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jaeho-lee avatar

jaeho-lee/layer-adaptive-sparsity

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68 estrellas·6 forks·Python·MIT·4 vistas

Layer Adaptive Sparsity

This is the official implementation of the paper: "Layerwise Sparsity for Magnitude-based Pruning", ICLR 2021.

Features

  • Weight Pruning - Magnitude-based pruning with layer-adaptive sparsity constraints.

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Preguntas frecuentes

¿Qué hace jaeho-lee/layer-adaptive-sparsity?

This is the official implementation of the paper: "Layerwise Sparsity for Magnitude-based Pruning", ICLR 2021.

¿Cuáles son las características principales de jaeho-lee/layer-adaptive-sparsity?

Las características principales de jaeho-lee/layer-adaptive-sparsity son: Weight Pruning.

¿Qué alternativas de código abierto existen para jaeho-lee/layer-adaptive-sparsity?

Las alternativas de código abierto para jaeho-lee/layer-adaptive-sparsity incluyen: tencent/pocketflow — PocketFlow is an integrated toolkit for deep learning model compression, distributed training, and mobile format… chrundle/biprop — This method identifies a binary weight or binary weight and activation subnetwork within a randomly initialized… dchiji-ntt/iterand — by Daiki Chijiwa\*, Shin’ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro Inoue. dem123456789/pruning-deep-neural-networks-from-a-sparsity-perspective — [ICLR 2023] Pruning Deep Neural Networks from a Sparsity Perspective. densoitlab/bitprune — This is the official repo for ICLR 2023 Paper "Bit-Pruning: A Sparse Multiplication-Less Dot-Product" Yusuke Sekikawa… boone891214/sanity-check-lth — Sample code use for NeurIPS 2021 paper: Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the…