GitLab

* 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

* 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.

* Merge latest code changes into Github Master

* temporary modification for travis

* temporary modification for travis

* Improve Makefile

* Bugfix

* Add make target for remote machine workers

* Update travis config

* Debug travis

* Debug travis

* Debug travis

* Debug travis

* Debug travis

* Debug travis

* Debug travis

* Install bash completion script