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When we load an image for the sample, we have to make sure that the image has three color channel (RGB) because it might be grayscale. So we should convert it for sampling.
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.
Table of Contents
1. Basics
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
Getting Started
$ git clone https://github.com/yunjey/pytorch-tutorial.git
$ cd pytorch-tutorial/tutorials/PATH_TO_PROJECT
$ python main.py
Dependencies
Author
Yunjey Choi/ @yunjey
Languages
Python
99.4%
Shell
0.6%