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Variational AutoEncoder Implementation

Description

Implementation of Variational AutoEncoder(VAE) using pytorch.

Please refer to the following blog post for more information about VAE

https://docs.jinhochoi.xyz/machine-learning/variational-auto-encoder

Getting Started

Prerequisite

python 3.11.10

Use pyenv to set python version to 3.11.10

$ python --version
Python 3.11.10

uv-python

We are going to use uv-python to install package and manage virtualenv.

Install requirements

Run the following command to install requirements:

// initialize venv
$ uv venv

// activating the venv
$ source .venv/bin/activate 

// install required packages
$ uv pip install -r requirements.txt

Run VAE

Execute jupyter lab using following command

$ jupyter lab
// this will run jupyter server, and you can open jupyter-notebook for VAE_tutorial.ipynb file

Open VAE_tutorial.ipynb file in jupyter lab, and run all the cells.

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