Release 0.5.0 - 01/15/2019

New tuner and assessor supports

Support Metis tuner as a new NNI tuner. Metis algorithm has been proofed to be well performed for online hyper-parameter tuning.
Support ENAS customized tuner, a tuner contributed by github community user, is an algorithm for neural network search, it could learn neural network architecture via reinforcement learning and serve a better performance than NAS.
Support Curve fitting assessor for early stop policy using learning curve extrapolation.
Advanced Support of Weight Sharing: Enable weight sharing for NAS tuners, currently through NFS.

FrameworkController Training service: Support run experiments using frameworkcontroller on kubernetes
- FrameworkController is a Controller on kubernetes that is general enough to run (distributed) jobs with various machine learning frameworks, such as tensorflow, pytorch, MXNet.
- NNI provides unified and simple specification for job definition.
- MNIST example for how to use FrameworkController.

A better trial logging support for NNI experiments in PAI, Kubeflow and FrameworkController mode:
- An improved logging architecture to send stdout/stderr of trials to NNI manager via Http post. NNI manager will store trial's stdout/stderr messages in local log file.
- Show the link for trial log file on WebUI.
Support to show final result's all key-value pairs.