Shypd.aiThe largest open index of AI toolspytorch-pruning is an Open Source & Models tool that implements pruning for convolutional neural networks. It helps reduce model size and improve inference speed, demonstrating a 3x CPU runtime reduction and 4x model size reduction for VGG16.
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pytorch-pruning is an open-source PyTorch implementation of the paper "Pruning Convolutional Neural Networks for Resource Efficient Inference." This tool is designed to optimize deep learning models by reducing their size and improving inference speed. It achieves this by systematically removing filters from convolutional layers. The project demonstrates its effectiveness by pruning a VGG16-based classifier on a small dog/cat dataset, resulting in a significant 3x reduction in CPU runtime and a 4x reduction in model size. While currently pruning filters sequentially, the project notes that future improvements could include a single-pass pruning mechanism for greater efficiency. It also aims to support additional architectures beyond VGG, such as VGG with batch normalization.
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