See the guide: Training > Training Hooks
Delay execution until global step reaches to wait_until_step.
This hook delays execution until global step reaches to
is used to gradually start workers in distributed settings. One example usage
would be setting
wait_until_step=int(K*log(task_id+1)) assuming that
task_id=0 is the chief.
Create a _GlobalStepWaiterHook.
intshows until which global step should we wait.
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.
session: A TensorFlow Session that has been created.
coord: A Coordinator object which keeps track of all threads.
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.
run_values: A SessionRunValues object.
Called at the end of session.
session argument can be used in case the hook wants to run final ops,
such as saving a last checkpoint.
session: A TensorFlow Session that will be soon closed.