moai

moai is a PyTorch-based AI Model Development Kit (MDK) that aims to improve data-driven model workflows, design and understanding. Since it is based on established open-source packages, it can be readily used to improve most AI workflows. To explore moai, simply install the package and follow the examples, having in mind that it is in early development alpha version, thus new features will be available soon.

Features & Design Goals

Modularity via Monads: Use moai’s existing pool of modular model building blocks. Reproducibility via Configuration: moai manages the hyper-parameter sensitive AI R&D workflows via its built-in configuration-based design. Productivity via Minimizing Coding: moai offers a data-driven domain modelling language (DML) that can facilitate quick & easy model design. Extensibility via Plugins: Easily integrate external code using moai’s built-in metaprogramming and external code integration. Understanding via Analysis: moai supports inter-model performance and design aggregation actions to consolidate knowledge between models and query differences.