# LIS-YNP

**Repository Path**: vantablack/LIS-YNP

## Basic Information

- **Project Name**: LIS-YNP
- **Description**: :crystal_ball: Life is short, you need PyTorch.
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-14
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## 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:. 


<br/>

# 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.