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Designed new interface to support reusable training service, currently only applies to OpenPAI, and default disabled.

Replace trial_keeper.py to trial_runner.py, trial_runner holds an environment, and receives commands from nni manager to run or stop an trial, and return events to nni manager.
Add trial dispatcher, which inherits from original trianing service interface. It uses to share as many as possible code of all training service, and isolate with training services.
Add EnvironmentService interface to manage environment, including start/stop an environment, refresh status of environments.
Add command channel on both nni manager and trial runner parts, it supports different ways to pass messages between them. Current supported channels are file, web sockets. and supported commands from nni manager are start, kill trial, send new parameters; from runner are initialized(support some channel doesn't know which runner connected), trial end, stdout ((new type), including metric like before), version check (new type), gpu info (new type).
Add storage service to wrapper a storage to standard file operations, like NFS, azure storage and so on.
Partial support run multiple trials in parallel on runner side, but not supported by trial dispatcher side.
Other minor changes,

Add log_level to TS UT, so that UT can show debug level log.
Expose platform to start info.
Add RouterTrainingService to keep origianl OpenPAI training service, and support dynamic IOC binding.
Add more GPU info for future usage, including GPU mem total/free/used, gpu type.
Make some license information consistence.
Fix async/await problems on Array.forEach, this method doesn't support async actually.
Fix IT errors on download data, which causes by my #2484 .
Accelerate some run loop pattern by reducing sleep seconds.

* Refactor multiphase interface

* Implement multiphase on PAI

* update multiphase doc

[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

* 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.

* support package install (#91)

* fix nnictl bug

* support package install

* update

* update package install logic

* Fix package install issue (#95)

* fix nnictl bug

* fix pakcage install

* support SMAC as a tuner on nni (#81)

* update doc

* update doc

* update doc

* update hyperopt installation

* update doc

* update doc

* update description in setup.py

* update setup.py

* modify encoding

* encoding

* add encoding

* remove pymc3

* update doc

* update builtin tuner spec

* support smac in sdk, fix logging issue

* support smac tuner

* add optimize_mode

* update config in nnictl

* add __init__.py

* update smac

* update import path

* update setup.py: remove entry_point

* update rest server validation

* fix bug in nnictl launcher

* support classArgs: optimize_mode

* quick fix bug

* test travis

* add dependency

* add dependency

* add dependency

* add dependency

* create smac python package

* fix trivial points

* optimize import of tuners, modify nnictl accordingly

* fix bug: incorrect algorithm_name

* trivial refactor

* for debug

* support virtual

* update doc of SMAC

* update smac requirements

* update requirements

* change debug mode

* update doc

* update doc

* refactor based on comments

* fix comments

* Merge latest code changes into Github Master

* temporary modification for travis

* temporary modification for travis