# Installation of NNI

Currently we support installation on Linux, macOS and Windows.

## Install on Linux or macOS

* Install NNI through pip

  Prerequisite: `python 64-bit >= 3.5`

  ```bash
  python3 -m pip install --upgrade nni
  ```

* Install NNI through source code

  If you are interested on special or latest code version, you can install NNI through source code.

  Prerequisites: `python 64-bit >=3.5`, `git`, `wget`

  ```bash
  git clone -b v0.8 https://github.com/Microsoft/nni.git
  cd nni
  ./install.sh
  ```

* Use NNI in a docker image

  You can also install NNI in a docker image. Please follow the instructions [here](https://github.com/Microsoft/nni/tree/master/deployment/docker/README.md) to build NNI docker image. The NNI docker image can also be retrieved from Docker Hub through the command `docker pull msranni/nni:latest`.

## Install on Windows

  Anaconda or Miniconda is highly recommended to manage multiple Python environments.

* Install NNI through pip

  Prerequisites: `python 64-bit >= 3.5`

  ```bash
  python -m pip install --upgrade nni
  ```

* Install NNI through source code

  If you are interested on special or latest code version, you can install NNI through source code.

  Prerequisites: `python 64-bit >=3.5`, `git`, `PowerShell`.

  ```bash
  git clone -b v0.8 https://github.com/Microsoft/nni.git
  cd nni
  powershell -ExecutionPolicy Bypass -file install.ps1
  ```

## Verify installation

The following example is built on TensorFlow 1.x. Make sure **TensorFlow 1.x is used** when running it.

* Download the examples via clone the source code.

  ```bash
  git clone -b v1.3 https://github.com/Microsoft/nni.git
  ```

* Run the MNIST example.

  Linux or macOS

  ```bash
  nnictl create --config nni/examples/trials/mnist-tfv1/config.yml
  ```

  Windows

  ```bash
  nnictl create --config nni\examples\trials\mnist-tfv1\config_windows.yml
  ```

* Wait for the message `INFO: Successfully started experiment!` in the command line. This message indicates that your experiment has been successfully started. You can explore the experiment using the `Web UI url`.

```text
INFO: Starting restful server...
INFO: Successfully started Restful server!
INFO: Setting local config...
INFO: Successfully set local config!
INFO: Starting experiment...
INFO: Successfully started experiment!
-----------------------------------------------------------------------
The experiment id is egchD4qy
The Web UI urls are: http://223.255.255.1:8080   http://127.0.0.1:8080
-----------------------------------------------------------------------

You can use these commands to get more information about the experiment
-----------------------------------------------------------------------
         commands                       description
1. nnictl experiment show        show the information of experiments
2. nnictl trial ls               list all of trial jobs
3. nnictl top                    monitor the status of running experiments
4. nnictl log stderr             show stderr log content
5. nnictl log stdout             show stdout log content
6. nnictl stop                   stop an experiment
7. nnictl trial kill             kill a trial job by id
8. nnictl --help                 get help information about nnictl
-----------------------------------------------------------------------
```

* Open the `Web UI url` in your browser, you can view detail information of the experiment and all the submitted trial jobs as shown below. [Here](../Tutorial/WebUI.md) are more Web UI pages.

![overview](../../img/webui_overview_page.png)

![detail](../../img/webui_trialdetail_page.png)

## System requirements

Due to potential programming changes, the minimum system requirements of NNI may change over time.

### Linux

|                      | Recommended                                    | Minimum                                |
| -------------------- | ---------------------------------------------- | -------------------------------------- |
| **Operating System** | Ubuntu 16.04 or above                          |
| **CPU**              | Intel® Core™ i5 or AMD Phenom™ II X3 or better | Intel® Core™ i3 or AMD Phenom™ X3 8650 |
| **GPU**              | NVIDIA® GeForce® GTX 660 or better             | NVIDIA® GeForce® GTX 460               |
| **Memory**           | 6 GB RAM                                       | 4 GB RAM                               |
| **Storage**          | 30 GB available hare drive space               |
| **Internet**         | Boardband internet connection                  |
| **Resolution**       | 1024 x 768 minimum display resolution          |

### macOS

|                      | Recommended                           | Minimum                                                   |
| -------------------- | ------------------------------------- | --------------------------------------------------------- |
| **Operating System** | macOS 10.14.1 or above                |
| **CPU**              | Intel® Core™ i7-4770 or better        | Intel® Core™ i5-760 or better                             |
| **GPU**              | AMD Radeon™ R9 M395X or better        | NVIDIA® GeForce® GT 750M or AMD Radeon™ R9 M290 or better |
| **Memory**           | 8 GB RAM                              | 4 GB RAM                                                  |
| **Storage**          | 70GB available space SSD              | 70GB available space 7200 RPM HDD                         |
| **Internet**         | Boardband internet connection         |
| **Resolution**       | 1024 x 768 minimum display resolution |

### Windows

|                      | Recommended                                    | Minimum                                |
| -------------------- | ---------------------------------------------- | -------------------------------------- |
| **Operating System** | Windows 10 1809 or above                       |
| **CPU**              | Intel® Core™ i5 or AMD Phenom™ II X3 or better | Intel® Core™ i3 or AMD Phenom™ X3 8650 |
| **GPU**              | NVIDIA® GeForce® GTX 660 or better             | NVIDIA® GeForce® GTX 460               |
| **Memory**           | 6 GB RAM                                       | 4 GB RAM                               |
| **Storage**          | 30 GB available hare drive space               |
| **Internet**         | Boardband internet connection                  |
| **Resolution**       | 1024 x 768 minimum display resolution          |

## Further reading

* [Overview](../Overview.md)
* [Use command line tool nnictl](Nnictl.md)
* [Use NNIBoard](WebUI.md)
* [Define search space](SearchSpaceSpec.md)
* [Config an experiment](ExperimentConfig.md)
* [How to run an experiment on local (with multiple GPUs)?](../TrainingService/LocalMode.md)
* [How to run an experiment on multiple machines?](../TrainingService/RemoteMachineMode.md)
* [How to run an experiment on OpenPAI?](../TrainingService/PaiMode.md)
* [How to run an experiment on Kubernetes through Kubeflow?](../TrainingService/KubeflowMode.md)
* [How to run an experiment on Kubernetes through FrameworkController?](../TrainingService/FrameworkControllerMode.md)
