Metadata-Version: 2.1
Name: moai-mdk
Version: 0.1.0a2
Summary: moai: Accelerated, Flexible, Modular, Reproducible, Insightful AI
Home-page: https://github.com/ai-in-motion/moai
Author: AI-in-Motion Team
Author-email: moai@ai-in-motion.dev
License: UNKNOWN
Project-URL: Documentation, https://moai.readthedocs.io/en/latest/
Project-URL: Source, https://github.com/ai-in-motion/moai
Keywords: AI,workflow,framework,PyTorch
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
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# _moai_ - Accelerating modern data-driven workflows

[![Documentation Status](https://readthedocs.org/projects/moai/badge/?version=latest)](https://moai.readthedocs.io/en/latest/?badge=latest)

**_moai_** is a [PyTorch](https://pytorch.org/)-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](#Dependencies), it can be readily used to improve most AI workflows. To explore _moai_, simply [install](#Installation) the package and follow the [examples](https://github.com/ai-in-motion/moai/tree/master/conf/examples), having in mind that it is in early development _alpha_ version, thus new features will be available soon.

![Overview](./docs/diagrams/overview_light.svg)

# 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 facilitates 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.

# Dependencies

_moai_ stands on the shoulders of giants as it relies on various large scale open-source projects:

1. [PyTorch](https://pytorch.org/) `> 1.7.0` needs to be customly installed on your system/environment.
2. [Lightning](https://www.pytorchlightning.ai/) `> 1.0.0` is the currently supported training backend.
3. [Hydra](https://hydra.cc/) `> 1.0` drives _moai_'s DML that sets up model configurations, and additionally manages the hyper-parameter complexity of modern AI models.
4. [Visdom](https://github.com/fossasia/visdom) is the currently supported visualization engine.
5. [HiPlot](https://github.com/facebookresearch/hiplot) drives _moai_'s inter-model analytics.
6. [Various PyTorch Open Source Projects](#Dependencies):

    - [Kornia](https://github.com/kornia/kornia) for a set of computer vision operations integrated as _moai_ monads.
    - [Albumentations](https://github.com/albumentations-team/albumentations) as the currently supported data augmentation framework.

7. [The Wider Open Source Community](www.github.com) that conducts accessible R&D and drives most of _moai_'s capabilities.

8. [A set of awesome Python libraries](#Dependencies) as found in our [**requirements**](https://github.com/ai-in-motion/moai/tree/master/requirements.txt) file.

# Installation

## Package
To install the currently **released** _moai_ version package run:

`pip install moai-mdk`

## Source
Download the master branch source and install it by opening a command line on the source directory and running:

`pip install .` or `pip install -e .` (in editable form)

# Getting Started

Visit the [**documentation**](#) site to learn about _moai_'s DML and the overall MDK design and usage.

Examples can be found at [**conf/examples**](https://github.com/ai-in-motion/moai/tree/main/moai/conf/examples). 

# Licence

_moai_ is Apache 2.0 licenced, as found in the corresponding [LICENCE](https://github.com/ai-in-motion/moai/blob/main/LICENSE) file.

However, some code integrated from external projects may carry their own licences.

# Citation
If you use _moai_ in your R&D workflows or find its code useful please consider citing:

```
@misc{moai,
    title = {{\textit{moai}: Accelerating modern data-driven workflows}},
    year = {2021},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/ai-in-motion/moai}},
}
```

# Contact

Either use the:

- [GitHub issue tracker](https://github.com/ai-in-motion/moai/issues), or,
- send an email to [moai `at` ai-in-motion `dot` dev](mailto:moai@ai-in-motion.dev)


