======================
Antgo
======================
.. image:: https://raw.githubusercontent.com/jianzfb/antgo/master/antgo/resource/static/card.png
:alt: Antgo
Target
----------------------
Antgo is a machine learning experiment manage platform, which has been integrated deeply with MLTalker.
Antgo provides a one-stop model development, deployment, analyze, auto-optimize and manage environment.
Installation
----------------------
1. (RECOMMENDED) use docker
`docker environment <docker/README.md>`__.
2. install from pip
pip install antgo
3. install from source
1. git clone https://github.com/jianzfb/antgo.git
2. cd antgo
3. pip install -r requirements.txt
4. python setup.py build_ext install
Register
-----------------------
Register in `MLTalker <http://www.mltalker.com/>`__.
.. image:: https://raw.githubusercontent.com/jianzfb/antgo/master/antgo/resource/static/register.png
:alt: Antgo and MLTalker
All user experiment records would be managed by MLTalker in user's personal page.
Quick Example
-----------------------
1.step create mvp code(cifar10 classification task)
antgo create mvp --name=cifar10
2.step start training process
python3 ./cifar10/main.py --exp=cifar10 --gpu-id=0 --process=train
3.step check training log
in ./output/cifar10/output/checkpoint
4.step export onnx model
python3 ./cifar10/main.py --exp=cifar10 --checkpoint=./output/cifar10/output/checkpoint/epoch_1500.pth --process=export
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