https://github.com/bharathgs/Awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Awesome-Pytorch-list

Pytorch & related libraries

1. pytorch : Tensors and Dynamic neural networks in Python with strong GPU acceleration.
2. pytorch extras : Some extra features for pytorch.
3. functional zoo : PyTorch, unlike lua torch, has autograd in it's core, so using modular structure of torch.nn modules is not necessary, one can easily allocate needed Variables and write a function that utilizes them, which is sometimes more convenient. This repo contains model definitions in this functional way, with pretrained weights for some models.
4. torch-sampling : This package provides a set of transforms and data structures for sampling from in-memory or out-of-memory data.
5. torchcraft-py : Python wrapper for TorchCraft, a bridge between Torch and StarCraft for AI research.
6. aorun : Aorun intend to be a Keras with PyTorch as backend.
7. logger : A simple logger for experiments.
8. PyTorch-docset : PyTorch docset! use with Dash, Zeal, Velocity, or LovelyDocs.
9. pytorch vision : Datasets, Transforms and Models specific to Computer Vision.
10. pytorch text : Torch text related contents.
11. convert_torch_to_pytorch : Convert torch t7 model to pytorch model and source.

Tutorials & examples

1. Practical Pytorch : Tutorials explaining different RNN models
2. DeepLearningForNLPInPytorch : An IPython Notebook tutorial on deep learning, with an emphasis on Natural Language Processing.
3. pytorch-tutorial : tutorial for researchers to learn deep learning with pytorch.
4. pytorch-exercises : pytorch-exercises collection.
5. pytorch tutorials : Various pytorch tutorials.
6. pytorch examples : A repository showcasing examples of using pytorch
7. pytorch practice : Some example scripts on pytorch.
8. pytorch mini tutorials : Minimal tutorials for PyTorch adapted from Alec Radford's Theano tutorials.
9. pytorch text classification : A simple implementation of CNN based text classification in Pytorch
10. cats vs dogs : Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition. Currently #27 (0.05074) on the leaderboard.
11. convnet : This is a complete training example for Deep Convolutional Networks on various datasets (ImageNet, Cifar10, Cifar100, MNIST).
12. pytorch-generative-adversarial-networks : simple generative adversarial network (GAN) using PyTorch.
13. pytorch containers : This repository aims to help former Torchies more seamlessly transition to the "Containerless" world of PyTorch by providing a list of PyTorch implementations of Torch Table Layers.
14. T-SNE in pytorch : t-SNE experiments in pytorch
15. AAE_pytorch : Adversarial Autoencoders (with Pytorch).

Paper implementations

1. google_evolution : This implements one of result networks from Large-scale evolution of image classifiers by Esteban Real, et. al.
2. pyscatwave : Fast Scattering Transform with CuPy/PyTorch,read the paper here
3. scalingscattering : Scaling The Scattering Transform : Deep Hybrid Networks.
4. deep-auto-punctuation : a pytorch implementation of auto-punctuation learned character by character.
5. Realtime_Multi-Person_Pose_Estimation : This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here .
6. PyTorch-value-iteration-networks : PyTorch implementation of the Value Iteration Networks (NIPS '16) paper
7. pytorch_Highway : Highway network implemented in pytorch.
8. pytorch_NEG_loss : NEG loss implemented in pytorch.
9. pytorch_RVAE : Recurrent Variational Autoencoder that generates sequential data implemented in pytorch.
10. pytorch_TDNN : Time Delayed NN implemented in pytorch.
11. eve.pytorch : An implementation of Eve Optimizer, proposed in Imploving Stochastic Gradient Descent with Feedback, Koushik and Hayashi, 2016.
12. e2e-model-learning : Task-based end-to-end model learning.
13. pix2pix-pytorch : PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".
14. Single Shot MultiBox Detector : A PyTorch Implementation of Single Shot MultiBox Detector.
15. DiscoGAN: PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
16. official DiscoGAN implementation : Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks".
17. pytorch-es : This is a PyTorch implementation of Evolution Strategies .
18. piwise : Pixel-wise segmentation on VOC2012 dataset using pytorch.
19. pytorch-dqn : Deep Q-Learning Network in pytorch.
20. neuraltalk2-pytorch : image captioning model in pytorch(finetunable cnn in branch with_finetune)
21. vnet.pytorch : A Pytorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation.
22. pytorch-fcn : PyTorch implementation of Fully Convolutional Networks.
23. WideResNets : WideResNets for CIFAR10/100 implemented in PyTorch. This implementation requires less GPU memory than what is required by the official Torch implementation: https://github.com/szagoruyko/wide-residual-networks .
24. pytorch_highway_networks : Highway networks implemented in PyTorch.
25. pytorch-NeuCom : Pytorch implementation of DeepMind's differentiable neural computer paper.
26. captionGen : Generate captions for an image using PyTorch.
27. AnimeGAN : A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.
28. Cnn-text classification : This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch.
29. deepspeach2 : Implementation of DeepSpeech2 using Baidu Warp-CTC. Creates a network based on the DeepSpeech2 architecture, trained with the CTC activation function.
30. seq2seq : This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch
31. Asynchronous Advantage Actor-Critic in PyTorch : This is PyTorch implementation of A3C as described in Asynchronous Methods for Deep Reinforcement Learning. Since PyTorch has a easy method to control shared memory within multiprocess, we can easily implement asynchronous method like A3C.
32. densenet : This is a PyTorch implementation of the DenseNet-BC architecture as described in the paper Densely Connected Convolutional Networks by G. Huang, Z. Liu, K. Weinberger, and L. van der Maaten. This implementation gets a CIFAR-10+ error rate of 4.77 with a 100-layer DenseNet-BC with a growth rate of 12. Their official implementation and links to many other third-party implementations are available in the liuzhuang13/DenseNet repo on GitHub.
33. nninit : Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin.
34. faster rcnn : This is a PyTorch implementation of Faster RCNN. This project is mainly based on py-faster-rcnn and TFFRCNN.For details about R-CNN please refer to the paper Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks by Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun.
35. doomnet : PyTorch's version of Doom-net implementing some RL models in ViZDoom environment.
36. flownet : Pytorch implementation of FlowNet by Dosovitskiy et al.
37. sqeezenet : Implementation of Squeezenet in pytorch, #### pretrained models on CIFAR10 data to come Plan to train the model on cifar 10 and add block connections too.
38. WassersteinGAN: wassersteinGAN in pytorch.
39. optnet : This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch source code to reproduce the experiments in our paper OptNet: Differentiable Optimization as a Layer in Neural Networks.
40. qp solver : A fast and differentiable QP solver for PyTorch. Crafted by Brandon Amos and J. Zico Kolter.
41. Continuous Deep Q-Learning with Model-based Acceleration : Reimplementation of Continuous Deep Q-Learning with Model-based Acceleration.
42. Learning to learn by gradient descent by gradient descent : PyTorch implementation of Learning to learn by gradient descent by gradient descent.
43. fast-neural-style : pytorch implementation of fast-neural-style, The model uses the method described in Perceptual Losses for Real-Time Style Transfer and Super-Resolution along with Instance Normalization.
44. PytorchNeuralStyleTransfer : Implementation of Neural Style Transfer in Pytorch.
45. Fast Neural Style for Image Style Transform by Pytorch : Fast Neural Style for Image Style Transform by Pytorch .
46. neural style transfer : An introduction to PyTorch through the Neural-Style algorithm (https://arxiv.org/abs/1508.06576) developed by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge.
47. VIN_PyTorch_Visdom : PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.
48. YOLO2: YOLOv2 in PyTorch.
49. attention-transfer: Attention transfer in pytorch, read the paper here.

Blogs & Articles

1. Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch)
2. adversarial-autoencoders-with-pytorch

Pytorch elsewhere

1. the-incredible-pytorch : The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
2. generative models : Collection of generative models, e.g. GAN, VAE in Tensorflow, Keras, and Pytorch. http://wiseodd.github.io
3. pytorch vs tensorflow : an informative thread on reddit.
4. Pytorch discussion forum
5. pytorch notebook: docker-stack : A project similar to Jupyter Notebook Scientific Python Stack

Feedback: If you have any ideas or you want any other content to be added to this list, feel free to contribute.