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Designed new interface to support reusable training service, currently only applies to OpenPAI, and default disabled.

Replace trial_keeper.py to trial_runner.py, trial_runner holds an environment, and receives commands from nni manager to run or stop an trial, and return events to nni manager.
Add trial dispatcher, which inherits from original trianing service interface. It uses to share as many as possible code of all training service, and isolate with training services.
Add EnvironmentService interface to manage environment, including start/stop an environment, refresh status of environments.
Add command channel on both nni manager and trial runner parts, it supports different ways to pass messages between them. Current supported channels are file, web sockets. and supported commands from nni manager are start, kill trial, send new parameters; from runner are initialized(support some channel doesn't know which runner connected), trial end, stdout ((new type), including metric like before), version check (new type), gpu info (new type).
Add storage service to wrapper a storage to standard file operations, like NFS, azure storage and so on.
Partial support run multiple trials in parallel on runner side, but not supported by trial dispatcher side.
Other minor changes,

Add log_level to TS UT, so that UT can show debug level log.
Expose platform to start info.
Add RouterTrainingService to keep origianl OpenPAI training service, and support dynamic IOC binding.
Add more GPU info for future usage, including GPU mem total/free/used, gpu type.
Make some license information consistence.
Fix async/await problems on Array.forEach, this method doesn't support async actually.
Fix IT errors on download data, which causes by my #2484 .
Accelerate some run loop pattern by reducing sleep seconds.

Co-authored-by: liuzhe <zhe.liu@microsoft.com>

* skeleton of dlts training service (#1844)

* Hello, DLTS!

* Revert version

* Remove fs-extra

* Add some default cluster config

* schema

* fix

* Optional cluster (default to `.default`)

Depends on DLWorkspace#837

* fix

* fix

* optimize gpu type

* No more copy

* Format

* Code clean up

* Issue fix

* Add optional fields in config

* Issue fix

* Lint

* Lint

* Validate email, password and team

* Doc

* Doc fix

* Set TMPDIR

* Use metadata instead of gpu_capacity

* Cancel paused DLTS job

* workaround lint rules

* pylint

* doc
Co-authored-by: QuanluZhang <z.quanluzhang@gmail.com>

* update eslint rules
* auto fix eslint
* manually fix eslint (#1833)

* Refactor web UI to support incremental metric loading

* refactor

* Remove host job

* Move sequence ID to NNI manager

* implement incremental loading

* support specifying gpu for tuner and advisor

* PPO tuner for NAS, supports NNI's NAS interface (#1380)

* dev oneshot and darts mode, add mnist example

* fix link err in docs

* add spaces

* re-organise links for detailed descriptions of the tuners and accessors; fix link err in HpoComparision.md

* add in-page link by change .md to .html

* delete #section from cross-file links to make links work in both readthedocs and github docs

* gp_tuner init from fmfn's repo

* fix params bug by adding float>int transition

* add optimal choices; support randint&quniform type; add doc

* refine doc and code

* change mnist yml comments

* typo fix

* fix val err

* fix minimize mode err

* add config test and Hpo result

* support quniform type; update doc; update test config

* update doc

* un-commit changed in yarn.lock

* fix optimize mode bug

* optimize mode

* optimize mode

* reset pylint, gitignore

* revert .gitignore yarn.lock

* update

* dev-tf-master

* fix bugs

* fix bugs

* remove unnecessary lines

* dev oneshot and darts

* dev nas

* dev enas and oneshot

* dev enas and oneshot

* dev enas and oneshot

* dev oneshot and enas

* dev oneshot

* add ut

* add docstring

* add docstring

* fix

* resolve comments by changing docstring

* resolve comments

* Refactoring local training service
* Designated GPU for local training service
* RemoteMachine designated GPU configuration

add BOHB Advisor

1. Route tuner and assessor commands to 2 seperate queues  issue #841
2. Allow tuner to leverage intermediate result when trial is early stopped.  issue #843

If user set remoteloggingType in config file, log content will not be transmitted from trialkeeper

check nni version in trialkeeper, to make sure the version of trialkeeper is consistent with trainingService
add a debug mode in config file

* Pull code (#22)

* Support distributed job for frameworkcontroller (#612)

support distributed job for frameworkcontroller

* Multiphase doc (#519)

* multiPhase doc

* updates

* updates

* Add time parser for 'nnictl update duration' (#632)

Current nnictl update duration only support seconds unit, add a parser for this command to support {s, m, h, d}

* fix experiment state bug (#629)

* update top README.md (#622)

* Update README.md

* update (#634)

* Integration tests refactoring (#625)

* Integration test refactoring (#21) (#616)

* Integration test refactoring (#21)

* Refactoring integration tests

* test metrics

* update azure pipeline

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* update trigger

* Integration test refactoring (#618)

* updates

* updates

* update pipeline (#619)

* update pipeline

* updates

* updates

* updates

* updates

* updates

* test pipeline (#623)

* test pipeline

* updates

* updates

* updates

* Update integration test (#624)

* Update integration test

* updates

* updates

* updates

* updates

* updates

* updates

* Revert "Pull code (#22)"

This reverts commit 62fc165ad7b2ba724eead3b99f010aa34491e2c7.

* Update nnimanager logs

* updates

* Update README.md

* Revert "Update README.md"

This reverts commit bc67061160e5d57305a6e7fb63d491d12d0e9002.

* updates

* updates

* add serviceAccountName

* add serviceAccountName for frameworkcontroller

* 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

Remote TrainingService, passwd is not required when users set sshKeyPath.

Add frameworkcontroller training service based on kubeflow training service.
Refactor code structure, add kubernetes training service as father class, and set kubeflow training service and frameworkcontroller training service as child class.

* Add curve fitting assessor

* Update HowToChooseTuner.md

* Update HowToChooseTuner.md

* Update HowToChooseTuner.md

* Update README.md

* Update README.md

* Update README.md

* Update HowToChooseTuner.md

* Update HowToChooseTuner.md

* Update HowToChooseTuner.md

* Update HowToChooseTuner.md

* Update curvefitting_assessor.py

* Update config_schema.py

* Add some comments and modifications

* Remove unnecessary .json file

* Remove unnecessary .lock file

* Revert "Remove unnecessary .lock file"

This reverts commit cdfaacb29114b3dee9c797d3e9b46ee18d7d34cc.

* Revert "Revert "Remove unnecessary .lock file""

This reverts commit 7182a5fb31a02b01684429eabb3347952bf7ce2a.

* Revert "Revert "Revert "Remove unnecessary .lock file"""

This reverts commit 0f010e2b508e9f7b34c809647ba09e4e132876d8.

* Revert "Remove unnecessary .json file"

This reverts commit c6f7b47c199dd0db7ccb850d4f2ac1fd97b0caf8.

* Revert "Add some comments and modifications"

This reverts commit f78f055df9a4eec5b433a9241ce93d8ba78e3500.

* Add some modifications by comments

* suppoort minimize mode

* Update README.md

* Update README.md

* Update modelfactory.py

* minor changes and fix typo

* minor chages

* update README.md

[Kubeflow training service] Use Kubernete API server to replace kubectl dependency

* Quick fix nnictl config logic (#289)

* fix nnictl bug

* fix install.sh

* add desc for Dockerfile.build.base

* update document for Dockerfile

* update

* refactor port detect

* update

* refactor NNICTLDOC.md

* add document for pai and nnictl

* add default value for port

* add exception handling in trial_keeper.py

* fix port bug

* fix resume

* fix nnictl resume and fix nnictl stop

* fix document

* update

* refactor nnictl

* update

* update doc

* update

* update nnictl

* fix comment

* revert dockerfile

* update

* update

* update

* fix nnictl error hit

* fix comments

* fix bash-completion

* fix paramiko install

* quick fix resume logic

* update

* quick fix nnictl

* PR merge to 0.3 (#297)

* refactor doc

* update with Mao's suggestions

* Set theme jekyll-theme-dinky

* update doc

* fix links

* fix links

* fix links

* merge

* fix links and doc errors

* merge

* merge

* merge

* merge

* Update README.md (#288)

added License badge

* merge

* updated the "Contribute" part (merged Gems' wiki in, updated ReadMe)

* fix link

* fix doc mistakes and broken links. (#271)

* refactor doc

* update with Mao's suggestions

* Set theme jekyll-theme-dinky

* updated the "Contribute" part (merged Gems' wiki in, updated ReadMe)

* fix link

* Update README.md

* Fix misspelling in examples/trials/ga_squad/README.md

* revise the installation cmd to v0.2

* revise to install v0.2

* remove enas readme (#292)

* Fix datastore performance issue (#301)

* Fix nnictl in v0.3 (#299)

Fix old version of config file
fix sklearn requirements
Fix resume log logic

* add basic tuner and trial for network morphism

* Complete basic receive_trial_result() and generate_parameters(). Use onnx  as the intermediate representation ( But it cannot convert to pytorch model )

* add tensorflow cifar10 for network morphism

* add unit test for tuner and its function

* use temporary torch_model

* fix request bug and program can communicate nni

* add basic pickle support for graph and train successful in pytorch

* Update unittest for networkmorphism_tuner

* Network Morphism add multi-gpu trial training support

* Format code with black tool

* change intermediate representation from pickle file to json we defined

* successfully pass the unittest for test_graph_json_transform

* add README for network morphism and it works fine in both Pytorch and Keras.

* separate the original Readme.md in network-morphism into two parts (tuner and trial)

* change the openpai image path

* beautify the file structure of network_morphism and add a fashion_mnist keras example

* pretty the source and add some docstring for funtion in order to pass the pylint.

* remove unused module import and add some docstring

* add some details for the application scenario Network Morphism Tuner

* follow the advice and modify the doc file

* add the config file for each task in the examples trial of network morphism

* change default python interpreter from python to python3