Autoencoder layers (with tied encode and decode weights) for Keras
Tutorial: https://amiralavi.com/tied-autoencoders/
DenseLayerAutoencoder is a derived class of the Keras built-in Dense class.
To use DenseLayerAutoencoder, you call its constructor in exactly the same way as you would for Dense, but instead of passing in a units argument, you pass in a layer_sizes argument which is just a python list of the number of units that you want in each of your encoder layers (it assumes that your autoencoder will have a symmetric architecture, so you only specify the encoder sizes). An example:
inputs = Input(shape=(1000,))
x = DenseLayerAutoencoder([100, 50, 20], activation='tanh')(inputs)
model = Model(inputs=inputs, outputs=x)
print(model.summary())
DenseLayerAutoencoder also provides an encode and decode function (which are both called by the call function).