torchsystem 0.2.1

An IA training system, based on domain driven design and an event driven architecture, created on top of the pybondi library.

torch-system

An IA training system, created using domain driven design and an event driven architecture.

Installation

Make sure you have a pytorch distribution installed. If you don't, go to the official website and follow the instructions.

Then, you can install the package using pip:

pip install torchsystem

Soon I will be adding the package to conda-forge when the package is more stable.

Introduction

Machine learning systems are getting more and more complex, and the need for a more organized and structured way to build and maintain them is becoming more evident. Training a neural network requires to define a cluster of related objects that should be treated as a single unit, this defines an aggregate. The training process mutates the state of the aggregate producing data that should be stored alongside the state of the aggregate in a transactional way. This establishes a clear bounded context that should be modeled using Domain Driven Design (DDD) principles.

The torch-system is a framework based on DDD and Event Driven Architecture (EDA) principles, using the pybondi library. It aims to provide a way to model complex machine models using aggregates and training flows using commands and events, and persist states and results using the repositories, the unit of work pattern and pub/sub.

It also provides out of the box tools for managing the training process, model compilation, centralized settings with enviroments variables using pydantic-settings, automatic parameter tracking using mlregistry.