lgalke / torch-pruning
Pruning methods for pytorch with an optimizer-like interface
☆15Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for torch-pruning
- Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"☆73Updated 4 years ago
- [ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vi…☆30Updated 8 months ago
- Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing …☆49Updated 2 years ago
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 5 years ago
- All about acceleration and compression of Deep Neural Networks☆33Updated 5 years ago
- ☆53Updated 5 years ago
- ☆70Updated 4 years ago
- Code for High-Capacity Expert Binary Networks (ICLR 2021).☆27Updated 2 years ago
- Post-training sparsity-aware quantization☆33Updated last year
- This repository provides code source used in the paper: A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off☆13Updated 5 years ago
- This is a PyTorch implementation of the Scalpel. Node pruning for five benchmark networks and SIMD-aware weight pruning for LeNet-300-100…☆39Updated 6 years ago
- DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures☆31Updated 4 years ago
- Official implementation of Neurips 2020 "Sparse Weight Activation Training" paper.☆26Updated 3 years ago
- Codes for Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit?☆31Updated 5 years ago
- Repository containing pruned models and related information☆36Updated 3 years ago
- Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule☆37Updated 2 years ago
- A Hackable Quantization Library for PyTorch☆19Updated 3 years ago
- ☆22Updated 6 years ago
- Official PyTorch Implementation of "Learning Architectures for Binary Networks" (ECCV2020)☆26Updated 3 years ago
- ProxQuant: Quantized Neural Networks via Proximal Operators☆28Updated 5 years ago
- Codes for Accepted Paper : "MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization" in NeurIPS 2019☆54Updated 4 years ago
- ☆11Updated 2 years ago
- Successfully training approximations to full-rank matrices for efficiency in deep learning.☆16Updated 3 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆88Updated last year
- PyTorch implementation of Towards Efficient Training for Neural Network Quantization☆15Updated 4 years ago
- The collection of training tricks of binarized neural networks.☆72Updated 3 years ago
- Class Project for 18663 - Implementation of FBNet (Hardware-Aware DNAS)☆33Updated 5 years ago
- ☆42Updated 9 months ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆100Updated 4 years ago