PyTorch1.0 教程 例子和书籍

 

 

PyTorch1.0-Zero-To-All

pytorch-handbook

Learning PyTorch with Examples (官方中文)

 

1. Deep Learning with PyTorch: a 60-minute blitz (1.x)

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

https://github.com/bat67/Deep-Learning-with-PyTorch-A-60-Minute-Blitz-cn  

PyTorch官网推荐的由网友提供的60分钟教程,本系列教程的重点在于介绍PyTorch的基本原理,包括自动求导,神经网络,以及误差优化API。

2 PyTorch Tutorials (比较早)
https://github.com/MorvanZhou/PyTorch-Tutorial.git
著名的“莫烦”PyTorch系列教程的源码。

3. Simple examples to introduce PyTorch (比较早)
https://github.com/jcjohnson/pytorch-examples.git
由网友提供的PyTorch教程,通过一些实例的方式,讲解PyTorch的基本原理。内容涉及Numpy、自动求导、参数优化、权重共享等。

 

  • PyTorch tutorials, examples and books
    • Table of Contents / 目录:
    • 1. PyTorch 版本变化及迁移指南
    • 2. PyTorch for Numpy users 给Numpy用户的PyTorch指南
    • 3. PyTorch 1.0 tutorials and examples
    • 4. Books and slides about PyTorch 书籍、PPT等
    • 5. 以下是一些独立的教程
      • 1) PyTorch深度学习:60分钟入门与实战
      • 2) Learning PyTorch with Examples 用例子学习PyTorch
      • 3) PyTorch1.0-Zero-To-All
      • 4) Grokking PyTorch
    • 6. How to run? 推荐的运行方式

 

入门实例

  1. Ten minutes pyTorch Tutorial
    https://github.com/SherlockLiao/pytorch-beginner.git
    知乎上“十分钟学习PyTorch“系列教程的源码。
  2. Official PyTorch Examples
    https://github.com/pytorch/examples
    官方提供的实例源码,包括以下内容:
    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 an LSTM to learn Sine waves
  3. PyTorch Tutorial for Deep Learning Researchers
    https://github.com/yunjey/pytorch-tutorial.git
    据说是提供给深度学习科研者们的PyTorch教程←_←。教程中的每个实例的代码都控制在30行左右,简单易懂,内容如下:
    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
  4. PyTorch-playground
    https://github.com/aaron-xichen/pytorch-playground.git
    PyTorch初学者的Playground,在这里针对一下常用的数据集,已经写好了一些模型,所以大家可以直接拿过来玩玩看,目前支持以下数据集的模型。
    mnist, svhn
    cifar10, cifar100
    stl10
    alexnet
    vgg16, vgg16_bn, vgg19, vgg19_bn
    resnet18, resnet34, resnet50, resnet101, resnet152
    squeezenet_v0, squeezenet_v1
    inception_v3

 

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