Vega ver1.2.0 released:
Introduction
Vega is an AutoML algorithm tool chain developed by Noah's Ark Laboratory, the main features are as follows:
- Full pipeline capailities: The AutoML capabilities cover key functions such as Hyperparameter Optimization, Data Augmentation, Network Architecture Search (NAS), Model Compression, and Fully Train. These functions are highly decoupled and can be configured as required, construct a complete pipeline.
- Industry-leading AutoML algorithms: provides Noah's Ark Laboratory's self-developed industry-leading algorithm (Benchmark) and Model Zoo to download the State-of-the-art (SOTA) model.
- Fine-grained network search space: The network search space can be freely defined, and rich network architecture parameters are provided for use in the search space. The network architecture parameters and model training hyperparameters can be searched at the same time, and the search space can be applied to Pytorch, TensorFlow and MindSpore.
- High-concurrency neural network training capability: Provides high-performance trainers to accelerate model training and evaluation.
- Multi-Backend: PyTorch, TensorFlow(trial), MindSpore(coming soon).
Installation
Install Vega and the open source softwares that Vega depends on:
pip3 install noah-vega
python3 -m vega.tools.install_pkgs
Cooperation and contribution
Welcome to use Vega. If you have any questions, ask for help, fix bugs, contribute algorithms, or improve documents, submit the issue in the community. We will reply to and communicate with you in a timely manner. Welcome to join our QQ chatroom (Chinese): 833345709.