Neural Network Intelligence

NNI (Neural Network Intelligence) is a toolkit to help users run automated machine learning experiments. The tool dispatches and runs trial jobs that generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different environments (e.g. local machine, remote servers and cloud).

            AutoML experiment                                 Training Services
┌────────┐        ┌────────────────────────┐                  ┌────────────────┐
│ nnictl │ ─────> │  nni_manager           │                  │ Local Machine  │
└────────┘        │    sdk/tuner           │                  └────────────────┘
                  │      hyperopt_tuner    │
                  │      evolution_tuner   │    trial jobs    ┌────────────────┐
                  │      ...               │     ────────>    │ Remote Servers │          
                  ├────────────────────────┤                  └────────────────┘
                  │  trial job source code │                  
                  │    sdk/annotation      │                  ┌────────────────┐
                  ├────────────────────────┤                  │ Yarn,K8s,      │
                  │  nni_board             │                  │ ...            │
                  └────────────────────────┘                  └────────────────┘

Who should consider using NNI

• You want to try different AutoML algorithms for your training code (model) at local
• You want to run AutoML trial jobs in different environments to speed up search (e.g. remote servers and cloud)
• As a researcher and data scientist, you want to implement your own AutoML algorithms and compare with other algorithms
• As a ML platform owner, you want to support AutoML in your platform

Getting Started with NNI

Installation

Install through python pip. (the current version only supports linux, nni on ubuntu 16.04 or newer has been well tested)

• requirements: python >= 3.5, git, wget

pip3 install -v --user git+https://github.com/Microsoft/nni.git@v0.1
source ~/.bashrc

Quick start: run an experiment at local

Requirements:

• NNI installed on your local machine
• tensorflow installed

Run the following command to create an experiment for [mnist]

    nnictl create --config ~/nni/examples/trials/mnist-annotation/config.yml

This command will start an experiment and a WebUI. The WebUI endpoint will be shown in the output of this command (for example, http://localhost:8080). Open this URL in your browser. You can analyze your experiment through WebUI, or browse trials' tensorboard.

Please refer to Get Started Tutorial for more detailed information.

More tutorials

• How to write a trial running on NNI (Mnist as an example)?
• Tutorial of NNI python annotation.
• Tuners supported by NNI.
• How to enable early stop (i.e. assessor) in an experiment?
• How to run an experiment on multiple machines?
• How to write a customized tuner?
• How to write a customized assessor?
• How to resume an experiment?
• Tutorial of the command tool nnictl.

Contributing

This project welcomes contributions and suggestions, we are constructing the contribution guidelines, stay tuned =).

We use GitHub issues for tracking requests and bugs.