https://github.com/eurus-holmes/lis-ynp

:crystal_ball: Life is short, you need PyTorch.
https://github.com/eurus-holmes/lis-ynp

examples models pytorch tutorials

Last synced: 2 days ago
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:crystal_ball: Life is short, you need PyTorch.

• Host: GitHub
• URL: https://github.com/eurus-holmes/lis-ynp
• Owner: Eurus-Holmes
• License: mit
• Created: 2018-07-06T17:47:25.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-12-18T15:16:01.000Z (almost 5 years ago)
• Last Synced: 2023-11-07T17:04:25.650Z (about 1 year ago)
• Topics: examples, models, pytorch, tutorials
• Language: Jupyter Notebook
• Homepage: https://chenfeiyang.top/LIS-YNP/
• Size: 12.5 MB
• Stars: 133
• Watchers: 5
• Forks: 29
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE

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README

        
# LIS-YNP (Life Is Short-You Need Pytorch)

![build](https://img.shields.io/badge/build-passing-brightgreen.svg)

![license](https://img.shields.io/badge/License-MIT-brightgreen.svg)

![prs](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)

Based on [Official Pytorch Tutorial](https://pytorch.org/tutorials/) and [yunjey's pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial), this repository provides tutorial code for deep learning researchers to learn [PyTorch](https://github.com/pytorch/pytorch) :octocat:. 

There is also a [PyTorch tutorial](https://github.com/spro/practical-pytorch) demonstrating modern techniques with readable code :ghost:.

If you are looking for some fun projects including neural talk, neural style, poem writing, anime generation and so on, you can read [pytorch-book](https://github.com/chenyuntc/pytorch-book) :squirrel:.

Of course, anything on github has its own "**Awesome**" :full_moon_with_face:. The [Awesome-pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list) collected different models, implementations, helper libraries, tutorials, etc :gift_heart:.

All in all, ***Life Is Short, You Need Pytorch*** :innocent:. 




# Table of Contents

### 1. Basics

* [Getting Started](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/01-basics/Getting_Started.ipynb)

* [Autograd](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/01-basics/Autograd.ipynb)

* [PyTorch Basics](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/01-basics/pytorch_basics/main.py)

* [Linear Regression](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/01-basics/linear_regression/main.py#L22-L23)

* [Logistic Regression](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/01-basics/logistic_regression/main.py#L33-L34)

* [Feedforward Neural Network](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/01-basics/feedforward_neural_network/main.py#L37-L49)

* [Neural Networks](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/01-basics/Neural_Networks.ipynb)

* [Optional Data Parallelism](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/01-basics/Optional_Data_Parallelism.ipynb)

### 2. Intermediate

* [Training a Classifier](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/02-intermediate/Training_a_Classifier.ipynb)

* [Convolutional Neural Network](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/02-intermediate/convolutional_neural_network/main.py#L35-L56)

* [Deep Residual Network](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/02-intermediate/deep_residual_network/main.py#L76-L113)

* [Recurrent Neural Network](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/02-intermediate/recurrent_neural_network/main.py#L39-L58)

* [Bidirectional Recurrent Neural Network](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/02-intermediate/bidirectional_recurrent_neural_network/main.py#L39-L58)

* [Language Model (RNN-LM)](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/02-intermediate/language_model/main.py#L30-L50)

### 3. Advanced

* [Chatbot](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/03-advanced/chatbot/chatbot_tutorial.ipynb)

* [Finetuning Torchvision Models](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/03-advanced/finetuning_torchvision_models/finetuning_torchvision_models_tutorial.ipynb)

* [Generative Adversarial Networks](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/03-advanced/generative_adversarial_network/main.py#L41-L57)

* [Image Captioning (CNN-RNN)](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/03-advanced/image_captioning)

* [Neural Style Transfer](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/03-advanced/neural_style_transfer)

* [NMT (Seq2Seq+Attention)](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/03-advanced/nmt/seq2seq_attention_nmt.ipynb)

* [Object Detection Finetuning](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/03-advanced/object_detection_finetuning/torchvision_finetuning_instance_segmentation.py)

* [Spatial Transformer Networks](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/03-advanced/spatial_transformer_network/spatial_transformer_tutorial.ipynb)

* [Variational Auto-Encoder](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/03-advanced/variational_autoencoder/main.py#L38-L65)

* [Meta-Learning](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/03-advanced/meta-learning)

### 4. Utilities

* [OpCounter](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/tutorials/04-utils/OpCounter)

* [TensorBoard in PyTorch](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/04-utils/tensorboard)

* [TensorWatch](https://github.com/Eurus-Holmes/LIS-YNP/tree/master/tutorials/04-utils/tensorwatch)

# License

See the [LICENSE](https://github.com/Eurus-Holmes/LIS-YNP/blob/master/LICENSE) file for this repository's licensing.