NVlabs / condensaLinks
Programmable Neural Network Compression
☆148Updated 3 years ago
Alternatives and similar repositories for condensa
Users that are interested in condensa are comparing it to the libraries listed below
Sorting:
- Simple Training and Deployment of Fast End-to-End Binary Networks☆157Updated 3 years ago
- Using ideas from product quantization for state-of-the-art neural network compression.☆145Updated 3 years ago
- A PyTorch implementation of "Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights"☆167Updated 5 years ago
- PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)☆126Updated 6 years ago
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 6 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…☆41Updated 6 years ago
- ☆70Updated 5 years ago
- A Pytorch implementation of Neural Network Compression (pruning, deep compression, channel pruning)☆155Updated last year
- ☆69Updated 5 years ago
- A PyTorch implementation of NASBench☆52Updated 2 years ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆113Updated 5 years ago
- MONeT framework for reducing memory consumption of DNN training☆173Updated 4 years ago
- A Re-implementation of Fixed-update Initialization☆153Updated 6 years ago
- PyProf2: PyTorch Profiling tool☆82Updated 5 years ago
- ☆213Updated 6 years ago
- Repository containing pruned models and related information☆37Updated 4 years ago
- Code for https://arxiv.org/abs/1810.04622☆141Updated 5 years ago
- On Network Design Spaces for Visual Recognition☆96Updated 5 years ago
- Discovering Neural Wirings (https://arxiv.org/abs/1906.00586)☆137Updated 5 years ago
- ☆35Updated 5 years ago
- Filter Response Normalization tested on better ImageNet baselines.☆35Updated 5 years ago
- A research library for pytorch-based neural network pruning, compression, and more.☆162Updated 2 years ago
- ☆53Updated 7 years ago
- How and why you want to make your pytorch CUDA/CPP extension with a Makefile☆172Updated 6 years ago
- [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices☆167Updated 4 years ago
- Mayo: Auto-generation of hardware-friendly deep neural networks. Dynamic Channel Pruning: Feature Boosting and Suppression.☆115Updated 5 years ago
- Official implementation of "UNAS: Differentiable Architecture Search Meets Reinforcement Learning", CVPR 2020 Oral☆61Updated last year
- Graph Transforms to Quantize and Retrain Deep Neural Nets in TensorFlow☆168Updated 5 years ago
- Path-Level Network Transformation for Efficient Architecture Search, in ICML 2018.☆112Updated 7 years ago
- All about acceleration and compression of Deep Neural Networks☆33Updated 5 years ago