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.
- [PyTorch install]
$ pip3 install http://download.pytorch.org/whl/torch-0.3.1-cp36-cp36m-macosx_10_7_x86_64.whl
$ pip3 install torchvision $ pip3 install http://download.pytorch.org/whl/cu90/torch-0.3.1-cp35-cp35m-linux_x86_64.whl
$ pip3 install torchvision - Lecture2:Linear Model
- Lecture3:Gradient_Descent
- Lecture4:Back_propagration
- Lecture5:Linear_regression
- Lecture6:Logistic_regression
- Lecture7:Wide_Deep
- Lecture8:DataLoader
- Lecture8:DataLoader_logistic
- Lecture9:Softmax_Classifier
- Lecture9:Softmax_Classifier_mnist
- 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
$ git clone https://github.com/Tim810306/PytorchTutorial.git
$ cd PytorchTutorial/tutorials/project_path
$ python main.py # cpu version
$ python main-gpu.py # gpu version
$ python main_XXX.py # execute XXX for cpu versionCheng Yu Ting/ @Tim810306