|View source on GitHub|
Hook to extend calls to MonitoredSession.run().
Compat aliases for migration
See Migration guide for more details.
after_create_session( session, coord )
Called when new TensorFlow session is created.
This is called to signal the hooks that a new session has been created. This
has two essential differences with the situation in which
begin is called:
- When this is called, the graph is finalized and ops can no longer be added to the graph.
- This method will also be called as a result of recovering a wrapped session, not only at the beginning of the overall session.
||A TensorFlow Session that has been created.|
||A Coordinator object which keeps track of all threads.|
after_run( run_context, run_values )
Called after each call to run().
run_values argument contains results of requested ops/tensors by
run_context argument is the same one send to
run_context.request_stop() can be called to stop the iteration.
session.run() raises any exceptions then
after_run() is not called.
||A SessionRunValues object.|
before_run( run_context )
Called before each call to run().
You can return from this call a
SessionRunArgs object indicating ops or
tensors to add to the upcoming
run() call. These ops/tensors will be run
together with the ops/tensors originally passed to the original run() call.
The run args you return can also contain feeds to be added to the run()
run_context argument is a
SessionRunContext that provides
information about the upcoming
run() call: the originally requested
op/tensors, the TensorFlow Session.
At this point graph is finalized and you can not add ops.