This repository implements MSDNet (Multi-Scale Dense Network), a deep learning architecture for efficient image classification. The network supports two inference modes: anytime prediction where classification confidence improves progressively, and batch-budget inference where computational resources are allocated dynamically based on example difficulty. The architecture uses multi-scale dense connections across classification layers to enable early exits for easier images.