I have Python code that generates a deep convolutional neural network using Keras. I'm trying to save the model, but the result is gigantic (100s of MBs). I'd like to pare that down a bit to make something more manageable.
The problem is that model.save() stores (quoting the Keras FAQ):
If I'm not doing any more training, I think I just need the first two.
I can use model.to_json() to make a JSON string of the architecture and save that off, and model.save_weights() to make a separate file containing the weights. That's about a third the size of the full model.save() result. But I'm wondering if there's some way to store these in a single self-contained file? (Short of outputting two files, zipping them together, and deleting the originals.) Alternatively, maybe there's a way to delete the training configuration and optimizer state when training is complete, so that model.save() doesn't give me something nearly so big?
Thanks.
The save function of a Model has a parameter exactly for this, called include_optimizer, setting it to false will save the model without including the optimizer state, which should lead to a much smaller HDF5 file:
model.save("something.hdf5", include_optimizer=False)
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