update customized algos doc (#3241)

docs/en_US/Tutorial/InstallCustomizedAlgos.rst

@@ -2,6 +2,8 @@
 **How to register customized algorithms as builtin tuners, assessors and advisors**
 =======================================================================================
 
+.. contents::
+
 Overview
 --------
 
@@ -103,8 +105,10 @@ Run following command to register the customized algorithms as builtin algorithm
 
 The ``<path_to_meta_file>`` is the path to the yaml file your created in above section.
 
-6. Use the installed builtin algorithms in experiment
------------------------------------------------------
+Reference `customized tuner example <#example-register-a-customized-tuner-as-a-builtin-tuner>`_ for a full example.
+
+Use the installed builtin algorithms in experiment
+--------------------------------------------------
 
 Once your customized algorithms is installed, you can use it in experiment configuration file the same way as other builtin tuners/assessors/advisors, for example:
 
@@ -117,7 +121,7 @@ Once your customized algorithms is installed, you can use it in experiment confi
        optimize_mode: maximize
 
 Manage builtin algorithms using ``nnictl algo``
----------------------------------------------------
+-----------------------------------------------
 
 List builtin algorithms
 ^^^^^^^^^^^^^^^^^^^^^^^
@@ -158,3 +162,61 @@ Run following command to uninstall an installed package:
 For example:
 
 ``nnictl algo unregister demotuner``
+
+
+Porting customized algorithms from v1.x to v2.x
+-----------------------------------------------
+
+All that needs to be modified is to delete ``NNI Package :: tuner`` metadata in ``setup.py`` and add a meta file mentioned in `4. Prepare meta file`_. Then you can follow `Register customized algorithms as builtin tuners, assessors and advisors`_ to register your customized algorithms.
+
+Example: Register a customized tuner as a builtin tuner
+-------------------------------------------------------
+
+You can following below steps to register a customized tuner in ``nni/examples/tuners/customized_tuner`` as a builtin tuner.
+
+Install the customized tuner package into python environment
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+There are 2 options to install the package into python environment:
+
+Option 1: install from directory
+""""""""""""""""""""""""""""""""
+
+From ``nni/examples/tuners/customized_tuner`` directory, run:
+
+``python setup.py develop``
+
+This command will build the ``nni/examples/tuners/customized_tuner`` directory as a pip installation source.
+
+Option 2: install from whl file
+"""""""""""""""""""""""""""""""
+
+Step 1: From ``nni/examples/tuners/customized_tuner`` directory, run:
+
+``python setup.py bdist_wheel``
+
+This command build a whl file which is a pip installation source.
+
+Step 2: Run command:
+
+``pip install dist/demo_tuner-0.1-py3-none-any.whl``
+
+Register the customized tuner as builtin tuner:
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Run following command:
+
+``nnictl algo register --meta meta_file.yml``
+
+Check the registered builtin algorithms
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Then run command ``nnictl algo list``\ , you should be able to see that demotuner is installed:
+
+.. code-block:: bash
+
+   +-----------------+------------+-----------+--------=-------------+------------------------------------------+
+   |      Name       |    Type    |   source  |      Class Name      |               Module Name                |
+   +-----------------+------------+-----------+----------------------+------------------------------------------+
+   | demotuner       | tuners     |    User   | DemoTuner            | demo_tuner                               |
+   +-----------------+------------+-----------+----------------------+------------------------------------------+