A framework to explore the latent space of autoencoders implemented in torch
Project description
lightcone
A framework to explore the latent space of convolutional autoencoders
implemented in pytorch
.
Example
Compose your decoder and your encoder into the lightcone
autoencoder:
from lightcone.models import AutoEncoder
model = AutoEncoder(encoder=your_encoder, decoder=your_decoder)
After model
has been training, the latent space can be explored in a
Jupyter-Notebook as follows
model.explore(data_loader=your_data_loader)
Jupyter Dash
Make sure to install and activate the Jupyter notebook extenstion
jupyter nbextension install --py jupyter_dash
jupyter nbextension enable --py jupyter_dash
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