Giter VIP home page Giter VIP logo

autoencoder.pytorch's Introduction

AutoEncoder with Pytorch

This project is an implementation of auto-encoder with MNIST dataset and pytorch = 1.4.0

Learn tensorboard by the way

Instruction to Prepare MNIST dataset

bash ./script/prepare.sh

Instruction to Train Model

bash ./script/train.sh ${model_name}

${model_name} can be one of conv/linear/vae...

Instruction to use tensorboard visulize

tensorboard --logdir=runs --bind_all
Trainning Loss

Decode Performance

Model Architecture

have to be aware of these information:

The output shape of ConvTranspose2d can be computed by formula:

Reference

Hung-yi Lee MachineLearning Spring2020 Course (https://www.bilibili.com/video/BV1JE411g7XF?p=59)

https://github.com/L1aoXingyu/pytorch-beginner (Conv Model from here, But train code with this repositories have a bug in transform operation, detail in this pr page)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.