How to get encoder and decoder parts of autoencoder in order to stack them?
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ytzhak goussha on 22 Jun 2021
I want to represent 128x128 images in a 1x64 vector, and for that I want to use autoencoders.
I have trained autoencoders in stages following the example in "Train Stacked Autoencoders for Image Classificatio".
However, I dont want to build a classifier, I want to build an autoencoder to embedd images.
(I tried build my own autoencoder with CNNs without using the built in autoencoder functions but I can't get good results for some reason)
Following the example I created two autoencoders, and added another one of my own instead of the softmax output and trained them:
encoder1 : 128x128 ->256-> 128x128
encoder2 : 256->128->256
encoder3 : 128->64->128
But how do I combine them?
If I use the "stack" function on these encoders like in the example:
stackednet = stack(encoder1,encoder2,encoder3)
I get this transformation :
128x128 -> 256 -> 128 -> 64
but what I want is this:
128x128 -> 256 -> 128 -> 64 ->128 -> 256 -> 128x128
So basicaly I need to stack this:
stackednet = stack(encoder1-encoder,encoder2-encoder,encoder3-encoder,encoder3-decoder,encoder2-decoder,encoder1-decoder)
Is there a way to extract the encoder and the decoder parts from an Autoencoder object and then stack them?
David Willingham on 23 Jun 2021
That example is using the older Neural Networks functionalilty. I'd recommend looking at one of the examples using the newer framework like this one here: Train Variational Autoencoder (VAE) to Generate Images.