Pytorch Project code and resource list | Resources Download _ Depth Learning

This article collects a large number of code links based on Pytorch implementations, including "Getting Started" series for beginners in depth learning, and paper code implementations for older drivers, including Attention Based CNN, A3C, Wgan, and more. All code is categorized according to the technical domain, including machine vision/image correlation, natural language processing related, reinforcement learning related, and so on. So if you're going to start the Pytorch technology of the first world, then quickly collect this article.

What Pytorch is.

Pytorch is the Python version of Torch. Torch is a deep learning framework published by Facebook, which supports dynamic definition of graphs, and is more flexible and convenient to use than TensorFlow, especially for small and medium machine learning programs and deep learning beginners. But because Torch's development language is LUA, it has been a minority in the country. Therefore, under the long-awaited, Pytorch emerged. Pytorch inherits the flexibility of Troch and uses popular Python as a development language, so it's popular once it's launched.

Directory:

Getting Started series tutorials

Getting Started example

Image, vision, CNN related implementation

Countermeasure generation network, generation model, Gan correlation implementation

Machine translation, question answering system, NLP related implementation

Advanced Vision Inference System

Deep Reinforcement Learning related realization

Advanced application of General neural network

1

Getting Started series tutorials

1.PyTorch Tutorials

Https://github.com/MorvanZhou/PyTorch-Tutorial.git

The famous "Mo Annoying" pytorch series of tutorials in the source code.

2.Deep Learning with pytorch:a 60-minute Blitz

Http://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html

Pytorch's website recommends a 60-minute tutorial, which focuses on introducing the fundamentals of Pytorch, including automatic derivation, neural networks, and error-tuning APIs.

3.Simple examples to introduce pytorch

Https://github.com/jcjohnson/pytorch-examples.git

Pytorch tutorials provided by users, through a number of examples of ways to explain the basic principles of pytorch. The content involves NumPy, automatic derivation, parameter optimization, weight sharing and so on.

2

Getting Started example

1.Ten minutes Pytorch Tutorial

Https://github.com/SherlockLiao/pytorch-beginner.git

Know the source of the "10-minute Learning Pytorch" series tutorial.

2.Official Pytorch Examples

Https://github.com/pytorch/examples

Official examples of source code, including the following:

Mnist convnets

Word level Language modeling using LSTM Rnns

Training imagenet classifiers with residual Networks

Generative adversarial Networks (Dcgan)

Variational auto-encoders

Superresolution using an efficient sub-pixel convolutional neural network

Hogwild training of shared convnets across multiple processes on mnist

Training a cartpole to balance in OpenAI Gym with actor-critic

Natural Language Inference (Snli) with GloVe vectors, Lstms, and Torchtext

Time sequence prediction-create a lstm to learn Sine waves

3.PyTorch Tutorial for Deep Learning researchers

Https://github.com/yunjey/pytorch-tutorial.git

It is said to be a pytorch tutorial ←_← for deep learning scientists. The code for each instance in the tutorial is controlled in about 30 lines, which is easy to understand and reads as follows:

Pytorch Basics

Linear regression

Logistic regression

Feedforward Neural Network

convolutional Neural Network

Deep Residual Network

Recurrent neural Network

Bidirectional Recurrent neural Network

Language Model (RNN-LM)

Generative adversarial network

Image captioning (CNN-RNN)

Deep convolutional GAN (Dcgan)

Variational Auto-encoder

Neural Style Transfer

Tensorboard in Pytorch

4pytorch-playground

Https://github.com/aaron-xichen/pytorch-playground.git

Pytorch Beginners of the playground, here for the common data set, has written some models, so you can directly to play to see, currently supports the following data set model.

Mnist, Svhn

Cifar10, cifar100

Stl10

Alexnet

Vgg16, Vgg16_bn, Vgg19, vgg19_bn

resnet18, Resnet34, Resnet50, resnet101, resnet152

Squeezenet_v0, SQUEEZENET_V1

Inception_v3

3

Image, vision, CNN related implementation

1.pytorch-fcn

Https://github.com/wkentaro/pytorch-fcn.git

Implemented implementation of FCN (fully convolutional Networks pytorch).

2.Attention Transfer

Https://github.com/szagoruyko/attention-transfer.git

Paper "Paying more Attention to attention:improving the performance of convolutional neural via Networks Attention" Implementation of the Pytorch.

3.Wide ResNet model in Pytorch

Https://github.com/szagoruyko/functional-zoo.git

A pytorch implementation of the Imagenet classification.

4.CRNN for image-based sequence recognition

Https://github.com/bgshih/crnn.git

This is the CRNN implementation of convolutional recurrent neural Network (pytorch). CRNN consists of a number of cnn,rnn and CTC, often used for image-based sequence recognition tasks, such as scene text recognition and OCR.

5.Scaling the scattering transform:deep Hybrid Networks

Https://github.com/edouardoyallon/pyscatwave.git

Using the "Scattering network" CNN implementation, the special architecture improves the network's effectiveness.

6.Conditional similarity Networks (CSNs)

Https://github.com/andreasveit/conditional-similarity-networks.git

The Pytorch realization of "Conditional similarity Networks".

7.multi-style generative network for real-time Transfer

Https://github.com/zhanghang1989/PyTorch-Style-Transfer.git

Msg-net and the Pytorch implementation of neural Style.

8.Big Batch Training

Https://github.com/eladhoffer/bigBatch.git

Generalization implementation of the Train longer, generalize better:closing large gap in batch training neural of networks.

9.CortexNet

Https://github.com/e-lab/pytorch-CortexNet.git

A robust predictive depth neural network using video training.

10.Neural message passing for Quantum chemistry

Https://github.com/priba/nmp_qc.git

The Pytorch realization of the neural message passing for Quantum chemistry is like the transmission of neural information under computer vision.

4

Countermeasure generation network, generation model, Gan correlation implementation

1.Generative adversarial Networks (Gans) in Pytorch

Https://github.com/devnag/pytorch-generative-adversarial-networks.git

A very simple confrontation generation network implemented by Pytorch

2.DCGAN & Wgan with Pytorch

Https://github.com/chenyuntc/pytorch-GAN.git

Dcgan and Wgan implemented by Chinese netizens, the code is very concise.

3.Official Code for Wgan

Https://github.com/martinarjovsky/WassersteinGAN.git

The official pytorch of Wgan is realized.

4.DiscoGAN in Pytorch

Https://github.com/carpedm20/DiscoGAN-pytorch.git

Generative implementation of the Learning to Discover Cross-domain Relations with adversarial Networks pytorch.

5.Adversarial Generator-encoder Network

Https://github.com/DmitryUlyanov/AGE.git

The Pytorch realization of "adversarial generator-encoder Networks".

6.CycleGAN and Pix2pix in Pytorch

Https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix.git

The translation of diagrams to graphs, the famous Cyclegan and the Pytorch implementations of Pix2pix.

7.Weight normalized GAN

Https://github.com/stormraiser/GAN-weight-norm.git

The generative implementation of the effects of Batch and Weight normalization in adversarial Networks.

5

Machine translation, question answering system, NLP related implementation

1.DeepLearningForNLPInPytorch

Https://github.com/rguthrie3/DeepLearningForNLPInPytorch.git

A set of Pytorch basic tutorials with NLP as its theme. This tutorial is written using Ipython notebook, which looks intuitive and easy to learn.

2.Practial Pytorch with Topic RNN & NLP

Https://github.com/spro/practical-pytorch

The Pytorch basic tutorials, starting with RNN for NLP, are divided into "Rnns for NLP" and "Rnns for timeseries data" two sections.

3.pyopennmt:open-source Neural Machine Translation

Https://github.com/OpenNMT/OpenNMT-py.git

A set of machine translation system implemented by Pytorch.

4.Deal or No Deal? End-to-end Learning for negotiation dialogues

Https://github.com/facebookresearch/end-to-end-negotiator.git

Facebook AI Research paper "Deal or No Deal"? End-to-end Learning for negotiation dialogues "Pytorch implementation.

5.Attention is all need:a pytorch implementation

Https://github.com/jadore801120/attention-is-all-you-need-pytorch.git

Google Research, the famous paper "Attention is the all you need" pytorch implementation.

6.Improved Visual Semantic embeddings

Https://github.com/fartashf/vsepp.git

A method of retrieving text from an image is derived from the thesis: "vse++: Improved Visual-semantic embeddings".

7.Reading Wikipedia to Answer open-domain Questions

Https://github.com/facebookresearch/DrQA.git

An open domain question and answer system Drqa pytorch implementation.