Skip to main content

Neural Network Intelligence package

Project description


MIT licensed Build Status Issues Bugs Pull Requests Version Join the chat at

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


Who should consider using NNI

  • Those who want to try different AutoML algorithms in their training code (model) at their local machine.
  • Those who want to run AutoML trial jobs in different environments to speed up search (e.g. remote servers and cloud).
  • Researchers and data scientists who want to implement their own AutoML algorithms and compare it with other algorithms.
  • ML Platform owners who want to support AutoML in their platform.

Install & Verify

Install through pip

  • We only support Linux in current stage, Ubuntu 16.04 or higher are tested and supported. Simply run the following pip install in an environment that has python >= 3.5.
    python3 -m pip install --user --upgrade nni

Note: If you are in docker container (as root), please remove --user from the installation command.

Install through source code

  • We only support Linux (Ubuntu 16.04 or higher) in our current stage.
  • Run the following commands in an environment that has python >= 3.5, git and wget.
    git clone -b v0.3.4
    cd nni	

Verify install

The following example is an experiment built on TensorFlow. Make sure you have TensorFlow installed before running it.

  • Download the examples via clone the source code.
    git clone -b v0.3.4
  • Run the mnist example.
    nnictl create --config nni/examples/trials/mnist/config.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.
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:

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 log stderr             show stderr log content
4. nnictl log stdout             show stdout log content
5. nnictl stop                   stop an experiment
6. nnictl trial kill             kill a trial job by id
7. 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 are more Web UI pages.
drawing drawing


How to



This project welcomes contributions and suggestions, we use GitHub issues for tracking requests and bugs.

Issues with the good first issue label are simple and easy-to-start ones that we recommend new contributors to start with.

To set up environment for NNI development, refer to the instruction: Set up NNI developer environment

Before start coding, review and get familiar with the NNI Code Contribution Guideline: Contributing

We are in construction of the instruction for How to Debug, you are also welcome to contribute questions or suggestions on this area.


The entire codebase is under MIT license

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release. See tutorial on generating distribution archives.

Built Distribution

nni_yds-0.3.7-py3-none-any.whl (27.5 MB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page