GitLab

* Add example for EfficientNet and upgrade PyTorch in Dockerfile

* squash commits in v1.0 first round bug bash

* Update readme

update version number

release related doc/note modification for v0.5.1

fix indents of doc,
change nni to NNI
yaml to yml(file) and YAML(doc)

* fix some bugs in doc and log

* The learning rate focus more on validation sets accuracy than training sets accuracy.

* update Dockerfile and README

* Update README.md

Merge to branch v0.5

* Dockerfile improvement

* Fix UT broken for kubeflow training service

Remove "RUN python3 -m pip --no-cache-dir install torch torchvision"

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 local demo doc and configuration

* change folder name

* Update tutorial_1_CR_exp_local_api.md

no need to have a new training file

* Delete mnist_gpu.py

no need to have a new training file

* Update config_gpu.yml

no need to have a new training file

* add PyTorch to Dockerfile

* update doc for docker image

* update

* Fix pypi package missing python module

* Fix pypi package missing python module

* fix bug in smartparam example (#322)

* Fix nnictl update trialnum and document (#326)

1.Fix restful server of update
2.Update nnictl document of update
3.Add tensorboard in docement

* Update the version numbers from 0.3.2 to 0.3.3

1.Fix old version of config file
2.fix sklearn requirements
3.Fix resume log logic