Awesome-Pytorch-list

2018-08-10 09:25:16

This blog is copied from: https://github.com/Epsilon-Lee/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.
12. pt-styletransfer: Neural style transfer as a class in PyTorch.
13. pretrained-models.pytorch: The goal of this repo is to help to reproduce research papers results.
14. pytorch_fft : PyTorch wrapper for FFTs
15. OpenFacePytorch: PyTorch module to use OpenFace’s nn4.small2.v1.t7 model
16. caffe_to_torch_to_pytorch
17. ptstat: Probabilistic Programming and Statistical Inference in PyTorch
18. pytorch-extension: This is a CUDA extension for PyTorch which computes the Hadamard product of two tensors.
19. tensorboard-pytorch: This module saves PyTorch tensors in tensorboard format for inspection. Currently supports scalar, image, audio, histogram features in tensorboard.
20. pytorch-seq2seq: A framework for sequence-to-sequence (seq2seq) models implemented in PyTorch.
21. SparseConvNet: Submanifold sparse convolutional networks.
22. gpytorch: GPyTorch is a Gaussian Process library, implemented using PyTorch. It is designed for creating flexible and modular Gaussian Process models with ease, so that you don’t have to be an expert to use GPs.
23. img_classification_pk_pytorch: Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, …)
24. tensorboard-pytorch: tensorboard for pytorch
25. Convolution_LSTM_pytorch: A multi-layer convolution LSTM module

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).
16. Kind_PyTorch_Tutorial: Kind PyTorch Tutorial for beginners.
17. pytorch-poetry-gen: a char-RNN based on pytorch.
18. pytorch-REINFORCE: PyTorch implementation of REINFORCE, This repo supports both continuous and discrete environments in OpenAI gym.
19. PyTorch-Tutorial: Build your neural network easy and fast https://morvanzhou.github.io/tutorials/
20. pytorch-intro: A couple of scripts to illustrate how to do CNNs and RNNs in PyTorch
21. pytorch-classification: A unified framework for the image classification task on CIFAR-10/100 and ImageNet.
22. pytorch_notebooks – hardmaru: Random tutorials created in NumPy and 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.
50. SVHNClassifier: A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks.
51. pytorch-deform-conv: PyTorch implementation of Deformable Convolution.
52. BEGAN-pytorch: PyTorch implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks.
53. treelstm.pytorch : Tree LSTM implementation in PyTorch.
54. AGE: Code for paper “Adversarial Generator-Encoder Networks” by Dmitry Ulyanov, Andrea Vedaldi and Victor Lempitsky which can be found here
55. ResNeXt.pytorch: Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch.
56. pytorch-rl: Deep Reinforcement Learning with pytorch & visdom
57. Deep-Leafsnap: LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods.
58. pytorch-CycleGAN-and-pix2pix: PyTorch implementation for both unpaired and paired image-to-image translation.
59. A3C-PyTorch:PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
60. pytorch-value-iteration-networks : Pytorch implementation of Value Iteration Networks (NIPS 2016 best paper)
61. PyTorch-Style-Transfer: PyTorch Implementation of Multi-style Generative Network for Real-time Transfer
62. pytorch-deeplab-resnet: pytorch-deeplab-resnet-model.
63. pointnet.pytorch: pytorch implementation for “PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation” https://arxiv.org/abs/1612.00593
64. pytorch-playground: Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet).
65. pytorch-dnc: Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom.
66. pytorch_image_classifier: Minimal But Practical Image Classifier Pipline Using Pytorch, Finetune on ResNet18, Got 99% Accuracy on Own Small Datasets.
67. mnist-svhn-transfer: PyTorch Implementation of CycleGAN and SGAN for Domain Transfer (Minimal).
68. pytorch-yolo2: pytorch-yolo2
69. dni: Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch
70. wgan-gp: A pytorch implementation of Paper “Improved Training of Wasserstein GANs”.
71. pytorch-seq2seq-intent-parsing: Intent parsing and slot filling in PyTorch with seq2seq + attention
72. pyTorch_NCE: An implementation of the Noise Contrastive Estimation algorithm for pyTorch. Working, yet not very efficient.
73. molencoder: Molecular AutoEncoder in PyTorch
74. GAN-weight-norm: Code for “On the Effects of Batch and Weight Normalization in Generative Adversarial Networks”
75. lgamma: Implementations of polygamma, lgamma, and beta functions for PyTorch
76. bigBatch : Code used to generate the results appearing in “Train longer, generalize better: closing the generalization gap in large batch training of neural networks”
77. rl_a3c_pytorch: Reinforcement learning with implementation of A3C LSTM for Atari 2600.
78. pytorch-retraining: Transfer Learning Shootout for PyTorch’s model zoo (torchvision)
79. nmp_qc: Neural Message Passing for Computer Vision
80. grad-cam: Pytorch implementation of Grad-CAM
81. pytorch-trpo: PyTorch Implementation of Trust Region Policy Optimization (TRPO)
82. pytorch-explain-black-box: PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation
83. vae_vpflows: Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling https://jmtomczak.github.io/deebmed.html
84. relational-networks: Pytorch implementation of “A simple neural network module for relational reasoning” (Relational Networks) https://arxiv.org/pdf/1706.01427.pdf
85. vqa.pytorch: Visual Question Answering in Pytorch
86. end-to-end-negotiator: Deal or No Deal? End-to-End Learning for Negotiation Dialogues
87. odin-pytorch: Principled Detection of Out-of-Distribution Examples in Neural Networks.
88. FreezeOut: Accelerate Neural Net Training by Progressively Freezing Layers.
89. ARAE: Code for the paper “Adversarially Regularized Autoencoders for Generating Discrete Structures” by Zhao, Kim, Zhang, Rush and LeCun.
90. forward-thinking-pytorch: Pytorch implementation of “Forward Thinking: Building and Training Neural Networks One Layer at a Time” https://arxiv.org/pdf/1706.02480.pdf
91. context_encoder_pytorch: PyTorch Implement of Context Encoders
92. attention-is-all-you-need-pytorch: A PyTorch implementation of the Transformer model in “Attention is All You Need”.https://github.com/thnkim/OpenFacePytorch
93. OpenFacePytorch: PyTorch module to use OpenFace’s nn4.small2.v1.t7 model
94. neural-combinatorial-rl-pytorch: PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning. 95.pytorch-nec: PyTorch Implementation of Neural Episodic Control (NEC)
95. seq2seq.pytorch: Sequence-to-Sequence learning using PyTorch
96. Pytorch-Sketch-RNN: a pytorch implementation of arxiv.org/abs/1704.03477
97. pytorch-pruning: PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
98. DrQA : A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.
99. YellowFin_Pytorch : auto-tuning momentum SGD optimizer
100. samplernn-pytorch : PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model.
101. AEGeAN: Deeper DCGAN with AE stabilization
102. /pytorch-SRResNet: pytorch implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802v2
103. vsepp: Code for the paper “VSE++: Improved Visual Semantic Embeddings”

Blogs & Articles

1. Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch)
2. adversarial-autoencoders-with-pytorch
3. transfer learning using 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
6. drawlikebobross: Draw like Bob Ross using the power of Neural Networks (With PyTorch)!
7. pytorch-tvmisc: Totally Versatile Miscellanea for Pytorch
8. pytorch-a3c-mujoco: Implement A3C for Mujoco gym envs.
9. PyTorch in 5 Minutes.
10. pytorch_chatbot: A Marvelous ChatBot implemented using PyTorch.
11. malmo-challenge: Malmo Collaborative AI Challenge – Team Pig Catcher

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