Gradient Checkpointing

2000년 도입 · 논문 14편에서 사용

Gradient Checkpointing is a method used for reducing the memory footprint when training deep neural networks, at the cost of having a small increase in computation time.

출처: Training Deep Nets with Sublinear Memory Cost

소개 논문: Training Deep Nets with Sublinear Memory Cost