====================== 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