Document updates for v0.3 (#318)

* refactor doc

* update with Mao's suggestions

* Set theme jekyll-theme-dinky

* update doc

* fix links

* fix links

* fix links

* merge

* fix links and doc errors

* merge

* merge

* merge

* merge

* Quick fix nnictl config logic (#289)

* fix nnictl bug

* fix install.sh

* add desc for Dockerfile.build.base

* update document for Dockerfile

* update

* refactor port detect

* update

* refactor NNICTLDOC.md

* add document for pai and nnictl

* add default value for port

* add exception handling in trial_keeper.py

* fix port bug

* fix resume

* fix nnictl resume and fix nnictl stop

* fix document

* update

* refactor nnictl

* update

* update doc

* update

* update nnictl

* fix comment

* revert dockerfile

* update

* update

* update

* fix nnictl error hit

* fix comments

* fix bash-completion

* fix paramiko install

* quick fix resume logic

* update

* quick fix nnictl

* merge

* updated the "Contribute" part (merged Gems' wiki in, updated ReadMe)

* fix link

* revise the installation cmd to v0.2

* revise to install v0.2

* Update nnictl_utils.py

* Update nnictl_utils.py

* Update nnictl_utils.py

* Update documentation for v0.3

README.md

@@ -82,24 +82,18 @@ You can use these commands to get more information about the experiment
 * [Installation](docs/InstallNNI_Ubuntu.md)
 * [Use command line tool nnictl](docs/NNICTLDOC.md)
 * [Use NNIBoard](docs/WebUI.md)
-* [Define search space](docs/SearchSpaceSpec.md)
-* [Use NNI sdk] - *coming soon*
+* [How to define search space](docs/SearchSpaceSpec.md)
 * [Config an experiment](docs/ExperimentConfig.md)
-* [Use annotation]- *coming soon*
+* [Use annotation](docs/AnnotationSpec.md)
 * [Debug](docs/HowToDebug.md)
 ## **Tutorials**
-* [How to run an experiment on local (with multiple GPUs)?](docs/tutorial_1_CR_exp_local_api.md)
-* [How to run an experiment on multiple machines?](docs/tutorial_2_RemoteMachineMode.md)
-* [How to run an experiment on OpenPAI?](docs/PAIMode.md)
-* [Try different tuners and assessors] - *coming soon*
-* [How to run an experiment on K8S services?] - *coming soon*
-* [Implement a customized tuner] - *coming soon*
-* [Implement a customized assessor] - *coming soon*
-* [Implement a custmoized weight sharing algorithm] - *coming soon*
-* [How to integrate NNI with your own custmoized training service] - *coming soon*
-### **Best practice**
-* [Compare different AutoML algorithms] - *coming soon*
-* [Serve NNI as a capability of a ML Platform] - *coming soon*
+* [Run an experiment on local (with multiple GPUs)?](docs/tutorial_1_CR_exp_local_api.md)
+* [Run an experiment on multiple machines?](docs/tutorial_2_RemoteMachineMode.md)
+* [Run an experiment on OpenPAI?](docs/PAIMode.md)
+* [Try different tuners and assessors](docs/tutorial_3_tryTunersAndAccessors.md)
+* [Implement a customized tuner](docs/howto_2_CustomizedTuner.md)
+* [Implement a customized assessor](examples/assessors/README.md)
+* [Use Genetic Algorithm to find good model architectures for Reading Comprehension task](examples/trials/ga_squad/README.md)
 
 ## **Contribute**
 This project welcomes contributions and suggestions, we use [GitHub issues](https://github.com/Microsoft/nni/issues) for tracking requests and bugs.

docs/AnnotationSpec.md

-# Introduction 
+# NNI Annotation 
 
 For good user experience and reduce user effort, we need to design a good annotation grammar.
 

docs/ExperimentConfig.md

-Experiment config reference
+# Experiment config reference
 ===
 
 If you want to create a new nni experiment, you need to prepare a config file in your local machine, and provide the path of this file to nnictl.

docs/tutorial_3_tryTunersAndAccessors.md

+# Tutorial - Try different Tuners and Accessors
+
+NNI provides an easy to adopt approach to set up parameter tuning algorithms as well as early stop policies, we call them **Tuners** and **Accessors**.
+  
+**Tuner** specifies the algorithm you use to generate hyperparameter sets for each trial. In NNI, we support two approaches to set the tuner. 
+1. Directly use tuner provided by nni sdk
+
+        required fields: builtinTunerName and classArgs. 
+
+2. Customize your own tuner file
+
+        required fields: codeDirectory, classFileName, className and classArgs.
+
+### **Learn More about tuners**
+* For detailed defintion and usage aobut the required field, please refer to [Config an experiment](ExperimentConfig.md)
+* [Tuners in the latest NNI release](../src/sdk/pynni/nni/README.md)
+* [How to implement your own tuner](howto_2_CustomizedTuner.md)
+
+
+**Assessor** specifies the algorithm you use to apply early stop policy. In NNI, there are two approaches to set theassessor. 
+1. Directly use accessor provided by nni sdk
+
+        required fields: builtinAssessorName and classArgs. 
+
+2. Customize your own tuner file
+
+        required fields: codeDirectory, classFileName, className and classArgs.
+
+### **Learn More about assessor**
+* For detailed defintion and usage aobut the required field, please refer to [Config an experiment](ExperimentConfig.md)
+* Find more about the detailed instruction about [enable accessor](EnableAssessor.md)
+* [How to implement your own assessor](../examples/assessors/README.md)
+
+## **Learn More**
+* [How to run an experiment on local (with multiple GPUs)?](tutorial_1_CR_exp_local_api.md)
+* [How to run an experiment on multiple machines?](tutorial_2_RemoteMachineMode.md)
+* [How to run an experiment on OpenPAI?](PAIMode.md)

examples/assessors/README.md

-# Customized Assessor for Experts
+# Define your own Assessor
 
 *Assessor receive intermediate result from Trial and decide whether the Trial should be killed. Once the Trial experiment meets the early stop conditions, the assessor will kill the Trial.*