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Vector Quantized Variational Autoencoders (VQ-VAE)


Implemenation of Vector Quantized Variational Autoencoders from scratch in python.

Step 1:


Setup environment:

conda env create -f environment.yml

Step 2:


Download dataset:
To download the dataset, at first, download the kaggle.json file from your kaggle profile and put it in the project directory. Navigate to your kaggle profile and download the .json file as shown below.

Now, run the following to download the celeba dataset.

python download_data.py

Step 3:


To train the model run:

python train.py

All the plots and model will be saved in the results directory.

Major credit: This Notebook

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