Tensorflow (tflearn) implementation of Convolutioanl sparse autoenocer, also known as Winner-Takes-All autoencoder [1].
To use:
ae = sparseAE(sess)
ae.build_model([None,28,28,1])
train the Autoencoder ae.train(X, valX, n_epochs=1) # valX for validation
compute the output for a certain input
out = ae.model.predict(X[0].reshape([-1, 28, 28, 1]))
get the weights of a certain layer
vars = tflearn.get_layer_variables_by_name('conv3') # in this case, it is the learned features
W = ae.model.get_weights(vars[0])
get output of encoder for certain input
m2 = tflearn.DNN(ae.sparse_rep, session=sess)
m2.predict(X[0].reshape([-1, 28, 28, 1]) )
save and load the model
ae.save('./sparseAE.tflearn')
ae.load('./sparseAE.tflearn')
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