【Github2.2K星】PyTorch资源列表:450个NLP/CV/SP、论文实现、教程、示例

简介:

项目地址:

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

980540c44173efd727bf4b2bed43f1cd0fd5b0cc

PyTorch 是什么?

PyTorch是一个用于科学计算和深度学习的Python扩展库。它便于学习、编写和调试,支持灵活的动态计算图和GPU高速运算,具有完善的研发生态和技术社区。PyTorch于2017年由Facebook正式推出后,迅速引起了人工智能研发人员的关注,目前已成为最受重视的机器学习软件库之一。近日,Facebook 在首届 PyTorch 开发者大会发布了 PyTorch1.0 预览版,标志着这一框架更为稳定可用。

目录

一. 自然语言与语音处理NLP & Speech Processing

二. 计算机视觉CV

三. 概率生成库

四. 其他库

五. 教程和例子

六. 论文实现

七.其他Pytorch资源

目录内容

Pytorch 官网

项目链接:https://github.com/pytorch/pytorch/releases

一. 自然语言与语音处理

pytorch text : Torch text related contents.
pytorch-seq2seq: A framework for sequence-to-sequence (seq2seq) models implemented in PyTorch.
anuvada: Interpretable Models for NLP using PyTorch.
audio: simple audio I/O for pytorch.
loop: A method to generate speech across multiple speakers
fairseq-py: Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
speech: PyTorch ASR Implementation.
OpenNMT-py: Open-Source Neural Machine Translation in PyTorch http://opennmt.net
neuralcoref: State-of-the-art coreference resolution based on neural nets and spaCy huggingface.co/coref
sentiment-discovery: Unsupervised Language Modeling at scale for robust sentiment classification.
MUSE: A library for Multilingual Unsupervised or Supervised word Embeddings
nmtpytorch: Neural Machine Translation Framework in PyTorch.
pytorch-wavenet: An implementation of WaveNet with fast generation
Tacotron-pytorch: Tacotron: Towards End-to-End Speech Synthesis.
AllenNLP: An open-source NLP research library, built on PyTorch.
PyTorch-NLP: Text utilities and datasets for PyTorch pytorchnlp.readthedocs.io
quick-nlp: Pytorch NLP library based on FastAI.
TTS: Deep learning for Text2Speech
LASER: Language-Agnostic SEntence Representations
pyannote-audio: Neural building blocks for speaker diarization: speech activity detection, speaker change detection, speaker embedding
gensen: Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning.
translate: Translate - a PyTorch Language Library.
espnet: End-to-End Speech Processing Toolkit espnet.github.io/espnet
pythia: A software suite for Visual Question Answering
UnsupervisedMT: Phrase-Based & Neural Unsupervised Machine Translation.
jiant: The jiant sentence representation learning toolkit.

二. 计算机视觉

pytorch vision : Datasets, Transforms and Models specific to Computer Vision.
pt-styletransfer: Neural style transfer as a class in PyTorch.
OpenFacePytorch: PyTorch module to use OpenFace's nn4.small2.v1.t7 model
img_classification_pk_pytorch: Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
SparseConvNet: Submanifold sparse convolutional networks.
Convolution_LSTM_pytorch: A multi-layer convolution LSTM module

face-alignment:

2D and 3D Face alignment library build using pytorch adrianbulat.com

pytorch-semantic-segmentation: PyTorch for Semantic Segmentation.
RoIAlign.pytorch: This is a PyTorch version of RoIAlign. This implementation is based on crop_and_resize and supports both forward and backward on CPU and GPU.
pytorch-cnn-finetune: Fine-tune pretrained Convolutional Neural Networks with PyTorch.
detectorch: Detectorch - detectron for PyTorch
Augmentor: Image augmentation library in Python for machine learning. http://augmentor.readthedocs.io
s2cnn: This library contains a PyTorch implementation of the SO(3) equivariant CNNs for spherical signals (e.g. omnidirectional cameras, signals on the globe) s

三. 概率生成库

ptstat: Probabilistic Programming and Statistical Inference in PyTorch
pyro: Deep universal probabilistic programming with Python and PyTorch http://pyro.ai
probtorch: Probabilistic Torch is library for deep generative models that extends PyTorch.
paysage: Unsupervised learning and generative models in python/pytorch.
pyvarinf: Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch.
pyprob: A PyTorch-based library for probabilistic programming and inference compilation.
mia: A library for running membership inference attacks against ML models.

四. 其他库

pytorch extras : Some extra features for pytorch.
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.
torch-sampling : This package provides a set of transforms and data structures for sampling from in-memory or out-of-memory data.
torchcraft-py : Python wrapper for TorchCraft, a bridge between Torch and StarCraft for AI research.
aorun : Aorun intend to be a Keras with PyTorch as backend.
logger : A simple logger for experiments.
PyTorch-docset : PyTorch docset! use with Dash, Zeal, Velocity, or LovelyDocs.
convert_torch_to_pytorch : Convert torch t7 model to pytorch model and source.
pretrained-models.pytorch: The goal of this repo is to help to reproduce research papers results.
pytorch_fft : PyTorch wrapper for FFTs

五. 教程例子

Practical Pytorch : Tutorials explaining different RNN models
DeepLearningForNLPInPytorch : An IPython Notebook tutorial on deep learning, with an emphasis on Natural Language Processing.
pytorch-tutorial : tutorial for researchers to learn deep learning with pytorch.
pytorch-exercises : pytorch-exercises collection.
pytorch tutorials : Various pytorch tutorials.
pytorch examples : A repository showcasing examples of using pytorch
pytorch practice : Some example scripts on pytorch.
pytorch mini tutorials : Minimal tutorials for PyTorch adapted from Alec Radford's Theano tutorials.
pytorch text classification : A simple implementation of CNN based text classification in Pytorch
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.

六. 论文实现

google_evolution : This implements one of result networks from Large-scale evolution of image classifiers by Esteban Real, et. al.
pyscatwave : Fast Scattering Transform with CuPy/PyTorch,read the paper here
scalingscattering : Scaling The Scattering Transform : Deep Hybrid Networks.
deep-auto-punctuation : a pytorch implementation of auto-punctuation learned character by character.
Realtime_Multi-Person_Pose_Estimation : This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here .
PyTorch-value-iteration-networks : PyTorch implementation of the Value Iteration Networks (NIPS '16) paper
pytorch_Highway : Highway network implemented in pytorch.
pytorch_NEG_loss : NEG loss implemented in pytorch.
pytorch_RVAE : Recurrent Variational Autoencoder that generates sequential data implemented in pytorch.
pytorch_TDNN : Time Delayed NN implemented in pytorch.

七. 其他Pytorch资源

the-incredible-pytorch : The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
generative models : Collection of generative models, e.g. GAN, VAE in Tensorflow, Keras, and Pytorch. http://wiseodd.github.io
pytorch vs tensorflow : an informative thread on reddit.
Pytorch discussion forum
pytorch notebook: docker-stack : A project similar to Jupyter Notebook Scientific Python Stack
drawlikebobross: Draw like Bob Ross using the power of Neural Networks (With PyTorch)!
pytorch-tvmisc: Totally Versatile Miscellanea for Pytorch
pytorch-a3c-mujoco: Implement A3C for Mujoco gym envs.
PyTorch in 5 Minutes.
pytorch_chatbot: A Marvelous ChatBot implemented using PyTorch.


原文发布时间为:2018-10-21

本文来自云栖社区合作伙伴“专知”,了解相关信息可以关注“专知”。

相关文章
|
机器学习/深度学习 存储 自然语言处理
NLP参数高效迁移学习:Adapter方法——论文简读
本研究深入探讨了自然语言处理中参数高效的迁移学习方法——Adapter。通过在预训练模型中引入小型可训练模块,仅调整少量额外参数即可完成模型适配。理论分析表明,该方法在初始化时保持网络行为稳定,并通过瓶颈结构大幅压缩参数规模。实验结果显示,Adapter在GLUE基准上仅用3.6%的参数便达到接近全微调的性能,且对学习率具有更强的鲁棒性。相比传统微调和其他参数高效方法,Adapter在多任务场景下展现出更优的存储效率与泛化能力,为大规模模型的实际部署提供了高效可行的解决方案。
870 7
|
人工智能 自然语言处理 API
用自然语言控制电脑,字节跳动开源 UI-TARS 的桌面版应用!内附详细的安装和配置教程
UI-TARS Desktop 是一款基于视觉语言模型的 GUI 代理应用,支持通过自然语言控制电脑操作,提供跨平台支持、实时反馈和精准的鼠标键盘控制。
7409 17
用自然语言控制电脑,字节跳动开源 UI-TARS 的桌面版应用!内附详细的安装和配置教程
|
人工智能 网络安全 开发工具
vscode代码推送到github库菜鸡专用教程
vscode代码推送到github库菜鸡专用教程
|
存储 Linux Go
如何在Github上Pull Request的教程
关于如何在GitHub上发起Pull Request(合并请求)的详细教程,包括Fork(分支)、Clone(克隆)、创建新分支、修改代码、提交更改、推送到远程仓库等步骤,并提供了解决权限问题的方法,如创建个人访问令牌(Personal Access Token)。
1154 6
|
机器学习/深度学习 自然语言处理 PyTorch
PyTorch与Hugging Face Transformers:快速构建先进的NLP模型
【8月更文第27天】随着自然语言处理(NLP)技术的快速发展,深度学习模型已经成为了构建高质量NLP应用程序的关键。PyTorch 作为一种强大的深度学习框架,提供了灵活的 API 和高效的性能,非常适合于构建复杂的 NLP 模型。Hugging Face Transformers 库则是目前最流行的预训练模型库之一,它为 PyTorch 提供了大量的预训练模型和工具,极大地简化了模型训练和部署的过程。
1308 2
|
机器学习/深度学习 自然语言处理 PyTorch
PyTorch 在自然语言处理中的应用案例研究
【8月更文第27天】PyTorch 是一个强大的开源机器学习框架,它为开发者提供了构建和训练深度学习模型的能力。在自然语言处理(NLP)领域,PyTorch 提供了一系列工具和库,使开发者能够快速地实现和测试新的想法。本文将介绍如何使用 PyTorch 来解决常见的 NLP 问题,包括文本分类和机器翻译,并提供具体的代码示例。
549 2
|
数据采集 数据可视化 Ruby
GitHub星标破万!Python学习教程(超详细),真的太强了!
Python 是一门初学者友好的编程语言,想要完全掌握它,你不必花上太多的时间和精力。 Python 的设计哲学之一就是简单易学,体现在两个方面: 1. 语法简洁明了:相对 Ruby 和 Perl,它的语法特性不多不少,大多数都很简单直接,不玩儿玄学。 2. 切入点很多:Python 可以让你可以做很多事情,科学计算和数据分析、爬虫、Web 网站、游戏、命令行实用工具等等等等,总有一个是你感兴趣并且愿意投入时间的。
GitHub爆赞的Web安全防护指南,网络安全零基础入门必备教程!
web安全现在占据了企业信息安全的很大一部分比重,每个企业都有对外发布的很多业务系统,如何保障web业务安全也是一项信息安全的重要内容。 然而Web 安全是一个实践性很强的领域,需要通过大量的练习来建立对漏洞的直观认识,并积累解决问题的经验。 Web安全与防护技术是当前安全界关注的热点,今天给小伙伴们分享的这份手册尝试针对各类漏洞的攻防技术进行体系化整理,从漏洞的原理到整体攻防技术演进过程进行详细讲解,从而形成对漏洞和web安全的体系化的认识。
怎样在GitHub上建立仓库、以及怎样实现分支代码的合并。保姆级别的教程
这篇文章是一份详细的GitHub使用教程,介绍了如何在GitHub上创建仓库、创建分支、编辑和发布更改内容、发起拉取请求以及合并分支的操作步骤。
怎样在GitHub上建立仓库、以及怎样实现分支代码的合并。保姆级别的教程
GitHub爆赞的Web安全防护指南,网络安全零基础入门必备教程!
web安全现在占据了企业信息安全的很大一部分比重,每个企业都有对外发布的很多业务系统,如何保障web业务安全也是一项信息安全的重要内容。 然而Web 安全是一个实践性很强的领域,需要通过大量的练习来建立对漏洞的直观认识,并积累解决问题的经验。 Web安全与防护技术是当前安全界关注的热点,今天给小伙伴们分享的这份手册尝试针对各类漏洞的攻防技术进行体系化整理,从漏洞的原理到整体攻防技术演进过程进行详细讲解,从而形成对漏洞和web安全的体系化的认识。

推荐镜像

更多