# How to 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:
```
+-----------------+------------+-----------+--------=-------------+------------------------------------------+
|      Name       |    Type    |  source   |      Class Name      |               Module Name                |
+-----------------+------------+-----------+----------------------+------------------------------------------+
| demotuner       | tuners     |  user     | DemoTuner            | demo_tuner                               |
+-----------------+------------+-----------+----------------------+------------------------------------------+
```

## Use the installed tuner in experiment

Now you can use the demotuner in experiment configuration file the same way as other builtin tuners:

```yaml
tuner:
  builtinTunerName: demotuner
  classArgs:
    #choice: maximize, minimize
    optimize_mode: maximize
```