GitLab

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

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

* 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

[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

* 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

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.

* fix-annotation

* fix annotation for error printing

* update annotation

* update annotation

* update annotation

* update annotation

* update unittest for annotation

* update unit test

* update annotation

* update annotation

* update annotation

* update ut

* update ut

* 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

* [PAI training service] codeDir files upload improvement

* Create full local temp folder

* Organize the folder structure for experiment and trial files

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

1.Support pytorch-operator
2.remove unsupported operator

move nnictl folder
delete kubernetsServer in nnictl
refactor aks document
add warning information to expand relative path
update experiment status when the experiment crashed.

* Change version number from v0.3.4 to v0.4, for NNI v0.4 release

* Remove unused kubernetesServer config entry in config file and schema validation

* support hyperband

* add example for hyperband

* register Hyperband in tuner

* after debug

* update doc

* trivial change

* update spec validation of yaml config

* modify nnictl launcher

* modify nnimanager and util to support advisor

* 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

* refactor sdk main

* update unit test accordingly

* update example's config file

* update restserver validation

* 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 files

* update

* remove enas readme (#292)

* support checkpoint directory

* Fix datastore performance issue (#301)

* fix pylint

* Fix nnictl in v0.3 (#299)

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

* modify log

* trivial changes

* update example

* update makefile

* update launcher.py to fix the problem of finding main.js

* debug

* add hyperparameter info into trial_end api

* fix bug and update example

* fix error induced by merge

* support initialize

* add doc for hyperband

* fix bugs and add config_pai

* fix bugs and add config_pai

* fix bugs and add config_pai

* fix bugs and add config_pai

* update doc

* add doc for advisor

* fit

* modification based on hui's comments

* update doc

* update doc for "write trial"

* fix link

* issue 414

1.Refactor nnictl information when validateion error.
2.Set kubernetesServer as optional.

* [Trial keeper refactor] refactor trial keeper stdout output

* [PAI training service] Support virtual cluster config

* fix a small bug to convert virtualCluster to string

Support aks of kuberflow training service
Support nnictl set nniManagerIp

Add nniManager Ip in nnictl, pai TrainingService and kubeflow TrainingService.
If users set nniManagerIp, pai and kubeflow will use this ip instead of using getIPV4() function.
Web UI will also use this nniManagerIp.

In nnictl, classArgs is not required, now set it as optional for some kind of tuner and assessor may not require classArgs.

[Kubeflow training service] Update kubeflow exp job config schema to support distributed training (#387)

* Support distributed training on tf-operator, for worker and ps

* Update validation rule for kubeflow config

* small code refactor adjustment for private methods

* Use different output folder for ps and worker

* Asynchronous dispatcher

* updates

* updates

* updates

* updates

* Kubeflow TrainingService support, v1 (#373)

1. Create new Training Service: kubeflow trainning service, use 'kubectl' and kubeflow tfjobs CRD to submit and manage jobs
2. Update nni python SDK to support new kubeflow platform
3. Update nni python SDK's get_sequende_id() implementation, read NNI_TRIAL_SEQ_ID env variable, instead of reading .nni/sequence_id file
4. This version only supports Tensorflow operator. Will add more operators' support in future versions

Fix "nnictl stop"

* add gridsearch tuner

* add gridsearchtuner

* add gridsearchtuner

* add gridsearchtuner

* update gridsearch tuner

* update gridsearch tuner

* update gridsearch tuner

* update gridsearch tuner

* update gridsearch tuner

* update gridsearch tuner

* update gridsearch tuner

* update gridsearch and pylint

1.Set scikit-learn==0.20.0 in Dockerfile
2.Update readme.md of dockerile
3.Add PyTorch 0.4.1
4.Add description for 'nnictl stop all'

* update makefile

* update launcher.py to fix the problem of finding main.js

* remove duplicated lib

* Change base image from devel to runtime, to reduce docker image size

* Support running multiple experiment for PAI

* Fix a bug regarding to recuisively reference between paiRestServer and
paiTrainingService