Sound way of managing multiple sessions and graphs

Question

I\'d like to manage multiple Keras models in multiple sessions. My application is constructed such that models can be live at the same time, in addition to creating, saving and

Answer 1

EDIT: Actually, seeing again how K.get_session() works, it should return the current default session, so I'm not sure set_session is doing anything meaningful there. I'll leave the answer just in case you want to try but probably this won't help.

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Maybe you can get it to work with something like this:

from contextlib import contextmanager

class NN:
    def __init__(self):
        self.graph = tf.Graph()
        self.session = tf.Session(graph=self.graph)

    def predict(self, x):
        with self._context():
            return self.model.predict(x)

    @contextmanager
    def _context(self):
        prev_sess = K.get_session()
        K.set_session(self.session)
        with self.graph.as_default(), self.session.as_default():
            yield
        K.set_session(prev_sess)

Note that the Keras session object is a global variable, so I suppose this should work as long as you don't try to use these contexts from multiple threads.