论文标题
以平衡的性能和修剪速度进行最佳修剪修剪
Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed
论文作者
论文摘要
过滤器修剪引起了更多的关注，因为资源约束平台需要更紧凑的模型进行部署。但是，当前的修剪方法遭受了一次性方法的劣质性能，或者迭代训练方法的昂贵时间成本。在本文中，我们为性能和修剪速度提出了一种平衡的过滤器修剪方法。基于滤波器的重要性标准，我们的方法能够在预设损耗变化时修剪具有近似层最佳修剪率的层。该网络以层次的方式修剪，而无需耗时的修剪ret式迭代。如果给出了整个网络的预定义的修剪率，我们还引入了一种方法，以快速收敛速度找到相应的损耗变化阈值。此外，我们提出了层组修剪和通道选择机制，以用于连接短的网络中的通道对齐。所提出的修剪方法广泛适用于通用架构，除最终的微调外，不涉及任何其他培训。全面的实验表明，我们的方法的表现优于许多最先进的方法。
Filter pruning has drawn more attention since resource constrained platform requires more compact model for deployment. However, current pruning methods suffer either from the inferior performance of one-shot methods, or the expensive time cost of iterative training methods. In this paper, we propose a balanced filter pruning method for both performance and pruning speed. Based on the filter importance criteria, our method is able to prune a layer with approximate layer-wise optimal pruning rate at preset loss variation. The network is pruned in the layer-wise way without the time consuming prune-retrain iteration. If a pre-defined pruning rate for the entire network is given, we also introduce a method to find the corresponding loss variation threshold with fast converging speed. Moreover, we propose the layer group pruning and channel selection mechanism for channel alignment in network with short connections. The proposed pruning method is widely applicable to common architectures and does not involve any additional training except the final fine-tuning. Comprehensive experiments show that our method outperforms many state-of-the-art approaches.
