How Are Variables Shared Between Concurrent `session.run(...)` Calls In Tensorflow?

If you make two concurrent calls to the same session, sess.run(...), how are variables concurrently accessed in tensorflow? Will each call see a snapshot of the variables as of th

Solution 1:

After doing some experimentation it appears that each call to sess.run(...) does indeed see a consistent point-in-time snapshot of the variables.

To test this I performed 2 big matrix multiply operations (taking about 10 sec each to complete), and updated a single, dependent, variable before, between, and after. In another thread I grabbed and printed that variable every 1/10th second to see if it picked up the change that occurred between operations while the first thread was still running. It did not, I only saw it's initial and final values. Therefore I conclude that variable changes are only visible outside of a specific call to sess.run(...) at the end of that run.