GitLab

* 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

* [PAI training service] codeDir files upload improvement

* Create full local temp folder

* Organize the folder structure for experiment and trial files

* [Trial keeper refactor] refactor trial keeper stdout output

* 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

* 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