Python Large-steps-pytorch Resources

PyTorch-LBFGS: A PyTorch Implementation of L-BFGS Authors: Hao-Jun Michael Shi (Northwestern University) and Dheevatsa Mudigere (Facebook) What is it?

geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur

lookahead optimizer for pytorch PyTorch implement of Lookahead Optimizer: k steps forward, 1 step back Usage: base_opt = torch.optim.Adam(model.parame

functorch is a prototype of JAX-like composable function transforms for PyTorch.

docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.

GluonMM is a library of transformer models for computer vision and multi-modality research. It contains reference implementations of widely adopted baseline models and also research work from Amazon Research.

Pytorch Geometric Tutorials

BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

Bunch of optimizer implementations in PyTorch

Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]

BERT Got a Date: Introducing Transformers to Temporal Tagging Satya Almasian*, Dennis Aumiller*, and Michael Gertz Heidelberg University Contact us vi

RE2 This is a pytorch implementation of the ACL 2019 paper "Simple and Effective Text Matching with Richer Alignment Features". The original Tensorflo

glow-pytorch PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions (https://arxiv.org/abs/1807.03039) Usage: python train.p

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

VoiceFilter Note from Seung-won (2020.10.25) Hi everyone! It's Seung-won from MINDs Lab, Inc. It's been a long time since I've released this open-sour

GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten

PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t

Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte

GPT2-Pytorch with Text-Generator Better Language Models and Their Implications Our model, called GPT-2 (a successor to GPT), was trained simply to pre

XLM NEW: Added XLM-R model. PyTorch original implementation of Cross-lingual Language Model Pretraining. Includes: Monolingual language model pretrain

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context This repository contains the code in both PyTorch and TensorFlow for our paper

WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install

English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se

transducer A Fast Sequence Transducer Implementation with PyTorch Bindings. The corresponding publication is Sequence Transduction with Recurrent Neur

Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR

AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O

Tacotron 2 (without wavenet) PyTorch implementation of Natural TTS Synthesis By Conditioning Wavenet On Mel Spectrogram Predictions. This implementati

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

Non-Autoregressive Transformer Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K.

Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations

Implementation of Deep-Forecast using PyTorch Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting Adapted from original implementation Setu

A Pytorch Implementation of the Transformer: Attention Is All You Need Our implementation is largely based on Tensorflow implementation Requirements N

StarGAN - Official PyTorch Implementation ***** New: StarGAN v2 is available at https://github.com/clovaai/stargan-v2 ***** This repository provides t

CompactBilinearPooling-Pytorch A Pytorch Implementation for Compact Bilinear Pooling. Adapted from tensorflow_compact_bilinear_pooling Prerequisites I

Compact Bilinear Pooling for PyTorch. This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch. This

PyTorch SGNS Word2Vec's SkipGramNegativeSampling in Python. Yet another but quite general negative sampling loss implemented in PyTorch. It can be use

tacotron_pytorch PyTorch implementation of Tacotron speech synthesis model. Inspired from keithito/tacotron. Currently not as much good speech quality

2017 VQA Challenge Winner (CVPR'17 Workshop) pytorch implementation of Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challeng

Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https

WIT (Wikipedia-based Image Text) Dataset is a large multimodal multilingual dataset comprising 37M+ image-text sets with 11M+ unique images across 100+ languages.

PyTorch implementations of normalizing flow and its variants.

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

Silero Models: pre-trained speech-to-text, text-to-speech models and benchmarks made embarrassingly simple

DeepLabv3+：Encoder-Decoder with Atrous Separable Convolution语义分割模型在Pytorch当中的实现 目录 性能情况 Performance 所需环境 Environment 注意事项 Attention 文件下载 Download 训练步骤

An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation (ICCV 2021) Introduction This is an official pytorch implemen

Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized

Dynamic Attentive Graph Learning for Image Restoration This repository is for GATIR introduced in the following paper: Chong Mou, Jian Zhang, Zhuoyuan

Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train

Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V

PyTorch Seq2Seq Intent Parsing Reframing intent parsing as a human - machine translation task. Work in progress successor to torch-seq2seq-intent-pars

PointNet.pytorch This repo is implementation for PointNet in pytorch. The model is in pointnet/model.py. It is teste

pytorch-deeplab-resnet DeepLab resnet v2 model implementation in pytorch. The architecture of deepLab-ResNet has been replicated exactly as it is from

VIN: Value Iteration Networks A quick thank you A few others have released amazing related work which helped inspire and improve my own implementation

Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea

CycleGAN and pix2pix in PyTorch New: Please check out contrastive-unpaired-translation (CUT), our new unpaired image-to-image translation model that e

Deep Reinforcement Learning with pytorch & visdom Sample testings of trained agents (DQN on Breakout, A3C on Pong, DoubleDQN on CartPole, continuous A

ResNeXt.pytorch Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch. Tried on pytorch 1.6 Trains on Cifar

Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati

BEGAN in PyTorch This project is still in progress. If you are looking for the working code, use BEGAN-tensorflow. Requirements Python 2.7 Pillow tqdm

PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple

SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If

Attention Transfer PyTorch code for "Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Tran

YOLOv2 in PyTorch NOTE: This project is no longer maintained and may not compatible with the newest pytorch (after 0.4.0). This is a PyTorch implement

VIN: Value Iteration Networks This is an implementation of Value Iteration Networks (VIN) in PyTorch to reproduce the results.(TensorFlow version) Key

PyTorch Tutorials This tutorial is no longer maintained. Please use the official version: https://pytorch.org/tutorials/advanced/neural_style_tutorial

FastNeuralStyle by Pytorch Fast Neural Style for Image Style Transform by Pytorch This is famous Fast Neural Style of Paper Perceptual Losses for Real

PytorchNeuralStyleTransfer Code to run Neural Style Transfer from our paper Image Style Transfer Using Convolutional Neural Networks. Also includes co

fast-neural-style 🌇 🚀 NOTICE: This codebase is no longer maintained, please use the codebase from pytorch examples repository available at pytorch/e

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.

OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc

Pytorch Squeeznet Pytorch implementation of Squeezenet model as described in https://arxiv.org/abs/1602.07360 on cifar-10 Data. The definition of Sque

FlowNetPytorch Pytorch implementation of FlowNet by Dosovitskiy et al. This repository is a torch implementation of FlowNet, by Alexey Dosovitskiy et

DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p

Faster RCNN with PyTorch Note: I re-implemented faster rcnn in this project when I started learning PyTorch. Then I use PyTorch in all of my projects.

nninit Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin. ##Update This repo has been

A PyTorch Implementation of DenseNet This is a PyTorch implementation of the DenseNet-BC architecture as described in the paper Densely Connected Conv

Asynchronous Advantage Actor-Critic in PyTorch This is PyTorch implementation of A3C as described in Asynchronous Methods for Deep Reinforcement Learn

Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha

deepspeech.pytorch Implementation of DeepSpeech2 for PyTorch using PyTorch Lightning. The repo supports training/testing and inference using the DeepS

Introduction This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch. Kim's implementation of t

AnimeGAN A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing. Randomly Generated Images The images are

DNC pytorch This is a Pytorch implementation of DeepMind's Differentiable Neural Computer (DNC) architecture introduced in their recent Nature paper:

PyTorch Highway Networks Highway networks implemented in PyTorch. Just the MNIST example from PyTorch hacked to work with Highway layers. Todo Make th

Wide Residual Networks (WideResNets) in PyTorch WideResNets for CIFAR10/100 implemented in PyTorch. This implementation requires less GPU memory than

pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm

A PyTorch implementation of V-Net Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Imag

An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin

pytoch-dqn This project is pytorch implementation of Human-level control through deep reinforcement learning and I also plan to implement the followin

PiWiSe Pixel-wise segmentation on the VOC2012 dataset using pytorch. FCN SegNet PSPNet UNet RefineNet For a more complete implementation of segmentati

Evolution Strategies This is a PyTorch implementation of Evolution Strategies. Requirements Python 3.5, PyTorch = 0.2.0, numpy, gym, universe, cv2 Wh

DiscoGAN in PyTorch PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. * All samples in READM

SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragom

pix2pix-pytorch PyTorch implementation of Image-to-Image Translation Using Conditional Adversarial Networks. Based on pix2pix by Phillip Isola et al.

Task-based End-to-end Model Learning in Stochastic Optimization This repository is by Priya L. Donti, Brandon Amos, and J. Zico Kolter and contains th

Pytorch Time Delayed NN Time Delayed NN implemented in PyTorch. Usage kernels = [(1, 25), (2, 50), (3, 75), (4, 100), (5, 125), (6, 150)] tdnn = TDNN

Pytorch Recurrent Variational Autoencoder Model: This is the implementation of Samuel Bowman's Generating Sentences from a Continuous Space with Kim's

Pytorch Negative Sampling Loss Negative Sampling Loss implemented in PyTorch. Usage neg_loss = NEG_loss(num_classes, embedding_size) optimizer =