AutoSculpt models DNNs as graphs, embeds pruning patterns, and uses deep reinforcement learning to reach up to 90% pruning and 18% better FLOPs reduction than baselines on ResNet, MobileNet, VGG, and Vision Transformers.
Movement pruning: Adaptive sparsity by fine-tuning.Advances in Neu- ral Information Processing Systems, 33:20378–20389, 2020
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AutoSculpt: A Pattern-based Model Auto-pruning Framework Using Reinforcement Learning and Graph Learning
AutoSculpt models DNNs as graphs, embeds pruning patterns, and uses deep reinforcement learning to reach up to 90% pruning and 18% better FLOPs reduction than baselines on ResNet, MobileNet, VGG, and Vision Transformers.