Microsoft / nni
- четверг, 13 сентября 2018 г. в 00:15:49
TypeScript
An open source AutoML toolkit for neural architecture search and hyper-parameter tuning.
NNI (Neural Network Intelligence) is a toolkit to help users running 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 at different environments (e.g. local, 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 │ │ ... │
└────────────────────────┘ └────────────────┘
Install through python pip
pip3 install -v --user git+https://github.com/Microsoft/nni.git@v0.1
source ~/.bashrc
Requirements:
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 here for the GetStarted tutorial.
This project welcomes contributions and suggestions, we are constructing the contribution guidelines, stay tuned =).
We use GitHub issues for tracking requests and bugs.