Younger-Logics-IR

Younger - Logics - Intermediate Representation

Younger-Logics-IR is a submodule of the Younger project designed to construct a unified Intermediate Representation (IR) for abstracting and describing the logic structure of deep learning models. It supports extracting model information from various frameworks (e.g., PyTorch and ONNX) and abstracts the operators and data flows into a unified graph structure. Younger-Logics-IR enables framework-agnostic model analysis, conversion, and optimization, serving as a foundational tool for deep learning workflows.

For the Use of Assorts

Requirements

Graphviz must be installed:

• Mac

brew install graphviz

• Debian/Ubuntu

sudo apt install graphviz

• Conda

conda install conda-forge::python-graphviz