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QuanluZhang authored and yds05 committed Oct 6, 2018
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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).

```
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 │ │ ... │
└────────────────────────┘ └────────────────┘
```
<p align="center">
<img src="./docs/nni_overview.png" alt="drawing" width="800"/>
</p>

## **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)
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