Doc fix0 (#677)

* fix doc titles

* fix doc bug

docs/Contribution.rst

 ###############################
-Contribution to NNI
+Contribute to NNI
 ###############################
 
 ..  toctree::

docs/Customize_Assessor.md

 # Customize Assessor
 
-## Customize Assessor
-
 NNI also support building an assessor by yourself to adjust your tuning demand.
 
 If you want to implement a customized Assessor, there are three things for you to do:

docs/Overview.md

@@ -56,6 +56,4 @@ More details about how to run an experiment, please refer to [Get Started](Quick
 * [How to run an experiment on local?](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](mnist_examples.md)
-
-[How to do trouble shooting when using NNI?]: <> ()
\ No newline at end of file
+* [Examples](mnist_examples.md)
\ No newline at end of file

docs/QuickStart.md

@@ -177,7 +177,7 @@ The Web UI urls are: [Your IP]:8080
 
 Open the `Web UI url`(In this information is: `[Your IP]:8080`) in your browser, you can view detail information of the experiment and all the submitted trial jobs as shown below.
 
-### View summary page
+#### View summary page
 
 Click the tab "Overview".
 
@@ -189,7 +189,7 @@ Top 10 trials will be listed in the Overview page, you can browse all the trials
 
 ![](./img/QuickStart2.png)
 
-### View trials detail page
+#### View trials detail page
 
 Click the tab "Default Metric" to see the point graph of all trials. Hover to see its specific default metric and search space message.
 

docs/index.rst

@@ -9,7 +9,7 @@ Contents
 ..  toctree::
     :caption: Table of Contents
     :maxdepth: 2
-    :glob:
+    :titlesonly:
 
     Overview
     GetStarted<QuickStart>

docs/tuners.rst

@@ -2,9 +2,6 @@
 Tuners
 #################
 
-Overview
------------------
-
 NNI provides an easy way to adopt an approach to set up parameter tuning algorithms, we call them **Tuner**.
 
 Tuner receives the result from `Trial` as a matrix to evaluate the performance of a specific parameters/architecture configures. And tuner sends next hyper-parameter or architecture configure to Trial.