NUS-HPC-AI-Lab / LARS-ImageNet-PyTorch
Accuracy 77%. Large batch deep learning optimizer LARS for ImageNet with PyTorch and ResNet, using Horovod for distribution. Optional accumulated gradient and NVIDIA DALI dataloader.
☆38Updated 3 years ago
Alternatives and similar repositories for LARS-ImageNet-PyTorch:
Users that are interested in LARS-ImageNet-PyTorch are comparing it to the libraries listed below
- PyTorch implementation of LAMB for ImageNet/ResNet-50 training☆13Updated 3 years ago
- ☆42Updated 2 years ago
- ☆202Updated 2 years ago
- ☆35Updated 3 years ago
- [NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang…☆89Updated last year
- ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training☆200Updated 2 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆89Updated 2 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- ☆16Updated 2 years ago
- Efficient reference implementations of the static & dynamic M-FAC algorithms (for pruning and optimization)☆16Updated 3 years ago
- This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).☆44Updated 2 years ago
- code for NASViT☆67Updated 3 years ago
- Pytorch implementation of our paper accepted by TPAMI 2023 — Lottery Jackpots Exist in Pre-trained Models☆34Updated last year
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆52Updated last year
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆27Updated 2 years ago
- Code for ICML 2021 submission☆34Updated 4 years ago
- ☆40Updated 3 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year
- Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint☆31Updated 3 years ago
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆33Updated last year
- Generic Neural Architecture Search via Regression (NeurIPS'21 Spotlight)☆36Updated 2 years ago
- Parameter Efficient Transfer Learning with Diff Pruning☆73Updated 4 years ago
- ☆43Updated last year
- [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…☆73Updated 2 years ago
- code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"☆104Updated 3 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- [ICLR 2021] CompOFA: Compound Once-For-All Networks For Faster Multi-Platform Deployment☆24Updated 2 years ago
- [KDD'22] Learned Token Pruning for Transformers☆95Updated 2 years ago
- Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".☆118Updated last year
- Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better perfo…☆90Updated 2 years ago