LiUzHiAn / VAE-Pytorch

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1.Overview

This is the Pytorch implementation of variational auto-encoder, applying on MNIST dataset.

Currently, the following models are supported:

  • ✔️ VAE
  • ✔️ Conv-VAE

2.Usage

python train.py

The code is self-explanatory, you can specify some customized options in train.py.

3.Result

Here are some visualization results:

3.1 Reconstruction results

Model epoch 10 epoch 20 epoch 30 epoch 40 epoch 50
VAE | |
Conv-VAE

3.2 Randomly generated results

Model epoch 10 epoch 20 epoch 30 epoch 40 epoch 50
VAE | |
Conv-VAE

4. Pre-trained model

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