Deeplite / deeplite-profilerLinks
A collection of metrics to profile a single deep learning model or compare two different deep learning models
☆27Updated 2 years ago
Alternatives and similar repositories for deeplite-profiler
Users that are interested in deeplite-profiler are comparing it to the libraries listed below
Sorting:
- Reference implementations of popular Binarized Neural Networks☆109Updated 2 weeks ago
- ☆58Updated 3 years ago
- Repository containing pruned models and related information☆38Updated 4 years ago
- A research library for pytorch-based neural network pruning, compression, and more.☆162Updated 3 years ago
- [ICLR 2020] Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks☆140Updated 5 years ago
- Using ideas from product quantization for state-of-the-art neural network compression.☆146Updated 4 years ago
- End-to-end training of sparse deep neural networks with little-to-no performance loss.☆333Updated 2 years ago
- All about acceleration and compression of Deep Neural Networks☆33Updated 6 years ago
- ☆69Updated 5 years ago
- Pruning methods for pytorch with an optimizer-like interface☆15Updated 5 years ago
- MUSCO: MUlti-Stage COmpression of neural networks☆72Updated 4 years ago
- Repository to track the progress in model compression and acceleration☆106Updated 4 years ago
- ☆22Updated 7 years ago
- Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"☆75Updated 6 years ago
- Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule☆39Updated 4 years ago
- Train neural networks with joint quantization and pruning on both weights and activations using any pytorch modules☆43Updated 3 years ago
- A highly modular PyTorch framework with a focus on Neural Architecture Search (NAS).☆23Updated 4 years ago
- A Pytorch implementation of Neural Network Compression (pruning, deep compression, channel pruning)☆158Updated last year
- A curated list of binary neural network research papers and software packages.☆28Updated 5 years ago
- 3rd place solution for NeurIPS 2019 MicroNet challenge☆37Updated 6 years ago
- Network Pruning That Matters: A Case Study on Retraining Variants (ICLR 2021)☆17Updated 4 years ago
- MONeT framework for reducing memory consumption of DNN training☆174Updated 4 years ago
- The collection of training tricks of binarized neural networks.☆72Updated 4 years ago
- A PyTorch implementation of "Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights"☆167Updated 5 years ago
- ☆17Updated 5 years ago
- papers about model compression☆166Updated 2 years ago
- Implémentation of the article **Deep Learning CUDA Memory Usage and Pytorch optimization tricks**☆43Updated 6 years ago
- Minimal implementation of adaptive gradient clipping (https://arxiv.org/abs/2102.06171) in TensorFlow 2.☆86Updated 4 years ago
- Highly optimized inference engine for Binarized Neural Networks☆251Updated this week
- PyTorch Pruning Example☆50Updated 3 years ago