doc refactor to master (#648)

* initial commit for document refactor (#533)

* enable sphinx

* fix docs/readme link

* update conf

* use mkdocs to build homepage

* Update mkdocs.yml

use docs/README as main

* delete sphinx file

* add nav to mkdocs config

* fix mkdocs bug

* add requirement for online build

* clean requirements.txt

* add contribution

* change requirements file location

* delete sphinx from gitignore

* mnist examples doc (#566)

* mnist examples doc

* update

* update

* update

* update

* update

* Docs refactor of Tutorial (QuickStart, Tuners, Assessors) (#554)

* Refactor of QuickStart

* fix some typo

* Make new changes based on suggestions

* update successful INFO

* update Tuners

* update Tuners:overview

* Update Tuners.md

* Add Assessor.md

* update

* update

* mkdocs.yml

* Update QuickStart.md

* update

* update

* update

* update

* update

* add diff

* modified QuickStart.md and add mnist without nni example

* update

* small change

* update

* update

* update

* update

* update and refactor the mnist.py

* update

* update working process

* refator the mnist.py

* update

* update

* update mkdocs.md

* add metis tuner

* update QuickStart webUI part

* update capture

* update capture

* update description

* update picture for assessor

* update

* modified mkdocs.yml

* update Tuners.md

* test format

* update Tuner.md

* update Tuner.md

* change display format

* fix typo

* update

* fix typo

* fix typo and rename customize_Advisor

* fix typo and modified

* Dev doc: Add docs for Trials, SearchSpace, Annotation and GridSearch (#569)

* add Trials.md

* add Trials.md

* add Trials.md

* add Trials.md

* add docs

* add docs

* add docs

* add docs

* add docs

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* update triaL.MD

* update triaL.MD

* update triaL.MD

* update triaL.MD

* update triaL.MD

* add grid search tuner doc

* add grid search tuner doc

* Chec dev doc (#606)

* multiPhase doc

* updates

* updates

* updates

* updates

* updates

* updates

* update dev-doc to sphinx (#630)

* add trigger (#544)

* NNI logging architecture improvement  (#539)

* Removed unused log code, refactor to rename some class name in nni sdk and trial_tools

* Fix the regression bug that loca/remote mode doesnt work

* [WebUI] Fix issue#517 & issue#459 (#524)

* [WebUI] Fix issue#517 & issue#459

* update

* [Logging architecture refactor] Remove unused metrics related code in nni trial_tools, support kubeflow mode for logging architecture refactor (#551)

* Remove unused metrics related code in nni trial_tools, support kubeflow mode for logging architecture refactor

* Doc typo and format fixes (#560)

* fix incorrect document

* fix doc format and typo

* fix state transition (#504)

* Add enas nni version from contributor (#557)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* update readme

* update

* fix path

* update reference

* fix bug in config file

* update nni_arch_overview.png

* update

* update

* update

* add enas_nni

* Code coverage report (#559)

* Add UT code coverage report

* updates

* updates

* updates

* updates

* updates

* updates

* integration test python code coverage report

* Updating Readme to add the Related Projects like PAI, KubeLauncher and MMdnn (#565)

* Adding related projects to Readme

* Fix remote TrainingService bug, change forEach to "for of" (#564)

trial job could not be stopped in remote machine when experiment is stopped, because awit/async does not work normally in forEach, refer https://codeburst.io/javascript-async-await-with-foreach-b6ba62bbf404

.

* To install the whole nni in an virtual environment (#538)

* support venv

* adapt venv

* adapt venv

* adapt venv

* adapt venv

* new test

* new test

* new test

* support venv

* support venv

* support venv

* support venv

* support venv

* support venv

* support venv

* colorful output for mac

* colorful output for mac

* permission denied in /tmp

* permission denied in /tmp

* permission denied in /tmp

* remove unused variable

* final

* remove build python

* Make it feasible for annotation whether to add an extra line "nni.get_next_parameter()" or not (#526)

* fix bug

* add docs

* add ut

* add ut

* add to ci

* update doc

* update doc

* update ut

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* test

* test

* test

* test

* test

* test

* test

* test

* test

* test

* revert

* refactor

* refactor

* s

* merge

* fix annotation for extra line

* add deprecation warning

* fix permision deny (#567)

* Add Metis Tuner (#534)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* update readme

* update

* fix path

* update reference

* fix bug in config file

* update nni_arch_overview.png

* update

* update

* update

* add metis tuner code

* 1. fix bug about import 2.update other sdk file

* add auto-gbdt-example and remove unused code

* add metis_tuner into README

* update the README

* update README | remove unused variable

* fix typo

* add sklearn into requirments

* Update src/sdk/pynni/nni/metis_tuner/metis_tuner.py

add default value in __init__
Co-Authored-By: xuehui1991 <xuehui@microsoft.com>

* Update docs/HowToChooseTuner.md
Co-Authored-By: xuehui1991 <xuehui@microsoft.com>

* Update docs/HowToChooseTuner.md
Co-Authored-By: xuehui1991 <xuehui@microsoft.com>

* fix typo | add more comments

* Change WARNING to INFO (#574)

change the warning level to info level when expand relative path
add nnictl --version log
update readme.md

* Fix some bugs in doc and log (#561)

* fix some bugs in doc and log

* The learning rate focus more on validation sets accuracy than training sets accuracy.

*  Fix a race condidtion issue in trial_keeper for reading log from pipe (#578)

* Fix a race condidtion issue in trial_keeper for reading log from pipe

* [WebUI] Fix issue#458 about final result as dict (#563)

* [WebUI] Fix issue#458 about final result as dict

* Fix comments

* fix bug

* support frameworkcontroller log (#572)

support frameworkcontroller log

* Dev weight sharing (#568) (#576)

* Dev weight sharing (#568)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* Dev weight sharing update doc (#577)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* add example section

* Dev weight sharing update (#579)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* add example section

* update weight sharing tutorial

* Dev weight sharing (#581)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* add example section

* update weight sharing tutorial

* fix divide by zero risk

* update tuner thread exception handling

* fix bug for async test

* Add frameworkcontroller document (#530)

Add frameworkcontroller document.
Fix other document small issues.

* [WebUI] Show trial log for pai and k8s (#580)

* [WebUI] Show trial log for pai and k8s

* fix lint

* Fix comments

* [WebUI] Show trial log for pai and k8s (#580)

* [WebUI] Show trial log for pai and k8s

* fix lint

* Fix comments

* add __init__.py to metis_tuner (#588)

* [Document] Update webui doc (#587)

* Update webui document

* update

* Update Dockerfile and README (#589)

* fix some bugs in doc and log

* The learning rate focus more on validation sets accuracy than training sets accuracy.

* update Dockerfile and README

* Update README.md

Merge to branch v0.5

* [WebUI] Fix bug (#591)

* fix bug

* fix bug of background

* update

* update

* add frameworkcontroller platform

* update README in metis and update RuntimeError info (#595)

* update README in metis and update RuntimeError

* fix typo

* add numerical choice check

* update

* udpate NFS setup tutorial (#597)

* Remove unused example (#600)

* update README in metis and update RuntimeError

* remove smart params

* Update release note (#603)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md
…

* update doc: overview (#555)

* doc overview

* update overview

* modification

* update overview

* update

* update

* update

* update

* Delete mkdocs.yml

* cifar10 example doc (#573)

* add cifar10 examples

* add search space and result

* update

* update typo

* update

* update

* Update doc: refactor ExperimentConfig.md (#602)

* fix doc

* add link in doc

* update

* add nnictl package cmd

* update doc index & add api reference (#636)

* add trigger (#544)

* NNI logging architecture improvement  (#539)

* Removed unused log code, refactor to rename some class name in nni sdk and trial_tools

* Fix the regression bug that loca/remote mode doesnt work

* [WebUI] Fix issue#517 & issue#459 (#524)

* [WebUI] Fix issue#517 & issue#459

* update

* [Logging architecture refactor] Remove unused metrics related code in nni trial_tools, support kubeflow mode for logging architecture refactor (#551)

* Remove unused metrics related code in nni trial_tools, support kubeflow mode for logging architecture refactor

* Doc typo and format fixes (#560)

* fix incorrect document

* fix doc format and typo

* fix state transition (#504)

* Add enas nni version from contributor (#557)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* update readme

* update

* fix path

* update reference

* fix bug in config file

* update nni_arch_overview.png

* update

* update

* update

* add enas_nni

* Code coverage report (#559)

* Add UT code coverage report

* updates

* updates

* updates

* updates

* updates

* updates

* integration test python code coverage report

* Updating Readme to add the Related Projects like PAI, KubeLauncher and MMdnn (#565)

* Adding related projects to Readme

* add Trials.md

* add Trials.md

* add Trials.md

* Fix remote TrainingService bug, change forEach to "for of" (#564)

trial job could not be stopped in remote machine when experiment is stopped, because awit/async does not work normally in forEach, refer https://codeburst.io/javascript-async-await-with-foreach-b6ba62bbf404

.

* add Trials.md

* add docs

* To install the whole nni in an virtual environment (#538)

* support venv

* adapt venv

* adapt venv

* adapt venv

* adapt venv

* new test

* new test

* new test

* support venv

* support venv

* support venv

* support venv

* support venv

* support venv

* support venv

* colorful output for mac

* colorful output for mac

* permission denied in /tmp

* permission denied in /tmp

* permission denied in /tmp

* remove unused variable

* final

* remove build python

* Make it feasible for annotation whether to add an extra line "nni.get_next_parameter()" or not (#526)

* fix bug

* add docs

* add ut

* add ut

* add to ci

* update doc

* update doc

* update ut

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* add ut to ci

* test

* test

* test

* test

* test

* test

* test

* test

* test

* test

* revert

* refactor

* refactor

* s

* merge

* fix annotation for extra line

* add deprecation warning

* fix permision deny (#567)

* Add Metis Tuner (#534)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* update readme

* update

* fix path

* update reference

* fix bug in config file

* update nni_arch_overview.png

* update

* update

* update

* add metis tuner code

* 1. fix bug about import 2.update other sdk file

* add auto-gbdt-example and remove unused code

* add metis_tuner into README

* update the README

* update README | remove unused variable

* fix typo

* add sklearn into requirments

* Update src/sdk/pynni/nni/metis_tuner/metis_tuner.py

add default value in __init__
Co-Authored-By: xuehui1991 <xuehui@microsoft.com>

* Update docs/HowToChooseTuner.md
Co-Authored-By: xuehui1991 <xuehui@microsoft.com>

* Update docs/HowToChooseTuner.md
Co-Authored-By: xuehui1991 <xuehui@microsoft.com>

* fix typo | add more comments

* Change WARNING to INFO (#574)

change the warning level to info level when expand relative path
add nnictl --version log
update readme.md

* Fix some bugs in doc and log (#561)

* fix some bugs in doc and log

* The learning rate focus more on validation sets accuracy than training sets accuracy.

*  Fix a race condidtion issue in trial_keeper for reading log from pipe (#578)

* Fix a race condidtion issue in trial_keeper for reading log from pipe

* [WebUI] Fix issue#458 about final result as dict (#563)

* [WebUI] Fix issue#458 about final result as dict

* Fix comments

* fix bug

* support frameworkcontroller log (#572)

support frameworkcontroller log

* Dev weight sharing (#568) (#576)

* Dev weight sharing (#568)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* Dev weight sharing update doc (#577)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* add example section

* Dev weight sharing update (#579)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* add example section

* update weight sharing tutorial

* Dev weight sharing (#581)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* simple weight sharing

* update gitignore file

* change tuner codedir to relative path

* add python cache files to gitignore list

* move extract scalar reward logic from dispatcher to tuner

* update tuner code corresponding to last commit

* update doc for receive_trial_result api change

* add numpy to package whitelist of pylint

* distinguish param value from return reward for tuner.extract_scalar_reward

* update pylintrc

* add comments to dispatcher.handle_report_metric_data

* update install for mac support

* fix root mode bug on Makefile

* Quick fix bug: nnictl port value error (#245)

* fix port bug

* Dev exp stop more (#221)

* Exp stop refactor (#161)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* fix setup.py (#115)

* Add DAG model configuration format for SQuAD example.

* Explain config format for SQuAD QA model.

* Add more detailed introduction about the evolution algorithm.

* Fix install.sh add add trial log path (#109)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* show trial log path

* update document

* fix install.sh

* set default vallue for maxTrialNum and maxExecDuration

* fix nnictl

* Dev smac (#116)

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* modify example config path to relative path and increase maxTrialNum (#94)

* modify example config path to relative path and increase maxTrialNum

* add document

* support conda (#90) (#110)

* support install from venv and travis CI

* support install from venv and travis CI

* support install from venv and travis CI

* support conda

* support conda

* modify example config path to relative path and increase maxTrialNum

* undo messy commit

* undo messy commit

* Support pip install as root (#77)

* Typo on #58 (#122)

* PAI Training Service implementation (#128)

* PAI Training service implementation
**1. Implement PAITrainingService
**2. Add trial-keeper python module, and modify setup.py to install the module
**3. Add PAItrainingService rest server to collect metrics from PAI container.

* fix datastore for multiple final result (#129)

* Update NNI v0.2 release notes (#132)

Update NNI v0.2 release notes

* Update setup.py Makefile and documents (#130)

* update makefile and setup.py

* update makefile and setup.py

* update document

* update document

* Update Makefile no travis

*  update doc

*  update doc

* fix convert from ss to pcs (#133)

* Fix bugs about webui (#131)

* Fix webui bugs

* Fix tslint

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* Merge branch V0.2 to Master (#143)

* webui logpath and document (#135)

* Add webui document and logpath as a href

* fix tslint

* fix comments by Chengmin

* Pai training service bug fix and enhancement (#136)

* Add NNI installation scripts

* Update pai script, update NNI_out_dir

* Update NNI dir in nni sdk local.py

* Create .nni folder in nni sdk local.py

* Add check before creating .nni folder

* Fix typo for PAI_INSTALL_NNI_SHELL_FORMAT

* Improve annotation (#138)

* Improve annotation

* Minor bugfix

* Selectively install through pip (#139)

Selectively install through pip 
* update setup.py

* fix paiTrainingService bugs (#137)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* Add documentation for NNI PAI mode experiment (#141)

* Add documentation for NNI PAI mode

* Fix typo based on PR comments

* Exit with subprocess return code of trial keeper

* Remove additional exit code

* Fix typo based on PR comments

* update doc for smac tuner (#140)

* Revert "Selectively install through pip (#139)" due to potential pip install issue (#142)

* Revert "Selectively install through pip (#139)"

This reverts commit 1d174836.

* Add exit code of subprocess for trial_keeper

* Update README, add link to PAImode doc

* fix bug (#147)

* Refactor nnictl and add config_pai.yml (#144)

* fix nnictl bug

* add hdfs host validation

* fix bugs

* fix dockerfile

* fix install.sh

* update install.sh

* fix dockerfile

* Set timeout for HDFSUtility exists function

* remove unused TODO

* fix sdk

* add optional for outputDir and dataDir

* refactor dockerfile.base

* Remove unused import in hdfsclientUtility

* add config_pai.yml

* refactor nnictl create logic and add colorful print

* fix nnictl stop logic

* add annotation for config_pai.yml

* add document for start experiment

* fix config.yml

* fix document

* Fix trial keeper wrongly exit issue (#152)

* Fix trial keeper bug, use actual exitcode to exit rather than 1

* Fix bug of table sort (#145)

* Update doc for PAIMode and v0.2 release notes (#153)

* Update v0.2 documentation regards to release note and PAI training service

* Update document to describe NNI docker image

* fix antd (#159)

* refactor experiment stopping logic

* support change concurrency

* remove trialJobs.ts

* trivial changes

* fix bugs

* fix bug

* support updating maxTrialNum

* Modify IT scripts for supporting multiple experiments

* Update ci (#175)

* Update RemoteMachineMode.md (#63)

* Remove unused classes for SQuAD QA example.

* Remove more unused functions for SQuAD QA example.

* Fix default dataset config.

* Add Makefile README (#64)

* update document (#92)

* Edit readme.md

* updated a word

* Update GetStarted.md

* Update GetStarted.md

* refact readme, getstarted and write your trial md.

* Update README.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Update WriteYourTrial.md

* Fix nnictl bugs and add new feature (#75)

* fix nnictl bug

* fix nnictl create bug

* add experiment status logic

* add more information for nnictl

* fix Evolution Tuner bug

* refactor code

* fix code in updater.py

* fix nnictl --help

* fix classArgs bug

* update check response.status_code logic

* remove Buffer warning (#100)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* Add support for debugging mode

* modify CI cuz of refracting exp stop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* update CI for expstop

* file saving

* fix issues from code merge

* remove $(INSTALL_PREFIX)/nni/nni_manager before install

* fix indent

* fix merge issue

* socket close

* update port

* fix merge error

* modify ci logic in nnimanager

* fix ci

* fix bug

* change suspended to done

* update ci (#229)

* update ci

* update ci

* update ci (#232)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update ci (#233)

* update ci

* update ci

* update azure-pipelines

* update azure-pipelines

* update azure-pipelines

* run.py (#238)

* Nnupdate ci (#239)

* run.py

* test ci

* Nnupdate ci (#240)

* run.py

* test ci

* test ci

* Udci (#241)

* run.py

* test ci

* test ci

* test ci

* update ci (#242)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh (#244)

* run.py

* test ci

* test ci

* test ci

* update ci

* revert install.sh

* add comments

* remove assert

* trivial change

* trivial change

* update Makefile (#246)

* update Makefile

* update Makefile

* quick fix for ci (#248)

* add update trialNum and fix bugs (#261)

* Add builtin tuner to CI (#247)

* update Makefile

* update Makefile

* add builtin-tuner test

* add builtin-tuner test

* refractor ci

* update azure.yml

* add built-in tuner test

* fix bugs

* Doc refactor (#258)

* doc refactor

* image name refactor

* Refactor nnictl to support listing stopped experiments. (#256)

Refactor nnictl to support listing stopped experiments.

* Show experiment parameters more beautifully (#262)

* fix error on example of RemoteMachineMode (#269)

* add pycharm project files to .gitignore list

* update pylintrc to conform vscode settings

* fix RemoteMachineMode for wrong trainingServicePlatform

* Update docker file to use latest nni release (#263)

* fix bug about execDuration and endTime (#270)

* fix bug about execDuration and endTime

* modify time interval to 30 seconds

* refactor based on Gems's suggestion

* for triggering ci

* Refactor dockerfile (#264)

* refactor Dockerfile

* Support nnictl tensorboard (#268)

support tensorboard

* Sdk update (#272)

* Rename get_parameters to get_next_parameter

* annotations add get_next_parameter

* updates

* updates

* updates

* updates

* updates

* add experiment log path to experiment profile (#276)

* refactor extract reward from dict by tuner

* update Makefile for mac support, wait for aka.ms support

* refix Makefile for colorful echo

* unversion config.yml with machine information

* sync graph.py between tuners & trial of ga_squad

* sync graph.py between tuners & trial of ga_squad

* copy weight shared ga_squad under weight_sharing folder

* mv ga_squad code back to master

* simple tuner & trial ready

* Fix nnictl multiThread option

* weight sharing with async dispatcher simple example ready

* update for ga_squad

* fix bug

* modify multihead attention name

* add min_layer_num to Graph

* fix bug

* update share id calc

* fix bug

* add save logging

* fix ga_squad tuner bug

* sync bug fix for ga_squad tuner

* fix same hash_id bug

* add lock to simple tuner in weight sharing

* Add readme to simple weight sharing

* update

* update

* add paper link

* update

* reformat with autopep8

* add documentation for weight sharing

* test for weight sharing

* delete irrelevant files

* move details of weight sharing in to code comments

* add example section

* update weight sharing tutorial

* fix divide by zero risk

* update tuner thread exception handling

* fix bug for async test

* Add frameworkcontroller document (#530)

Add frameworkcontroller document.
Fix other document small issues.

* [WebUI] Show trial log for pai and k8s (#580)

* [WebUI] Show trial log for pai and k8s

* fix lint

* Fix comments

* [WebUI] Show trial log for pai and k8s (#580)

* [WebUI] Show trial log for pai and k8s

* fix lint

* Fix comments

* add __init__.py to metis_tuner (#588)

* add docs

* [Document] Update webui doc (#587)

* Update webui document

* update

* Update Dockerfile and README (#589)

* fix some bugs in doc and log

* The learning rate focus more on validation sets accuracy than training sets accuracy.

* update Dockerfile and README

* Update README.md

Merge to branch v0.5

* [WebUI] Fix bug (#591)

* fix bug

* fix bug of background

* update

* update

* add frameworkcontroller platform

* update README in metis and update RuntimeError info (#595)

* update README in metis and update RuntimeError

* fix typo

* add numerical choice check

* update

* udpate NFS setup tutorial (#597)

* Remove unused example (#600)

* update README in metis and update RuntimeError

* remove smart params

* Update release note …

* Add sklearn_example.md (#647)

* fix doc

* add link in doc

* update

* add nnictl package cmd

* add sklearn-example.md

* update

* update

* fix link

* add desc in example.rst

* revert nnictl before sphinx try

* fix mnist.py example

* add SQuAD_evolution_examples.md (#620)

* add SQuAD_evolution_examples.md

* add update

* remove yml file

* remove mkdoc.yml

* update Example.rst

* Add GBDT example doc (#654)

* add SQuAD_evolution_examples.md

* add update

* remove yml file

* remove mkdoc.yml

* update Example.rst

* update gbdt_example.md

* update

* add run command line

* update Evlution_SQuAD.md

* update link

* add gbdt in Example.rst

* Update SearchSpaceSpec (#656)

* add Trials.md

* add Trials.md

* add Trials.md

* add Trials.md

* add docs

* add docs

* add docs

* add docs

* add docs

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* docs modification

* update triaL.MD

* update triaL.MD

* update triaL.MD

* update triaL.MD

* update triaL.MD

* add grid search tuner doc

* add grid search tuner doc

* update SearchSpaceSpec

* update SearchSpaceSpec

* update SearchSpaceSpec

* update SearchSpaceSpec

* update SearchSpaceSpec

* update SearchSpaceSpec

* update SearchSpaceSpec

* update SearchSpaceSpec

* update SearchSpaceSpec

* fix color for zejun

* fix mnist before

* fix image

* Fix doc format (#658)

* add SQuAD_evolution_examples.md

* add update

* remove yml file

* fix format problem

* update index

* fix typo

* fix broken-links of quickstart/tuners/assessors (#662)

* update assessor.rst

* fix

* Dev doc fix4 (#672)

* refactor index

* fix title format for remote

* fix nnictl doc w/ rst

* fix assessor pic link

* fix type for training service

* adjust tutorial

* fix typo

* Dev doc (#669)

* changed image link

* deleted link of triallog.png

new version do not has this function

* Update AdvancedNAS.md

* changed image link

weight sharing image

* update doc (#670)

* update doc

* Dev doc fix4 (#672)

* refactor index

* fix title format for remote

* fix nnictl doc w/ rst

* fix assessor pic link

* fix type for training service

* adjust tutorial

* fix typo

* Update customized assessor doc (#671)

* Update customized assessor doc

* updates

* fix typo

* update doc (#673)

docs/README.md

+# Overview
+
+<p align="center">
+<img src="https://raw.githubusercontent.com/Microsoft/nni/master/docs/img/nni_logo.png" alt="drawing" width="300"/>
+</p>
+
+-----------
+
+[![](https://img.shields.io/badge/license-MIT-yellow.svg)](https://github.com/Microsoft/nni/blob/master/LICENSE)
+[![](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/Microsoft.nni)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=6)
+[![](https://img.shields.io/github/issues-raw/Microsoft/nni.svg)](https://github.com/Microsoft/nni/issues?q=is%3Aissue+is%3Aopen)
+[![](https://img.shields.io/github/issues/Microsoft/nni/bug.svg)](https://github.com/Microsoft/nni/issues?q=is%3Aissue+is%3Aopen+label%3Abug)
+[![](https://img.shields.io/github/issues-pr-raw/Microsoft/nni.svg)](https://github.com/Microsoft/nni/pulls?q=is%3Apr+is%3Aopen)
+[![](https://img.shields.io/github/release/Microsoft/nni.svg)](https://github.com/Microsoft/nni/releases) 
+[![](https://badges.gitter.im/Microsoft/nni.svg)](https://gitter.im/Microsoft/nni?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
+
+NNI (Neural Network Intelligence) is a toolkit to help users run automated machine learning (AutoML) experiments. 
+The tool dispatches and runs trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different environments like local machine, remote servers and cloud.
+
+
+![](img/nni_arch_overview.png)
+
+## **Who should consider using NNI**
+* Those who want to try different AutoML algorithms in their training code (model) at their local machine.
+* Those who want to run AutoML trial jobs in different environments to speed up search (e.g. remote servers and cloud).
+* Researchers and data scientists who want to implement their own AutoML algorithms and compare it with other algorithms.
+* ML Platform owners who want to support AutoML in their platform.
+
+## **Install & Verify**
+
+**Install through pip** 	
+* We support Linux and MacOS in current stage, Ubuntu 16.04 or higher, along with MacOS 10.14.1 are tested and supported. Simply run the following `pip install` in an environment that has `python >= 3.5`.	
+```bash	
+    python3 -m pip install --user --upgrade nni
+```
+* Note:
+  * If you are in docker container (as root), please remove `--user` from the installation command.
+  * If there is any error like `Segmentation fault`, please refer to [FAQ](FAQ.md)
+
+**Install through source code**
+* We support Linux (Ubuntu 16.04 or higher), MacOS (10.14.1) in our current stage. 
+* Run the following commands in an environment that has `python >= 3.5`, `git` and `wget`.
+```bash	
+    git clone -b v0.4.1 https://github.com/Microsoft/nni.git
+    cd nni	
+    source install.sh	
+```
+
+For the system requirements of NNI, please refer to [Install NNI](Installation.md)
+
+**Verify install**	
+
+The following example is an experiment built on TensorFlow. Make sure you have **TensorFlow installed** before running it.	
+* Download the examples via clone the source code.	
+```bash	
+    git clone -b v0.4.1 https://github.com/Microsoft/nni.git
+```
+* Run the mnist example.
+```bash
+    nnictl create --config nni/examples/trials/mnist/config.yml
+```
+
+* Wait for the message `INFO: Successfully started experiment!` in the command line. This message indicates that your experiment has been successfully started. You can explore the experiment using the `Web UI url`.
+```
+INFO: Starting restful server...
+INFO: Successfully started Restful server!
+INFO: Setting local config...
+INFO: Successfully set local config!
+INFO: Starting experiment...
+INFO: Successfully started experiment!
+-----------------------------------------------------------------------
+The experiment id is egchD4qy
+The Web UI urls are: http://223.255.255.1:8080   http://127.0.0.1:8080
+-----------------------------------------------------------------------
+
+You can use these commands to get more information about the experiment
+-----------------------------------------------------------------------
+         commands                       description
+1. nnictl experiment show        show the information of experiments
+2. nnictl trial ls               list all of trial jobs
+3. nnictl log stderr             show stderr log content
+4. nnictl log stdout             show stdout log content
+5. nnictl stop                   stop an experiment
+6. nnictl trial kill             kill a trial job by id
+7. nnictl --help                 get help information about nnictl
+-----------------------------------------------------------------------
+```
+
+* Open the `Web UI url` in your browser, you can view detail information of the experiment and all the submitted trial jobs as shown below. [Here](WebUI.md) are more Web UI pages.
+
+
+<table style="border: none">
+    <th><img src="https://raw.githubusercontent.com/Microsoft/nni/dev-doc/docs/img/webui_overview_page.png" alt="drawing" width="395"/></th>
+    <th><img src="https://raw.githubusercontent.com/Microsoft/nni/dev-doc/docs/img/webui_trialdetail_page.png" alt="drawing" width="410"/></th>
+</table>
+
+
+## **Documentation**
+* [NNI overview](Overview.md)
+* [Quick start](GetStarted.md)
+
+## **How to**
+* [Install NNI](Installation.md)
+* [Use command line tool nnictl](NNICTLDOC.md)
+* [Use NNIBoard](WebUI.md)
+* [How to define search space](SearchSpaceSpec.md)
+* [How to define a trial](howto_1_WriteTrial.md)
+* [Config an experiment](ExperimentConfig.md)
+* [How to use annotation](howto_1_WriteTrial.md#nni-python-annotation)
+## **Tutorials**
+* [Run an experiment on local (with multiple GPUs)?](tutorial_1_CR_exp_local_api.md)
+* [Run an experiment on multiple machines?](tutorial_2_RemoteMachineMode.md)
+* [Run an experiment on OpenPAI?](PAIMode.md)
+* [Run an experiment on Kubeflow?](KubeflowMode.md)
+* [Try different tuners and assessors](tutorial_3_tryTunersAndAssessors.md)
+* [Implement a customized tuner](howto_2_CustomizedTuner.md)
+* [Implement a customized assessor](../examples/assessors/README.md)
+* [Use Genetic Algorithm to find good model architectures for Reading Comprehension task](../examples/trials/ga_squad/README.md)
+
+## **Contribute**
+This project welcomes contributions and suggestions, we use [GitHub issues](https://github.com/Microsoft/nni/issues) for tracking requests and bugs.
+
+Issues with the **good first issue** label are simple and easy-to-start ones that we recommend new contributors to start with.
+
+To set up environment for NNI development, refer to the instruction: [Set up NNI developer environment](SetupNNIDeveloperEnvironment.md)
+
+Before start coding, review and get familiar with the NNI Code Contribution Guideline: [Contributing](CONTRIBUTING.md)
+
+We are in construction of the instruction for [How to Debug](HowToDebug.md), you are also welcome to contribute questions or suggestions on this area.
+
+## **License** 
+The entire codebase is under [MIT license](https://github.com/Microsoft/nni/blob/master/LICENSE)
+

docs/RELEASE.md

-# Release 0.5.0 - 01/14/2019
-## Major Features
-### New tuner and assessor supports
+# ChangeLog
+
+## Release 0.5.0 - 01/14/2019
+### Major Features
+#### New tuner and assessor supports
   * Support [Metis tuner](./HowToChooseTuner.md#MetisTuner) as a new NNI tuner. Metis algorithm has been proofed to be well performed for **online** hyper-parameter tuning.
   * Support [ENAS customized tuner](https://github.com/countif/enas_nni), a tuner contributed by github community user, is an algorithm for neural network search, it could learn neural network architecture via reinforcement learning and serve a better performance than NAS.
   * Support [Curve fitting assessor](./HowToChooseTuner.md#Curvefitting) for early stop policy using learning curve extrapolation. 
   * Advanced Support of [Weight Sharing](./AdvancedNAS.md): Enable weight sharing for NAS tuners, currently through NFS.
 
 
-### Training Service Enhancement
+#### Training Service Enhancement
 * [FrameworkController Training service](./FrameworkControllerMode.md): Support run experiments using frameworkcontroller on kubernetes
    * FrameworkController is a Controller on kubernetes that is general enough to run (distributed) jobs with various machine learning frameworks, such as tensorflow, pytorch, MXNet.
    * NNI provides unified and simple specification for job definition.
    * MNIST example for how to use FrameworkController.
 
-### User Experience improvements
+#### User Experience improvements
   * A better trial logging support for NNI experiments in PAI, Kubeflow and FrameworkController mode:
       * An improved logging architecture to send stdout/stderr of trials to NNI manager via Http post. NNI manager will store trial's stdout/stderr messages in local log file.
       * Show the link for trial log file on WebUI. 
   * Support to show final result's all key-value pairs.
 
-# Release 0.4.1 - 12/14/2018
-## Major Features
-### New tuner supports
+## Release 0.4.1 - 12/14/2018
+### Major Features
+#### New tuner supports
   * Support [network morphism](./HowToChooseTuner.md#NetworkMorphism) as a new tuner
 
-### Training Service improvements
+#### Training Service improvements
   * Migrate [Kubeflow training service](https://github.com/Microsoft/nni/blob/master/docs/KubeflowMode.md)'s dependency from kubectl CLI to [Kubernetes API](https://kubernetes.io/docs/concepts/overview/kubernetes-api/) client
   * [Pytorch-operator](https://github.com/kubeflow/pytorch-operator) support for Kubeflow training service
   * Improvement on local code files uploading to OpenPAI HDFS
   * Fixed OpenPAI integration WebUI bug: WebUI doesn't show latest trial job status, which is caused by OpenPAI token expiration
 
-### NNICTL improvements
+#### NNICTL improvements
   * Show version information both in nnictl and WebUI. You can run **nnictl -v** to show your current installed NNI version
 
-### WebUI improvements
+#### WebUI improvements
   * Enable modify concurrency number during experiment
   * Add feedback link to NNI github 'create issue' page
   * Enable customize top 10 trials regarding to metric numbers (largest or smallest)
@@ -41,14 +43,14 @@
   * Enable automatic scaling of axes for metric number
   * Update annotation to support displaying real choice in searchspace
 
-## New examples
+### New examples
   * [FashionMnist](https://github.com/Microsoft/nni/tree/master/examples/trials/network_morphism), work together with network morphism tuner
   * [Distributed MNIST example](https://github.com/Microsoft/nni/tree/master/examples/trials/mnist-distributed-pytorch) written in PyTorch
   
   
-# Release 0.4 - 12/6/2018
+## Release 0.4 - 12/6/2018
 
-## Major Features
+### Major Features
   * [Kubeflow Training service](./KubeflowMode.md)
     * Support tf-operator
     * [Distributed trial example](../examples/trials/mnist-distributed/dist_mnist.py) on Kubeflow
@@ -63,7 +65,7 @@
     *  Support search a specific trial by trial number
     *  Show trial's hdfsLogPath
     *  Download experiment parameters
-## Others
+### Others
   * Asynchronous dispatcher
   * Docker file update, add pytorch library 
   * Refactor 'nnictl stop' process, send SIGTERM to nni manager process, rather than calling stop Rest API. 
@@ -73,8 +75,8 @@
     *  Don’t print useless ‘metrics is empty’ log int PAI job’s stdout. Only print useful message once new metrics are recorded, to reduce confusion when user checks PAI trial’s output for debugging purpose
     *  Add timestamp at the beginning of each log entry in trial keeper.
 
-# Release 0.3.0 - 11/2/2018
-## NNICTL new features and updates
+## Release 0.3.0 - 11/2/2018
+### NNICTL new features and updates
 * Support running multiple experiments simultaneously. 
 
     Before v0.3, NNI only supports running single experiment once a time. After this realse, users are able to run multiple experiments simultaneously. Each experiment will require a unique port, the 1st experiment will be set to the default port as previous versions. You can specify a unique port for the rest experiments as below:
@@ -83,7 +85,7 @@
 * Support updating max trial number.
     use ```nnictl update --help``` to learn more. Or refer to [NNICTL Spec](https://github.com/Microsoft/nni/blob/master/docs/NNICTLDOC.md) for the fully usage of NNICTL.
 
-## API new features and updates
+### API new features and updates
 * <span style="color:red">**breaking change**</span>: nn.get_parameters() is refactored to nni.get_next_parameter. All examples of prior releases can not run on v0.3, please clone nni repo to get new examples. If you had applied NNI to your own codes, please update the API accordingly.
 
 * New API **nni.get_sequence_id()**. 
@@ -96,23 +98,23 @@
     * float
     * A python dict containing 'default' key, the value of 'default' key should be of type int or float. The dict can contain any other key value pairs.
 
-## New tuner support
+### New tuner support
 * **Batch Tuner** which iterates all parameter combination, can be used to submit batch trial jobs.
 
-## New examples
+### New examples
 * A NNI Docker image for public usage:
       ```docker pull msranni/nni:latest```
 * New trial example: [NNI Sklearn Example](https://github.com/Microsoft/nni/tree/master/examples/trials/sklearn)
 * New competition example: [Kaggle Competition TGS Salt Example](https://github.com/Microsoft/nni/tree/master/examples/trials/kaggle-tgs-salt)
     
-## Others
+### Others
 * UI refactoring, refer to [WebUI doc](WebUI.md) for how to work with the new UI.
 * Continuous Integration: NNI had switched to Azure pipelines
 * [Known Issues in release 0.3.0](https://github.com/Microsoft/nni/labels/nni030knownissues).
 
 
-# Release 0.2.0 - 9/29/2018
-## Major Features
+## Release 0.2.0 - 9/29/2018
+### Major Features
    * Support [OpenPAI](https://github.com/Microsoft/pai) (aka pai) Training Service (See [here](./PAIMode.md) for instructions about how to submit NNI job in pai mode)
       * Support training services on pai mode. NNI trials will be scheduled to run on OpenPAI cluster
       * NNI trial's output (including logs and model file) will be copied to OpenPAI HDFS for further debugging and checking
@@ -123,14 +125,14 @@
       * Update ga squad example and related documentation
       * WebUI UX small enhancement and bug fix
 
-## Known Issues
+### Known Issues
 [Known Issues in release 0.2.0](https://github.com/Microsoft/nni/labels/nni020knownissues).
 
-# Release 0.1.0 - 9/10/2018 (initial release)
+## Release 0.1.0 - 9/10/2018 (initial release)
 
 Initial release of Neural Network Intelligence (NNI).
 
-## Major Features
+### Major Features
    * Installation and Deployment
       * Support pip install and source codes install
       * Support training services on local mode(including Multi-GPU mode) as well as multi-machines mode
@@ -147,5 +149,5 @@ Initial release of Neural Network Intelligence (NNI).
    * Others
       * Support simple GPU job scheduling 
 
-## Known Issues
+### Known Issues
 [Known Issues in release 0.1.0](https://github.com/Microsoft/nni/labels/nni010knownissues).

docs/Reference.rst

+References
+==================
+
+..  toctree::
+    :maxdepth: 3
+    
+    Command Line <NNICTL>
+    Python API <sdk_reference>
+    Annotation <AnnotationSpec>
+    Configuration<ExperimentConfig>
+    Search Space <SearchSpaceSpec>
\ No newline at end of file

docs/RemoteMachineMode.md

-**Run an Experiment on Multiple Machines**
-
-===
+# Run an Experiment on Multiple Machines
 
 NNI supports running an experiment on multiple machines through SSH channel, called `remote` mode. NNI assumes that you have access to those machines, and already setup the environment for running deep learning training code.
 
@@ -16,14 +14,6 @@ e.g. Three machines and you login in with account `bob` (Note: the account is no
 
 Install NNI on each of your machines following the install guide [here](GetStarted.md).
 
-For remote machines that are used only to run trials but not the nnictl, you can just install python SDK:
-
-* __Install python SDK through pip__
-
-  ```bash
-  python3 -m pip install --user --upgrade nni-sdk
-  ```
-
 ## Run an experiment
 
 Install NNI on another machine which has network accessibility to those three machines above, or you can just use any machine above to run nnictl command line tool.

docs/SQuAD_evolution_examples.md

+# Automatic Model Architecture Search for Reading Comprehension
+This example shows us how to use Genetic Algorithm to find good model architectures for Reading Comprehension.
+
+## 1. Search Space
+Since attention and recurrent neural network (RNN) have been proven effective in Reading Comprehension.
+We conclude the search space as follow:
+
+1. IDENTITY (Effectively means keep training).
+2. INSERT-RNN-LAYER (Inserts a LSTM. Comparing the performance of GRU and LSTM in our experiment, we decided to use LSTM here.)
+3. REMOVE-RNN-LAYER
+4. INSERT-ATTENTION-LAYER(Inserts an attention layer.)
+5. REMOVE-ATTENTION-LAYER
+6. ADD-SKIP (Identity between random layers).
+7. REMOVE-SKIP (Removes random skip).
+
+![](../examples/trials/ga_squad/ga_squad.png)
+
+### New version
+Also we have another version which time cost is less and performance is better. We will release soon.
+
+## 2. How to run this example in local?
+
+### 2.1 Use downloading script to download data
+
+Execute the following command to download needed files
+using the downloading script:
+
+```
+chmod +x ./download.sh
+./download.sh
+```
+
+Or Download manually
+
+1. download "dev-v1.1.json" and "train-v1.1.json" in https://rajpurkar.github.io/SQuAD-explorer/
+
+```
+wget https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json
+wget https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v1.1.json
+```
+
+2. download "glove.840B.300d.txt" in https://nlp.stanford.edu/projects/glove/
+
+```
+wget http://nlp.stanford.edu/data/glove.840B.300d.zip
+unzip glove.840B.300d.zip
+```
+
+### 2.2 Update configuration
+Modify `nni/examples/trials/ga_squad/config.yml`, here is the default configuration:
+
+```
+authorName: default
+experimentName: example_ga_squad
+trialConcurrency: 1
+maxExecDuration: 1h
+maxTrialNum: 1
+#choice: local, remote
+trainingServicePlatform: local
+#choice: true, false
+useAnnotation: false
+tuner:
+  codeDir: ~/nni/examples/tuners/ga_customer_tuner
+  classFileName: customer_tuner.py
+  className: CustomerTuner
+  classArgs:
+    optimize_mode: maximize
+trial:
+  command: python3 trial.py
+  codeDir: ~/nni/examples/trials/ga_squad
+  gpuNum: 0
+```
+
+In the "trial" part, if you want to use GPU to perform the architecture search, change `gpuNum` from `0` to `1`. You need to increase the `maxTrialNum` and `maxExecDuration`, according to how long you want to wait for the search result.
+
+### 2.3 submit this job
+
+```
+nnictl create --config ~/nni/examples/trials/ga_squad/config.yml
+```
+
+## 3 Run this example on OpenPAI
+
+Due to the memory limitation of upload, we only upload the source code and complete the data download and training on OpenPAI. This experiment requires sufficient memory that `memoryMB >= 32G`, and the training may last for several hours.
+
+### 3.1 Update configuration
+Modify `nni/examples/trials/ga_squad/config_pai.yaml`, here is the default configuration:
+
+```
+authorName: default
+experimentName: example_ga_squad
+trialConcurrency: 1
+maxExecDuration: 1h
+maxTrialNum: 10
+#choice: local, remote, pai
+trainingServicePlatform: pai
+#choice: true, false
+useAnnotation: false
+#Your nni_manager ip
+nniManagerIp: 10.10.10.10
+tuner:
+  codeDir: ../../tuners/ga_customer_tuner
+  classFileName: customer_tuner.py
+  className: CustomerTuner
+  classArgs:
+    optimize_mode: maximize
+trial:
+  command: chmod +x ./download.sh && ./download.sh && python3 trial.py
+  codeDir: .
+  gpuNum: 0
+  cpuNum: 1
+  memoryMB: 32869
+  #The docker image to run nni job on pai
+  image: msranni/nni:latest
+  #The hdfs directory to store data on pai, format 'hdfs://host:port/directory'
+  dataDir: hdfs://10.10.10.10:9000/username/nni
+  #The hdfs directory to store output data generated by nni, format 'hdfs://host:port/directory'
+  outputDir: hdfs://10.10.10.10:9000/username/nni
+paiConfig:
+  #The username to login pai
+  userName: username
+  #The password to login pai
+  passWord: password
+  #The host of restful server of pai
+  host: 10.10.10.10
+```
+
+Please change the default value to your personal account and machine information. Including `nniManagerIp`, `dataDir`, `outputDir`, `userName`, `passWord` and `host`.
+
+In the "trial" part, if you want to use GPU to perform the architecture search, change `gpuNum` from `0` to `1`. You need to increase the `maxTrialNum` and `maxExecDuration`, according to how long you want to wait for the search result.
+
+`trialConcurrency` is the number of trials running concurrently, which is the number of GPUs you want to use, if you are setting `gpuNum` to 1.
+
+### 3.2 submit this job
+
+```
+nnictl create --config ~/nni/examples/trials/ga_squad/config_pai.yml
+```
+
+## 4. Technical details about the trial
+
+### 4.1 How does it works
+The evolution-algorithm based architecture for question answering has two different parts just like any other examples: the trial and the tuner.
+
+### 4.2 The trial
+
+The trial has a lot of different files, functions and classes. Here we will only give most of those files a brief introduction:
+
+* `attention.py` contains an implementation for attention mechanism in Tensorflow.
+* `data.py` contains functions for data preprocessing.
+* `evaluate.py` contains the evaluation script.
+* `graph.py` contains the definition of the computation graph.
+* `rnn.py` contains an implementation for GRU in Tensorflow.
+* `train_model.py` is a wrapper for the whole question answering model.
+
+Among those files, `trial.py` and `graph_to_tf.py` are special.
+
+`graph_to_tf.py` has a function named as `graph_to_network`, here is its skeleton code:
+
+```
+def graph_to_network(input1,
+                     input2,
+                     input1_lengths,
+                     input2_lengths,
+                     graph,
+                     dropout_rate,
+                     is_training,
+                     num_heads=1,
+                     rnn_units=256):
+    topology = graph.is_topology()
+    layers = dict()
+    layers_sequence_lengths = dict()
+    num_units = input1.get_shape().as_list()[-1]
+    layers[0] = input1*tf.sqrt(tf.cast(num_units, tf.float32)) + \
+        positional_encoding(input1, scale=False, zero_pad=False)
+    layers[1] = input2*tf.sqrt(tf.cast(num_units, tf.float32))
+    layers[0] = dropout(layers[0], dropout_rate, is_training)
+    layers[1] = dropout(layers[1], dropout_rate, is_training)
+    layers_sequence_lengths[0] = input1_lengths
+    layers_sequence_lengths[1] = input2_lengths
+    for _, topo_i in enumerate(topology):
+        if topo_i == '|':
+            continue
+        if graph.layers[topo_i].graph_type == LayerType.input.value:
+            # ......
+        elif graph.layers[topo_i].graph_type == LayerType.attention.value:
+            # ......
+        # More layers to handle
+```
+
+As we can see, this function is actually a compiler, that converts the internal model DAG configuration (which will be introduced in the `Model configuration format` section) `graph`, to a Tensorflow computation graph.
+
+```
+topology = graph.is_topology()
+```
+
+performs topological sorting on the internal graph representation, and the code inside the loop:
+
+```
+for _, topo_i in enumerate(topology):
+```
+
+performs actually conversion that maps each layer to a part in Tensorflow computation graph.
+
+### 4.3 The tuner
+
+The tuner is much more simple than the trial. They actually share the same `graph.py`. Besides, the tuner has a `customer_tuner.py`, the most important class in which is `CustomerTuner`:
+
+```
+class CustomerTuner(Tuner):
+    # ......
+
+    def generate_parameters(self, parameter_id):
+        """Returns a set of trial graph config, as a serializable object.
+        parameter_id : int
+        """
+        if len(self.population) <= 0:
+            logger.debug("the len of poplution lower than zero.")
+            raise Exception('The population is empty')
+        pos = -1
+        for i in range(len(self.population)):
+            if self.population[i].result == None:
+                pos = i
+                break
+        if pos != -1:
+            indiv = copy.deepcopy(self.population[pos])
+            self.population.pop(pos)
+            temp = json.loads(graph_dumps(indiv.config))
+        else:
+            random.shuffle(self.population)
+            if self.population[0].result > self.population[1].result:
+                self.population[0] = self.population[1]
+            indiv = copy.deepcopy(self.population[0])
+            self.population.pop(1)
+            indiv.mutation()
+            graph = indiv.config
+            temp =  json.loads(graph_dumps(graph))
+    
+    # ......
+```
+
+As we can see, the overloaded method `generate_parameters` implements a pretty naive mutation algorithm. The code lines:
+
+```
+            if self.population[0].result > self.population[1].result:
+                self.population[0] = self.population[1]
+            indiv = copy.deepcopy(self.population[0])
+```
+
+controls the mutation process. It will always take two random individuals in the population, only keeping and mutating the one with better result.
+
+### 4.4 Model configuration format
+
+Here is an example of the model configuration, which is passed from the tuner to the trial in the architecture search procedure.
+
+```
+{
+    "max_layer_num": 50,
+    "layers": [
+        {
+            "input_size": 0,
+            "type": 3,
+            "output_size": 1,
+            "input": [],
+            "size": "x",
+            "output": [4, 5],
+            "is_delete": false
+        },
+        {
+            "input_size": 0,
+            "type": 3,
+            "output_size": 1,
+            "input": [],
+            "size": "y",
+            "output": [4, 5],
+            "is_delete": false
+        },
+        {
+            "input_size": 1,
+            "type": 4,
+            "output_size": 0,
+            "input": [6],
+            "size": "x",
+            "output": [],
+            "is_delete": false
+        },
+        {
+            "input_size": 1,
+            "type": 4,
+            "output_size": 0,
+            "input": [5],
+            "size": "y",
+            "output": [],
+            "is_delete": false
+        },
+        {"Comment": "More layers will be here for actual graphs."}
+    ]
+}
+```
+
+Every model configuration will have a "layers" section, which is a JSON list of layer definitions. The definition of each layer is also a JSON object, where:
+
+ * `type` is the type of the layer. 0, 1, 2, 3, 4 corresponds to attention, self-attention, RNN, input and output layer respectively.
+ * `size` is the length of the output. "x", "y" correspond to document length / question length, respectively.
+ * `input_size` is the number of inputs the layer has.
+ * `input` is the indices of layers taken as input of this layer.
+ * `output` is the indices of layers use this layer's output as their input.
+ * `is_delete` means whether the layer is still available.

docs/SearchSpaceSpec.md

-## How to define search space?
+# Search Space
 
-### Hyper-parameter Search Space
+## Overview
 
-* A search space configure example as follow:
+In NNI, tuner will sample parameters/architecture according to the search space, which is defined as a json file.
+
+To define a search space, users should define the name of variable, the type of sampling strategy and its parameters.
+
+* A example of search space definition as follow:
 
 ```python
 {
@@ -15,11 +19,12 @@
 
 ```
 
-The example define `dropout_rate` as variable which priori distribution is uniform distribution, and its value from `0.1` and `0.5`.
-The tuner will sample parameters/architecture by understanding the search space first.
 
-User should define the name of variable, type and candidate value of variable.
-The candidate type and value for variable is here:
+Take the first line as an example. ```dropout_rate``` is defined as a variable whose priori distribution is a uniform distribution of a range from ```0.1``` and ```0.5```.
+
+## Types
+
+All types of sampling strategies and their parameter are listed here:
 
 * {"_type":"choice","_value":options}
    * Which means the variable value is one of the options, which should be a list. The elements of options can themselves be [nested] stochastic expressions. In this case, the stochastic choices that only appear in some of the options become conditional parameters.
@@ -67,8 +72,24 @@ The candidate type and value for variable is here:
    * Suitable for a discrete variable with respect to which the objective is smooth and gets smoother with the size of the variable, which is bounded from one side.
 <br/>
 
-Note that SMAC only supports a subset of the types above, including `choice`, `randint`, `uniform`, `loguniform`, `quniform(q=1)`. In the current version, SMAC does not support cascaded search space (i.e., conditional variable in SMAC).
 
-Note that GridSearch Tuner only supports a subset of the types above, including `choice`, `quniform` and `qloguniform`, where q here specifies the number of values that will be sampled. Details about the last two type as follows
+## Search Space Types Supported by Each Tuner
+
+|                   | choice  | randint | uniform | quniform | loguniform | qloguniform | normal  | qnormal | lognormal | qlognormal |
+|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|
+| TPE Tuner         | &#10003; | &#10003; | &#10003; | &#10003;  | &#10003;    | &#10003;     | &#10003; | &#10003; | &#10003;   | &#10003;    |
+| Random Search Tuner| &#10003; | &#10003; | &#10003; | &#10003;  | &#10003;    | &#10003;     | &#10003; | &#10003; | &#10003;   | &#10003;    |
+| Anneal Tuner   | &#10003; | &#10003; | &#10003; | &#10003;  | &#10003;    | &#10003;     | &#10003; | &#10003; | &#10003;   | &#10003;    |
+| Evolution Tuner   | &#10003; | &#10003; | &#10003; | &#10003;  | &#10003;    | &#10003;     | &#10003; | &#10003; | &#10003;   | &#10003;    |
+| SMAC Tuner        | &#10003; | &#10003; | &#10003; | &#10003;  | &#10003;    |      |  |  |    |     |
+| Batch Tuner       | &#10003; |  |  |   |     |      |  |  |    |     |
+| Grid Search Tuner | &#10003; |  |  | &#10003;  |     | &#10003;     |  |  |    |     |
+| Hyperband Advisor | &#10003; | &#10003; | &#10003; | &#10003;  | &#10003;    | &#10003;     | &#10003; | &#10003; | &#10003;   | &#10003;    |
+| Metis Tuner   | &#10003; | &#10003; | &#10003; | &#10003;  |     |      |  |  |    |     |
+
+Note that In GridSearch Tuner, for users' convenience, the definition of `quniform` and `qloguniform` change, where q here specifies the number of values that will be sampled. Details about them are listed as follows
+
 * Type 'quniform' will receive three values [low, high, q], where [low, high] specifies a range and 'q' specifies the number of values that will be sampled evenly. Note that q should be at least 2. It will be sampled in a way that the first sampled value is 'low', and each of the following values is (high-low)/q larger that the value in front of it.
 * Type 'qloguniform' behaves like 'quniform' except that it will first change the range to [log(low), log(high)] and sample and then change the sampled value back.
+
+Note that Metis Tuner only support numerical `choice` now

docs/Trials.md

+# Write a Trial Run on NNI
+
+A **Trial** in NNI is an individual attempt at applying a configuration (e.g., a set of hyper-parameters) on a model.
+
+To define an NNI trial, you need to firstly define the set of parameters (i.e., search space) and then update the model. NNI provide two approaches for you to define a trial: [NNI API](#nni-api) and [NNI Python annotation](#nni-annotation). You could also refer to [here](#more-examples) for more trial examples.
+
+<a name="nni-api"></a>
+## NNI API
+
+### Step 1 - Prepare a SearchSpace parameters file. 
+
+An example is shown below:
+
+```json
+{
+    "dropout_rate":{"_type":"uniform","_value":[0.1,0.5]},
+    "conv_size":{"_type":"choice","_value":[2,3,5,7]},
+    "hidden_size":{"_type":"choice","_value":[124, 512, 1024]},
+    "learning_rate":{"_type":"uniform","_value":[0.0001, 0.1]}
+}
+```
+
+Refer to [SearchSpaceSpec.md](./SearchSpaceSpec.md) to learn more about search space. Tuner will generate configurations from this search space, that is, choosing a value for each hyperparameter from the range.
+
+### Step 2 - Update model codes
+
+- Import NNI
+
+    Include `import nni` in your trial code to use NNI APIs. 
+
+- Get configuration from Tuner
+    
+```json 
+RECEIVED_PARAMS = nni.get_next_parameter()
+```
+`RECEIVED_PARAMS` is an object, for example: 
+`{"conv_size": 2, "hidden_size": 124, "learning_rate": 0.0307, "dropout_rate": 0.2029}`.
+
+- Report metric data periodically (optional)
+
+```json
+nni.report_intermediate_result(metrics)
+```
+`metrics` could be any python object. If users use NNI built-in tuner/assessor, `metrics` can only have two formats: 1) a number e.g., float, int, 2) a dict object that has a key named `default` whose value is a number. This `metrics` is reported to [assessor](Builtin_Assessors.md). Usually, `metrics` could be periodically evaluated loss or accuracy.
+
+- Report performance of the configuration
+
+```json
+nni.report_final_result(metrics)
+```
+`metrics` also could be any python object. If users use NNI built-in tuner/assessor, `metrics` follows the same format rule as that in `report_intermediate_result`, the number indicates the model's performance, for example, the model's accuracy, loss etc. This `metrics` is reported to [tuner](Builtin-Tuner.md).
+
+### Step 3 - Enable NNI API
+
+To enable NNI API mode, you need to set useAnnotation to *false* and provide the path of SearchSpace file (you just defined in step 1):
+
+```json
+useAnnotation: false
+searchSpacePath: /path/to/your/search_space.json
+```
+
+You can refer to [here](ExperimentConfig.md) for more information about how to set up experiment configurations.
+
+*Please refer to [here]() for more APIs (e.g., `nni.get_sequence_id()`) provided by NNI.
+
+
+<a name="nni-annotation"></a>
+## NNI Python Annotation
+
+An alternative to writing a trial is to use NNI's syntax for python. Simple as any annotation, NNI annotation is working like comments in your codes. You don't have to make structure or any other big changes to your existing codes. With a few lines of NNI annotation, you will be able to:
+
+* annotate the variables you want to tune 
+* specify in which range you want to tune the variables
+* annotate which variable you want to report as intermediate result to `assessor`
+* annotate which variable you want to report as the final result (e.g. model accuracy) to `tuner`. 
+
+Again, take MNIST as an example, it only requires 2 steps to write a trial with NNI Annotation.
+
+### Step 1 - Update codes with annotations 
+
+The following is a tensorflow code snippet for NNI Annotation, where the highlighted four lines are annotations that help you to: 
+  1. tune batch\_size and dropout\_rate
+  2. report test\_acc every 100 steps
+  3. at last report test\_acc as final result.
+
+What noteworthy is: as these newly added codes are annotations, it does not actually change your previous codes logic, you can still run your code as usual in environments without NNI installed.
+
+```diff
+with tf.Session() as sess:
+    sess.run(tf.global_variables_initializer())
++   """@nni.variable(nni.choice(50, 250, 500), name=batch_size)"""
+    batch_size = 128
+    for i in range(10000):
+        batch = mnist.train.next_batch(batch_size)
++       """@nni.variable(nni.choice(1, 5), name=dropout_rate)"""
+        dropout_rate = 0.5
+        mnist_network.train_step.run(feed_dict={mnist_network.images: batch[0],
+                                                mnist_network.labels: batch[1],
+                                                mnist_network.keep_prob: dropout_rate})
+        if i % 100 == 0:
+            test_acc = mnist_network.accuracy.eval(
+                feed_dict={mnist_network.images: mnist.test.images,
+                            mnist_network.labels: mnist.test.labels,
+                            mnist_network.keep_prob: 1.0})
++           """@nni.report_intermediate_result(test_acc)"""
+
+    test_acc = mnist_network.accuracy.eval(
+        feed_dict={mnist_network.images: mnist.test.images,
+                    mnist_network.labels: mnist.test.labels,
+                    mnist_network.keep_prob: 1.0})
++   """@nni.report_final_result(test_acc)"""
+```
+
+**NOTE**: 
+- `@nni.variable` will take effect on its following line, which is an assignment statement whose leftvalue must be specified by the keyword `name` in `@nni.variable`.
+- `@nni.report_intermediate_result`/`@nni.report_final_result` will send the data to assessor/tuner at that line. 
+
+For more information about annotation syntax and its usage, please refer to [Annotation README](../tools/nni_annotation/README.md) . 
+
+
+### Step 2 - Enable NNI Annotation
+
+In the yaml configure file, you need to set *useAnnotation* to true to enable NNI annotation:
+```
+useAnnotation: true
+```
+
+<a name="more-examples"></a>
+## More Trial Examples
+
+* [MNIST examples](mnist_examples.md)
+* [Finding out best optimizer for Cifar10 classification](cifar10_examples.md)
+* [How to tune Scikit-learn on NNI](sklearn_examples.md)
+* [Automatic Model Architecture Search for Reading Comprehension.](SQuAD_evolution_examples.md)
+* [Tuning GBDT on NNI](gbdt_example.md)

docs/Tutorials.rst

+######################
+Tutorials
+######################
+
+..  toctree::
+    Installation
+    Write Trial<Trials>
+    Tuners<tuners>
+    Assessors<assessors>
+    WebUI
+    Training Platform<training_services>
+    advanced
\ No newline at end of file

docs/WebUI.md

@@ -45,7 +45,6 @@ Click the tab "Trials Detail" to see the status of the all trials. Specifically:
 
 ![](./img/webui-img/detail-pai.png)
 
-![](./img/webui-img/trialog.png)
 
 * Kill: you can kill a job that status is running.
 * Support to search for a specific trial.

docs/advanced.rst

+Advanced Features 
+=====================
+
+..  toctree::
+    MultiPhase<multiPhase>
+    AdvancedNAS
\ No newline at end of file

docs/assessors.rst

+Assessors
+==============
+In order to save our computing resources, NNI supports an early stop policy and creates **Assessor** to finish this job.
+
+Assessor receives the intermediate result from Trial and decides whether the Trial should be killed by specific algorithm. Once the Trial experiment meets the early stop conditions(which means assessor is pessimistic about the final results), the assessor will kill the trial and the status of trial will be `"EARLY_STOPPED"`.
+
+Here is an experimental result of MNIST after using 'Curvefitting' Assessor in 'maximize' mode, you can see that assessor successfully **early stopped** many trials with bad hyperparameters in advance. If you use assessor, we may get better hyperparameters under the same computing resources.
+
+*Implemented code directory: config_assessor.yml <https://github.com/Microsoft/nni/blob/master/examples/trials/mnist/config_assessor.yml>*
+
+..  image:: ./img/Assessor.png
+
+Like Tuners, users can either use built-in Assessors, or customize an Assessor on their own. Please refer to the following tutorials for detail:
+
+..  toctree::
+    Builtin Assessors<Builtin_Assessors>
+    Customized Assessors<Customize_Assessor>

docs/cifar10_examples.md

+# CIFAR-10 examples
+
+## Overview
+
+[CIFAR-10][3] classification is a common benchmark problem in machine learning. The CIFAR-10 dataset is the collection of images. It is one of the most widely used datasets for machine learning research which contains 60,000 32x32 color images in 10 different classes. Thus, we use CIFAR-10 classification as an example to introduce NNI usage.
+
+### **Goals**
+
+As we all know, the choice of model optimizer is directly affects the performance of the final matrix. The goal of this tutorial is to **tune a better performace optimizer** to train a relatively small convolutional neural network (CNN) for recognizing images.
+
+In this example, we have selected the following common deep learning optimizer:
+
+> "SGD", "Adadelta", "Adagrad", "Adam", "Adamax"
+
+### **Experimental**
+
+#### Preparations
+
+This example requires pytorch. Pytorch install package should be chosen based on python version and cuda version.
+
+Here is an example of the environment python==3.5 and cuda == 8.0, then using the following commands to install [pytorch][2]:
+
+```bash
+python3 -m pip install http://download.pytorch.org/whl/cu80/torch-0.4.1-cp35-cp35m-linux_x86_64.whl
+python3 -m pip install torchvision
+```
+
+#### CIFAR-10 with NNI
+
+**Search Space**
+
+As we stated in the target, we target to find out the best `optimizer` for training CIFAR-10 classification. When using different optimizers, we also need to adjust `learning rates` and `network structure` accordingly. so we chose these three parameters as hyperparameters and write the following search space.
+
+```json
+{
+    "lr":{"_type":"choice", "_value":[0.1, 0.01, 0.001, 0.0001]},
+    "optimizer":{"_type":"choice", "_value":["SGD", "Adadelta", "Adagrad", "Adam", "Adamax"]},
+    "model":{"_type":"choice", "_value":["vgg", "resnet18", "googlenet", "densenet121", "mobilenet", "dpn92", "senet18"]}
+}
+```
+
+*Implemented code directory: [search_space.json][8]*
+
+**Trial**
+
+The code for CNN training of each hyperparameters set, paying particular attention to the following points are specific for NNI:
+
+* Use `nni.get_next_parameter()` to get next training hyperparameter set.
+* Use `nni.report_intermediate_result(acc)` to report the intermedian result after finish each epoch.
+* Use `nni.report_intermediate_result(acc)` to report the final result before the trial end.
+
+*Implemented code directory: [main.py][9]*
+
+You can also use your previous code directly, refer to [How to define a trial][5] for modify.
+
+**Config**
+
+Here is the example of running this experiment on local(with multiple GPUs):
+
+code directory: [examples/trials/cifar10_pytorch/config.yml][6]
+
+Here is the example of running this experiment on OpenPAI:
+
+code directory: [examples/trials/cifar10_pytorch/config_pai.yml][7]
+
+*The complete examples we have implemented: [examples/trials/cifar10_pytorch/][1]*
+
+#### Lauch the experiment
+
+We are ready for the experiment, let's now **run the config.yml file from your command line to start the experiment**.
+
+ ```bash
+    nnictl create --config nni/examples/trials/cifar10_pytorch/config.yml
+```
+
+[1]: https://github.com/Microsoft/nni/tree/master/examples/trials/cifar10_pytorch
+[2]: https://pytorch.org/
+[3]: https://www.cs.toronto.edu/~kriz/cifar.html
+[4]: https://github.com/Microsoft/nni/tree/master/examples/trials/cifar10_pytorch
+[5]: https://github.com/Microsoft/nni/blob/master/docs/howto_1_WriteTrial.md
+[6]: https://github.com/Microsoft/nni/blob/master/examples/trials/cifar10_pytorch/config.yml
+[7]: https://github.com/Microsoft/nni/blob/master/examples/trials/cifar10_pytorch/config_pai.yml
+[8]: https://github.com/Microsoft/nni/blob/master/examples/trials/cifar10_pytorch/search_space.json
+[9]: https://github.com/Microsoft/nni/blob/master/examples/trials/cifar10_pytorch/main.py
\ No newline at end of file

docs/conf.py

+# -*- coding: utf-8 -*-
+#
+# Configuration file for the Sphinx documentation builder.
+#
+# This file does only contain a selection of the most common options. For a
+# full list see the documentation:
+# http://www.sphinx-doc.org/en/master/config
+
+# -- Path setup --------------------------------------------------------------
+
+# If extensions (or modules to document with autodoc) are in another directory,
+# add these directories to sys.path here. If the directory is relative to the
+# documentation root, use os.path.abspath to make it absolute, like shown here.
+#
+# import os
+# import sys
+# sys.path.insert(0, os.path.abspath('.'))
+
+import recommonmark
+from recommonmark.parser import CommonMarkParser
+
+# -- Project information ---------------------------------------------------
+
+project = 'Neural Network Intelligence'
+copyright = '2019, Microsoft'
+author = 'Microsoft'
+
+# The short X.Y version
+version = ''
+# The full version, including alpha/beta/rc tags
+release = 'v0.5'
+
+# -- General configuration ---------------------------------------------------
+
+# If your documentation needs a minimal Sphinx version, state it here.
+#
+# needs_sphinx = '1.0'
+
+# Add any Sphinx extension module names here, as strings. They can be
+# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
+# ones.
+extensions = [
+    'sphinx.ext.autodoc',
+    'sphinx.ext.mathjax',
+    'sphinx_markdown_tables',
+    'sphinxarg.ext',
+]
+
+# Add any paths that contain templates here, relative to this directory.
+templates_path = ['_templates']
+
+# The suffix(es) of source filenames.
+# You can specify multiple suffix as a list of string:
+#
+source_parsers = {
+    '.md': CommonMarkParser
+}
+
+source_suffix = ['.rst', '.md']
+
+# The master toctree document.
+master_doc = 'index'
+
+# The language for content autogenerated by Sphinx. Refer to documentation
+# for a list of supported languages.
+#
+# This is also used if you do content translation via gettext catalogs.
+# Usually you set "language" from the command line for these cases.
+language = None
+
+# List of patterns, relative to source directory, that match files and
+# directories to ignore when looking for source files.
+# This pattern also affects html_static_path and html_extra_path.
+exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
+
+# The name of the Pygments (syntax highlighting) style to use.
+pygments_style = None
+
+
+# -- Options for HTML output -------------------------------------------------
+
+# The theme to use for HTML and HTML Help pages.  See the documentation for
+# a list of builtin themes.
+#
+html_theme = 'sphinx_rtd_theme'
+
+# Theme options are theme-specific and customize the look and feel of a theme
+# further.  For a list of options available for each theme, see the
+# documentation.
+#
+html_theme_options = {
+    'logo_only': True,
+}
+
+# Add any paths that contain custom static files (such as style sheets) here,
+# relative to this directory. They are copied after the builtin static files,
+# so a file named "default.css" will overwrite the builtin "default.css".
+html_static_path = ['_static']
+
+# Custom sidebar templates, must be a dictionary that maps document names
+# to template names.
+#
+# The default sidebars (for documents that don't match any pattern) are
+# defined by theme itself.  Builtin themes are using these templates by
+# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
+# 'searchbox.html']``.
+#
+# html_sidebars = {}
+
+html_logo = './img/nni_logo_dark.png'
+
+# -- Options for HTMLHelp output ---------------------------------------------
+
+# Output file base name for HTML help builder.
+htmlhelp_basename = 'NeuralNetworkIntelligencedoc'
+
+
+# -- Options for LaTeX output ------------------------------------------------
+
+latex_elements = {
+    # The paper size ('letterpaper' or 'a4paper').
+    #
+    # 'papersize': 'letterpaper',
+
+    # The font size ('10pt', '11pt' or '12pt').
+    #
+    # 'pointsize': '10pt',
+
+    # Additional stuff for the LaTeX preamble.
+    #
+    # 'preamble': '',
+
+    # Latex figure (float) alignment
+    #
+    # 'figure_align': 'htbp',
+}
+
+# Grouping the document tree into LaTeX files. List of tuples
+# (source start file, target name, title,
+#  author, documentclass [howto, manual, or own class]).
+latex_documents = [
+    (master_doc, 'NeuralNetworkIntelligence.tex', 'Neural Network Intelligence Documentation',
+     'Microsoft', 'manual'),
+]
+
+
+# -- Options for manual page output ------------------------------------------
+
+# One entry per manual page. List of tuples
+# (source start file, name, description, authors, manual section).
+man_pages = [
+    (master_doc, 'neuralnetworkintelligence', 'Neural Network Intelligence Documentation',
+     [author], 1)
+]
+
+
+# -- Options for Texinfo output ----------------------------------------------
+
+# Grouping the document tree into Texinfo files. List of tuples
+# (source start file, target name, title, author,
+#  dir menu entry, description, category)
+texinfo_documents = [
+    (master_doc, 'NeuralNetworkIntelligence', 'Neural Network Intelligence Documentation',
+     author, 'NeuralNetworkIntelligence', 'One line description of project.',
+     'Miscellaneous'),
+]
+
+
+# -- Options for Epub output -------------------------------------------------
+
+# Bibliographic Dublin Core info.
+epub_title = project
+
+# The unique identifier of the text. This can be a ISBN number
+# or the project homepage.
+#
+# epub_identifier = ''
+
+# A unique identification for the text.
+#
+# epub_uid = ''
+
+# A list of files that should not be packed into the epub file.
+epub_exclude_files = ['search.html']
+
+
+# -- Extension configuration -------------------------------------------------

docs/gbdt_example.md

+# GBDT in nni
+Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion as other boosting methods do, and it generalizes them by allowing optimization of an arbitrary differentiable loss function. 
+
+Gradient boosting decision tree has many popular implementations, such as [lightgbm](https://github.com/Microsoft/LightGBM), [xgboost](https://github.com/dmlc/xgboost), and [catboost](https://github.com/catboost/catboost), etc. GBDT is a great tool for solving the problem of traditional machine learning problem. Since GBDT is a robust algorithm, it could use in many domains. The better hyper-parameters for GBDT, the better performance you could achieve.
+
+NNI is a great platform for tuning hyper-parameters, you could try various builtin search algorithm in nni and run multiple trials concurrently. 
+
+
+## 1. Search Space in GBDT
+There are many hyper-parameters in GBDT, but what kind of parameters will affect the performance or speed? Based on some practical experience, some suggestion here(Take lightgbm as example):
+
+> * For better accuracy
+* `learning_rate`. The range of `learning rate` could be [0.001, 0.9].
+
+* `num_leaves`. `num_leaves` is related to `max_depth`, you don't have to tune both of them.
+    
+* `bagging_freq`. `bagging_freq` could be [1, 2, 4, 8, 10]
+
+* `num_iterations`. May larger if underfitting.
+
+> * For speed up
+* `bagging_fraction`. The range of `bagging_fraction` could be [0.7, 1.0].
+
+* `feature_fraction`. The range of `feature_fraction` could be [0.6, 1.0].
+    
+* `max_bin`.
+
+> * To avoid overfitting
+* `min_data_in_leaf`. This depends on your dataset.
+
+* `min_sum_hessian_in_leaf`. This depend on your dataset.
+
+* `lambda_l1` and `lambda_l2`.
+
+* `min_gain_to_split`.
+
+* `num_leaves`.
+
+Reference link:
+[lightgbm](https://lightgbm.readthedocs.io/en/latest/Parameters-Tuning.html) and 
+[autoxgoboost](https://github.com/ja-thomas/autoxgboost/blob/master/poster_2018.pdf)
+
+## 2. Task description
+Now we come back to our example "auto-gbdt" which run in lightgbm and nni. The data including [train data](https://github.com/Microsoft/nni/blob/master/examples/trials/auto-gbdt/data/regression.train) and [test data](https://github.com/Microsoft/nni/blob/master/examples/trials/auto-gbdt/data/regression.train). 
+Given the features and label in train data, we train a GBDT regression model and use it to predict.
+
+## 3. How to run in nni
+
+### 3.1 Prepare your trial code
+You need to prepare a basic code as following:
+``` python
+
+...
+
+def get_default_parameters():
+    ...
+    return params
+
+
+def load_data(train_path='./data/regression.train', test_path='./data/regression.test'):
+    '''
+    Load or create dataset
+    '''
+    ...
+
+    return lgb_train, lgb_eval, X_test, y_test
+
+def run(lgb_train, lgb_eval, params, X_test, y_test):
+    # train
+    gbm = lgb.train(params,
+                    lgb_train,
+                    num_boost_round=20,
+                    valid_sets=lgb_eval,
+                    early_stopping_rounds=5)
+    # predict
+    y_pred = gbm.predict(X_test, num_iteration=gbm.best_iteration)
+
+    # eval 
+    rmse = mean_squared_error(y_test, y_pred) ** 0.5
+    print('The rmse of prediction is:', rmse)
+
+if __name__ == '__main__':
+    lgb_train, lgb_eval, X_test, y_test = load_data()
+
+    PARAMS = get_default_parameters()
+    # train
+    run(lgb_train, lgb_eval, PARAMS, X_test, y_test)
+```
+
+### 3.2 Prepare your search space.
+If you like to tune `num_leaves`, `learning_rate`, `bagging_fraction` and `bagging_freq`, 
+you could write a [search_space.json](https://github.com/Microsoft/nni/blob/master/examples/trials/auto-gbdt/search_space.json) as follow:
+```
+{
+    "num_leaves":{"_type":"choice","_value":[31, 28, 24, 20]},
+    "learning_rate":{"_type":"choice","_value":[0.01, 0.05, 0.1, 0.2]},
+    "bagging_fraction":{"_type":"uniform","_value":[0.7, 1.0]},
+    "bagging_freq":{"_type":"choice","_value":[1, 2, 4, 8, 10]}
+}
+```
+
+More support variable type you could reference [here](https://github.com/Microsoft/nni/blob/master/docs/SearchSpaceSpec.md).
+
+### 3.3 Add SDK of nni into your code.
+```diff
++import nni
+...
+
+def get_default_parameters():
+    ...
+    return params
+
+
+def load_data(train_path='./data/regression.train', test_path='./data/regression.test'):
+    '''
+    Load or create dataset
+    '''
+    ...
+
+    return lgb_train, lgb_eval, X_test, y_test
+
+def run(lgb_train, lgb_eval, params, X_test, y_test):
+    # train
+    gbm = lgb.train(params,
+                    lgb_train,
+                    num_boost_round=20,
+                    valid_sets=lgb_eval,
+                    early_stopping_rounds=5)
+    # predict
+    y_pred = gbm.predict(X_test, num_iteration=gbm.best_iteration)
+
+    # eval 
+    rmse = mean_squared_error(y_test, y_pred) ** 0.5
+    print('The rmse of prediction is:', rmse)
++   nni.report_final_result(rmse)
+
+if __name__ == '__main__':
+    lgb_train, lgb_eval, X_test, y_test = load_data()
++   RECEIVED_PARAMS = nni.get_next_parameter()
+    PARAMS = get_default_parameters()
++   PARAMS.update(RECEIVED_PARAMS)
+    PARAMS = get_default_parameters()
+    PARAMS.update(RECEIVED_PARAMS)
+
+    # train
+    run(lgb_train, lgb_eval, PARAMS, X_test, y_test)
+```
+
+### 3.4 Write a config file and run it.
+In the config file, you could set some settings including:
+
+* Experiment setting: `trialConcurrency`, `maxExecDuration`, `maxTrialNum`, `trial gpuNum`, etc.
+* Platform setting: `trainingServicePlatform`, etc.
+* Path seeting: `searchSpacePath`, `trial codeDir`, etc.
+* Algorithm setting: select `tuner` algorithm, `tuner optimize_mode`, etc.
+
+An config.yml as follow:
+```yml
+authorName: default
+experimentName: example_auto-gbdt
+trialConcurrency: 1
+maxExecDuration: 10h
+maxTrialNum: 10
+#choice: local, remote, pai
+trainingServicePlatform: local
+searchSpacePath: search_space.json
+#choice: true, false
+useAnnotation: false
+tuner:
+  #choice: TPE, Random, Anneal, Evolution, BatchTuner
+  #SMAC (SMAC should be installed through nnictl)
+  builtinTunerName: TPE
+  classArgs:
+    #choice: maximize, minimize
+    optimize_mode: minimize
+trial:
+  command: python3 main.py
+  codeDir: .
+  gpuNum: 0
+```
+
+Run this experiment with command as follow:
+```
+nnictl create --config ./config.yml
+```
\ No newline at end of file

docs/howto_1_WriteTrial.md

-**Write a Trial Run on NNI**
-===
+# Write a Trial Run on NNI
 
 A **Trial** in NNI is an individual attempt at applying a set of parameters on a model.