An open source AutoML toolkit for neural architecture search and hyper-parameter tuning.

10 months after

Neural Network Intelligence

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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).


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

Install & Verify

pip install

  • 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, git and wget.
    python3 -m pip install -v --user git+https://github.com/Microsoft/[email protected]
    source ~/.bashrc

verify install

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

    nnictl create --config ~/nni/examples/trials/mnist/config.yml
  • In the command terminal, waiting for the message Info: Start experiment success! which indicates your experiment had been successfully started. You are able to explore the experiment using the Web UI url.

    Info: Checking experiment...
    Info: Starting experiment...
    Info: Checking web ui...
    Info: Starting web ui...
    Info: Starting web ui success!
  • Info: Web UI url:

  • Info: Start experiment success! The experiment id is LrNK4hae, and the restful server post is 51188.



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

We use GitHub issues for tracking requests and bugs.


The entire codebase is under MIT license

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