MLX-Cluster Documentation

Welcome to the mlx-cluster documentation! This library provides high-performance graph algorithms optimized for Apple's MLX framework, including random walks and neighbor sampling.

Installation and Quickstart

• Installation
  • Requirements
  • Install from PyPI
  • Install from Source
  • Verify Installation
  • Troubleshooting
    • ImportError: No module named 'mlx'
    • Performance Issues
• Quick Start
  • Random Walks
  • Biased Random Walks (Node2Vec style)
  • Neighbor Sampling
  • Key Features

Functions and APIs

• API Reference
  • random_walk()
  • rejection_sampling()
  • neighbor_sample()

Indices and tables

• Index

• Search Page