PyTorch implementation of Learning to learn by gradient descent by gradient descent.
python main.py
AdaBound An optimizer that trains as fast as Adam and as good as SGD, for developing state-of-the-art deep learning models on a wide variety of popula
TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers (e.g., ViT, BERT and
Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st
High-fidelity performance metrics for generative models in PyTorch
Use Jax functions in Pytorch with DLPack
farabio is a minimal PyTorch toolkit for out-of-the-box deep learning support in biomedical imaging. For further information, see Wikis and Docs.
Example implementation of the L0 regularization method described at Learning Sparse Neural Networks through L0 regularization, Christos Louizos, Max W
Tacotron 2 (without wavenet) PyTorch implementation of Natural TTS Synthesis By Conditioning Wavenet On Mel Spectrogram Predictions. This implementati
Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST
PyTorch misc Collection of code snippets I've written for the PyTorch discussion board. All scripts were testes using the PyTorch 1.0 preview and torc
PyTorch-LBFGS: A PyTorch Implementation of L-BFGS Authors: Hao-Jun Michael Shi (Northwestern University) and Dheevatsa Mudigere (Facebook) What is it?
(Generic) EfficientNets for PyTorch A 'generic' implementation of EfficientNet, MixNet, MobileNetV3, etc. that covers most of the compute/parameter ef
Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers (BMVC 2021) Zai Shi*, Zhao Meng*, Yiran Xing, Yunpu Ma, Roger Wattenhofe
News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which
This is an differentiable pytorch implementation of SIFT patch descriptor. It is very slow for describing one patch, but quite fast for batch. It can
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli
Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
PyTorch Sparse This package consists of a small extension library of optimized sparse matrix operations with autograd support. This package currently
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