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Discrete Neural Algorithmic Reasoning

This repository contains the code to reproduce the experiments from "Discrete Neural Algorithmic Reasoning" paper.

Setup

Before running the source code, make sure to install the project dependencies:

pip install -r requirements.txt

Main experiments

Algorithms

  • Breadth-first search
  • Depth-first search
  • Minimum spanning tree (Prim's algorithm)
  • Maximum Independent Set (randomized)
  • Shortest paths (Dijkstra's algorithm)

Train a single-task model

python train.py --config_path
python eval.py

Hints generation

You can find hints generation procedures for each algorithm in generate_data.py.