To continue training an existing tensorflow model do I need to restore the session? I'm trying to work out the best way to integrate with EC2 spot instances that can be started and stopped.

Do I need to store the tf.session or can I just do load_model('myfile.h5') and continue with mymodel.fit(....checkpoint=...) which saves the model every epoch back to myfile.h5?
I managed to get it workng with just load_model and then continue with model.fit(...). My model is quite simple, using just Keras Input, LSTM and Dense layers with no variables or anything complex.