Structural pruning has emerged as a promising approach for producing more efficient models. Nevertheless, the community suffers from a lack of standardized benchmarks and metrics, leaving the progress in this area not fully comprehended.To fill this gap, we present the first comprehensive benchmark, termed PruningBench, for structural pruning. PruningBench showcases the following three characteristics: 1) PruningBench employs a unified and consistent framework for evaluating the effectiveness of diverse structural pruning techniques; 2) PruningBench systematically evaluates 16 existing pruning methods, encompassing a wide array of models (e.g., CNNs and ViTs) and tasks (e.g., classification and detection); 3) PruningBench provides easily implementable interfaces to facilitate the implementation of future pruning methods, and enables the subsequent researchers to incorporate their work into our leaderboards. We provide an online pruning platform http://pruning.vipazoo.cn for customizing pruning tasks and reproducing all results in this paper. Leaderboard results can be available on https://github.com/HollyLee2000/PruningBench.

翻译：结构化剪枝已成为一种生产更高效模型的有前景的方法。然而，该领域缺乏标准化的基准测试和评估指标，导致该领域的进展未能被充分理解。为填补这一空白，我们提出了首个用于结构化剪枝的综合性基准测试，命名为 PruningBench。PruningBench 展现出以下三个特征：1) PruningBench 采用统一且一致的框架来评估多种结构化剪枝技术的有效性；2) PruningBench 系统性地评估了 16 种现有剪枝方法，涵盖了广泛的模型（例如 CNNs 和 ViTs）和任务（例如分类和检测）；3) PruningBench 提供了易于实现的接口，以促进未来剪枝方法的实现，并使后续研究人员能够将其工作纳入我们的排行榜。我们提供了一个在线剪枝平台 http://pruning.vipazoo.cn，用于定制剪枝任务和复现本文中的所有结果。排行榜结果可在 https://github.com/HollyLee2000/PruningBench 上获取。