GitLab

* Revert to orginal `nnictl log trial` and `nnictl trial kill`

* Change print() to print_normal()

Fix issue #890

Advisor and assessor could not be used simultaneously.
Refactor config file error message.
Support scientific notation, like 1e-2

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

add BOHB Advisor

add trial id to csv and remove pandas

* export to csv core code done

* add nnictl trail export

* fix bug

* add dependency for pandas

* remove pandas from dependency

* add multi phase support

* add document

* 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

* update home page

* fix issue: #902, random parameter

* update doc about random

* change Random tuner test

* update metric_test for Random tuner

* update random config in test

* update Evolution_SQuAD doc

* add different tuner config files for config_test

* change MetisTuner config test due to no lightgbm python module in integration test

* install smac package in azure-pipelines

* SMAC need swig to be installed

* Try to install swig from source code

* remove SMAC test because the dependency can not be installed

* use sudo to install the swig

* sleep 10s to make sure the port has been released

* remove tuner test for networkmorphism because it uses more than 30s to release the tcp port

* word "down" to "done"

* add config test for Curvefitting assessor

* change file name

* Fix data type not match bug

* Optimize MetisTunner

* pretty the code

* Follow the review comment

* add exploration probability

* Avoid None type object generating

* fix nnictl log trial bug

* rollback chinese doc

* add argument 'experiment' to parser_log_trial and parser_trial_kill

* update doc

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

In nnictl, we support debug mode from config file and --debug.
If users does not set debug: true in config, nnictl will use --debug value.

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

Improve the performance of the curve fitting assessor 

Add integration test for remoteTrainingService platform

* add trialkeeper_stdout and trialkeeper_stderr
* fix nnictl set remote nniManagerIP

* fix remote bug

* add document

* add document

* update

* update

* update

* update

* fix remote issue

* fix forEach

* update doc according to comments

* update

* update

* update

* remove 'any more'

* add base version for remote-log

* change launcher.py

* test

* basic version

* debug

* debug

* basic work version

* fix code

* update disable_log

* remove unused line

* add diable log in kubernetesTrainingService

* add detect frameworkcontroller

* fix comment

* update

* update

* fix kubernetesData

* debug

* debug

* debug

* fix comment

* fix conflict

* remove local temp files

* revert launcher.py

* update code by comments

* remove disableLog

* remove disable Log

* set timeout for cleanup

* fix code by comments

* update variable names

* add comments

* add delay function

* update

* update

* update by comments

* add  in remote script path

* rename variables

* update variable name

* add mkdir -p for subfolder

* 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.

* Configurable nniManager log path

* Configure log level

* add --debug command line for nnictl

* updates

* fix nni-sdk version problem

* fix

* fix installation

* fix installation

* fix installation

* resolve suggestion

* resolve suggestion

* resolve suggestion

* resolve suggestion

* refactor logic

* refactor logic

* resolve comments

* add serviceAccountName

* add serviceAccountName for frameworkcontroller

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

* add module info for launcher check

* update launcher.py

Add packages check before start restful server.

* check sub-key

* modify mistype

* delete non-tuner in constants/ModuleName

* Delete ModuleName to prevent double maintain

* only catch ModuleNotFoundError

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

* 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

* 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

* Add UT code coverage report

* updates

* updates

* updates

* updates

* updates

* updates

* integration test python code coverage report

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.

* Update nnictl.py

Fix the issue that nnictl --version via pip installation doesn't work

* Update kubeflow training service document (#494)

* Remove kubectl related document, add messages for kubeconfig
* Add design section for kubeflow training service
* Move the image files for PAI training service doc into img folder.

* Update KubeflowMode.md (#498)

Update KubeflowMode.md, small terms change

* [V0.4.1 bug fix] Cannot run kubeflow training service due to trial_keeper change (#503)

* Update kubeflow training service document

* fix bug a that kubeflow trial job cannot run

* upgrade version number (#499)

* [V0.4.1 bug fix] Support read K8S config from KUBECONFIG environment variable (#507)

* Add KUBCONFIG env variable support

* In main.ts, throw cached error to make sure nnictl can show the error in stderr

* 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

rest api of kubernetes does not use base64 to encode chars, now use base64 to encode username and then create secret.

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

Add nnictl top command to monitor the nni experiments.

* 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