lyeoni/pytorch-tutorial-1

PyTorch Tutorial for Deep Learning Researchers

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This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less than 30 lines of code. Before starting this tutorial, it is recommended to finish Official Pytorch Tutorial. If you are also interested in generative adversarial networks, check out our recent work, TUNIT.

Table of Contents

1. Basics

• PyTorch Basics
• Linear Regression
• Logistic Regression
• Feedforward Neural Network

2. Intermediate

• Convolutional Neural Network
• Deep Residual Network
• Recurrent Neural Network
• Bidirectional Recurrent Neural Network
• Language Model (RNN-LM)

3. Advanced

• Generative Adversarial Networks
• Variational Auto-Encoder
• Neural Style Transfer
• Image Captioning (CNN-RNN)

4. Utilities

• TensorBoard in PyTorch

Getting Started

$ git clone https://github.com/yunjey/pytorch-tutorial.git
$ cd pytorch-tutorial/tutorials/PATH_TO_PROJECT
$ python main.py

Dependencies

• Python 2.7 or 3.5+
• PyTorch 0.4.0+