I have created an autoencoder using a separate encoder and decoder as described in this link.
Split autoencoder on encoder and decoder keras
I am checkpointing my autoencoder as followed. How do I save the encoder and decoder separately corresponding to the autoencoder? Alternatively, can I extract deep encoder and decoder from my save autoencoder?
checkpoint = ModelCheckpoint(filepath, monitor='val_accuracy', verbose = 1, save_best_only=True, mode='max') callbacks_list = [checkpoint] autoencoder.fit( x=x_train, y=x_train, epochs=10, batch_size=128, shuffle=True, validation_data=(x_test, x_test), callbacks=callbacks_list )
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Answer
You could try to overwrite the autoencoder’s save function, which the ModelCheckpoint uses, to have it save the encoder and decoder Models separately instead.
def custom_save(filepath, *args, **kwargs): """ Overwrite save function to save the two sub-models """ global encoder, decoder # fix name path, ext = os.path.splitext(filepath) # save encoder/decoder separately encoder.save(path + '-encoder.h5', *args, **kwargs) decoder.save(path + '-decoder.h5', *args, **kwargs) auto_encoder = Model(auto_input, decoded) setattr(auto_encoder, 'save', custom_save)
Make sure to set the save function BEFORE fit.