/agent/user_proxy_agent.py
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* simply funccall in userproxyagent, rewind auto-gen.md, revise to comments
* code format
* update
* remove notebook for another pr
* revise oai_conversation part in agent, revise function exec in user_proxy_agent
* update test_funccall
* update
* update
* fix pydantic version
* Update test/autogen/test_agent.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* fix bug
* fix bug
* update
* update is_termination_msg to accept dict
---------
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
Co-authored-by: Li Jiang <bnujli@gmail.com>
* add agent notebook and documentation
* fix bug
* set flush to True when printing msg in agent
* add a math problem in agent notebook
* remove
* header
* improve notebook doc
* notebook update
* improve notebook example
* improve doc
* improve notebook doc
* improve print
* doc
* human_input_mode
* human_input_mode str
* indent
* indent
* Update flaml/autogen/agent/user_proxy_agent.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update notebook/autogen_agent.ipynb
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update notebook/autogen_agent.ipynb
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update notebook/autogen_agent.ipynb
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* renaming and doc format
* typo
---------
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* 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
* 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 1e6a550f913bb94df6e9680934ccb7175d00702e.
* 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>
* add basic support to Spark dataframe
add support to SynapseML LightGBM model
update to pyspark>=3.2.0 to leverage pandas_on_Spark API
* clean code, add TODOs
* add sample_train_data for pyspark.pandas dataframe, fix bugs
* improve some functions, fix bugs
* fix dict change size during iteration
* update model predict
* update LightGBM model, update test
* update SynapseML LightGBM params
* update synapseML and tests
* update TODOs
* Added support to roc_auc for spark models
* Added support to score of spark estimator
* Added test for automl score of spark estimator
* Added cv support to pyspark.pandas dataframe
* Update test, fix bugs
* Added tests
* Updated docs, tests, added a notebook
* Fix bugs in non-spark env
* Fix bugs and improve tests
* Fix uninstall pyspark
* Fix tests error
* Fix java.lang.OutOfMemoryError: Java heap space
* Fix test_performance
* Update test_sparkml to test_0sparkml to use the expected spark conf
* Remove unnecessary widgets in notebook
* Fix iloc java.lang.StackOverflowError
* fix pre-commit
* Added params check for spark dataframes
* Refactor code for train_test_split to a function
* Update train_test_split_pyspark
* Refactor if-else, remove unnecessary code
* Remove y from predict, remove mem control from n_iter compute
* Update workflow
* Improve _split_pyspark
* Fix test failure of too short training time
* Fix typos, improve docstrings
* Fix index errors of pandas_on_spark, add spark loss metric
* Fix typo of ndcgAtK
* Update NDCG metrics and tests
* Remove unuseful logger
* Use cache and count to ensure consistent indexes
* refactor for merge maain
* fix errors of refactor
* Updated SparkLightGBMEstimator and cache
* Updated config2params
* Remove unused import
* Fix unknown parameters
* Update default_estimator_list
* Add unit tests for spark metrics
* 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
* WIP
* WIP - Notes below
Got to the point where the methods from AutoML are pulled to
GenericTask. Started removing private markers and removing the passing
of automl to these methods. Done with decide_split_type, started on
prepare_data. Need to do the others after
* Re-add generic_task
* Fix tests: add Task.__str__
* Fix tests: test for ray.ObjectRef
* Hotwire TS_Sklearn wrapper to fix test fail
* Remove unused data size field from Task
* Fix import for CLASSIFICATION in notebook
* Update flaml/automl/data.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Fix review comments
* Fix task -> str in custom learner constructor
* Remove unused CLASSIFICATION imports
* Hotwire TS_Sklearn wrapper to fix test fail by setting
optimizer_for_horizon == False
* Revert changes to the automl_classification and pin FLAML version
* Fix imports in reverted notebook
* Fix FLAML version in automl notebooks
* Fix ml.py line endings
* Fix CLASSIFICATION task import in automl_classification notebook
* Uncomment pip install in notebook and revert import
Not convinced this will work because of installing an older version of
the package into the environment in which we're running the tests, but
let's see.
* Revert c6a5dd1a0
* Revert "Revert c6a5dd1a0"
This reverts commit e55e35adea03993de87b23f092b14c6af623d487.
* Black format model.py
* Bump version to 1.1.2 in automl_xgboost
* Add docstrings to the Task ABC
* Fix import in custom_learner
* fix 'optimize_for_horizon' for ts_sklearn
* remove debugging print statements
* Check for is_forecast() before is_classification() in decide_split_type
* Attempt to fix formatting fail
* Another attempt to fix formatting fail
* And another attempt to fix formatting fail
* Add type annotations for task arg in signatures and docstrings
* Fix formatting
* Fix linting
---------
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
Co-authored-by: EgorKraevTransferwise <egor.kraev@transferwise.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Kevin Chen <chenkevin.8787@gmail.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
* 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>
* add cost budget; move loc of make_dir
* support openai completion
* install pytest in workflow
* skip openai test
* test openai
* path for docs rebuild
* install datasets
* signal
* notebook
* notebook in workflow
* optional arguments and special params
* key -> k
* improve readability
* assumption
* optimize for model selection
* larger range of max_tokens
* notebook
* python package workflow
* skip on win
* notebook test
* add ipykernel, remove except
* only create dir if not empty
* Stop sequential tuning when result is None
* fix reproducibility of global search
* save gs seed
* use get to avoid KeyError
* test
* 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
* added a link to documentation webpage in notebook time_series_forcast
* added a link to documentation webpage in notebook time_series_forcast
* Update notebook/automl_time_series_forecast.ipynb
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* complete output
* added all cell output
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: zsk <shaokunzhang529@gmail.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* 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>
* 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
* 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
if save_best_model_per_estimator is False and retrain_final is True, unfit the model after evaluation in HPO.
retrain if using ray.
update ITER_HP in config after a trial is finished.
change prophet logging level.
example and notebook update.
allow settings to be passed to AutoML constructor. Are you planning to add multi-output-regression capability to FLAML #192 Is multi-tasking allowed? #277 can pass the auotml setting to the constructor instead of requiring a derived class.
remove model_history.
checkpoint bug fix.
* model_history meaning save_best_model_per_estimator
* ITER_HP
* example update
* prophet logging level
* comment update in forecast notebook
* print format improvement
* allow settings to be passed to AutoML constructor
* checkpoint bug fix
* time limit for autohf regression test
* skip slow test on macos
* cleanup before del
* limit time and memory
* separate tests
* lrl1 can't be limited by limit_resource
* free memory when possible
* passthrough=False when ensemble fails;
retrain when trained_estimator is None
* use callback to for resource limit
* handle lower version of xgb with no callback
* free mem ratio
* reduce verbosity
* retrain_final when max_iter==1
* remove trained_estimator from result
* model_history
* wheel
* retrain time as best_config_train_time
* ci: libomp version for xgboost on macos
* limit_resource not working in windows
* test pickle load
* mute forecaster
* notebook update
* check hard
* preventive callback
* add use_ray
* Integrate multivariate time series forecasting, now supports
continuous and categorical variables
- update data.py to transform time series data
- update search space
- update documentations to reflect changes
- update test_forecast.py
- rename 'forecast' task to 'ts_forecast' task
* update automl.py and test_forecast.py
* update forecast notebook
* update README.md and setup.py
* update ml.py and test_forecast.py
- make "ds" and "y" constant variables
* replace constants with constant variables
* bump version to 0.7.0
* update setup.py
- support 'forecast' and 'ts_forecast'
* update automl.py and data.py
- support 'forecast' and 'ts_forecast' tasks
* warning -> info for low cost partial config
#195, #110
* when n_estimators < 0, use trained_estimator's
* log debug info
* test random seed
* remove "objective"; avoid ZeroDivisionError
* hp config to estimator params
* check type of searcher
* default n_jobs
* try import
* Update searchalgo_auto.py
* CLASSIFICATION
* auto_augment flag
* min_sample_size
* make catboost optional
* config in result
* value can be float
* pytorch notebook example
* docker, pre-commit
* max_failure (#192); early_stop
* extend starting_points (#196)
Co-authored-by: Chi Wang (MSR) <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qw2ky@virginia.edu>
* increase test coverage
* use define by run only when needed
* warmstart bs
* classification -> binary, multi
* warm start with evaluated rewards
* data transformer; resource attr for gs
* BlendSearchTuner bug fix and unittest
* bug fix
* docstr and import
* task type
* remove catboost training dir
* close#48
* bs for hierarchical space. close#85
* retrain for hierarchical space
* clean ml (#180)
Co-authored-by: Qingyun Wu <qxw5138@psu.edu>
* support ranking task
* examples
* cv shuffle
* forecast api and implementation cleaner
* period constraints
* delete groups after fit
* non hashable value out of signature
* parallel trials
* add random in _search_parallel
* fix bug in retraining
* check memory constraint before training
* retrain_full
* log custom metric
* retraining budget check
* sample size check before retrain
* remove 'time2eval' from result
* report 'total_search_time' in result
* rename total_search_time to wall_clock_time
* rename train_loss boolean to log_training_metric
* set default train_loss to None
* exclude oom result
* log retrained model
* no subsample
* doc str
* notebook
* predicted value is NaN for sarimax
* version
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qxw5138@psu.edu>
* added 'forecast' task with estimators ['fbprophet', 'arima', 'sarimax']
* update setup.py
* add TimeSeriesSplit to 'regression' and 'classification' task
* add 'time' split_type for 'classification' and 'regression' task
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* feature importance
* variable name
* Update test/test_split.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update test/test_forecast.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* prophet installation fail in windows
* upload flaml_forecast.ipynb
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* subspace in flow2
* search space and trainable from AutoML
* experimental features: multivariate TPE, grouping, add_evaluated_points
* test experimental features
* readme
* define by run
* set time_budget_s for bs
Co-authored-by: liususan091219 <Xqq630517>
* version
* acl
* test define_by_run_func
* size
* constraints
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* api doc for chacha
* update params
* link to paper
* update dataset id
Co-authored-by: Chi Wang (MSR) <chiw@microsoft.com>
Co-authored-by: Qingyun Wu <qiw@microsoft.com>
* pickle the AutoML object
* get best model per estimator
* test deberta
* stateless API
* pickle the AutoML object
* get best model per estimator
* test deberta
* stateless API
* prevent divide by zero
* test roberta
* BlendSearchTuner
* sync
* version number
* update gitignore
* delta time
* reindex columns when dropping int-indexed columns
* add seed
* add seed in Args
* merge
* init upload of ChaCha
* remove redundancy
* add back catboost
* improve AutoVW API
* set min_resource_lease in VWOnlineTrial
* docstr
* rename
* docstr
* add docstr
* improve API and documentation
* fix name
* docstr
* naming
* remove max_resource in scheduler
* add TODO in flow2
* remove redundancy in rearcher
* add input type
* adapt code from ray.tune
* move files
* naming
* documentation
* fix import error
* fix format issues
* remove cb in worse than test
* improve _generate_all_comb
* remove ray tune
* naming
* VowpalWabbitTrial
* import error
* import error
* merge test code
* scheduler import
* fix import
* remove
* import, minor bug and version
* Float or Categorical
* fix default
* add test_autovw.py
* add vowpalwabbit and openml
* lint
* reorg
* lint
* indent
* add autovw notebook
* update notebook
* update log msg and autovw notebook
* update autovw notebook
* update autovw notebook
* add available strings for model_select_policy
* string for metric
* Update vw format in flaml/onlineml/trial.py
Co-authored-by: olgavrou <olgavrou@gmail.com>
* make init_config optional
* add _setup_trial_runner and update notebook
* space
Co-authored-by: Chi Wang (MSR) <chiw@microsoft.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qiw@microsoft.com>
Co-authored-by: olgavrou <olgavrou@gmail.com>
* add customized lgbm learner
* add comments
* fix format issue
* format
* OpenMLError
* add test
* add notebook
Co-authored-by: Chi Wang (MSR) <chiw@microsoft.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* pickle the AutoML object
* get best model per estimator
* test deberta
* stateless API
* Add Gitter badge (#41)
* prevent divide by zero
* test roberta
* BlendSearchTuner
Co-authored-by: Chi Wang (MSR) <chiw@microsoft.com>
Co-authored-by: The Gitter Badger <badger@gitter.im>
* xgboost notebook
* finetuning notebook
* finetuning test
* experimental nni support
* support nested search space
* log file name
* record training_iteration
* eps
* reset times
* std set to default step size if 0
* v0.2.2
separate the HPO part into the module flaml.tune
enhanced implementation of FLOW^2, CFO and BlendSearch
support parallel tuning using ray tune
add support for sample_weight and generic fit arguments
enable mlflow logging
Co-authored-by: Chi Wang (MSR) <chiw@microsoft.com>
Co-authored-by: qingyun-wu <qw2ky@virginia.edu>
* set default logging level to INFO
* remove unnecessary import
* API future compatibility
* add test for customized learner
* test dependency
Co-authored-by: Chi Wang (MSR) <chiw@microsoft.com>
Shruti Patel