A debugger hook that dumps debug data to filesystem.
Can be used as a monitor/hook for
__init__( session_root, watch_fn=None, thread_name_filter=None, log_usage=True )
Create a local debugger command-line interface (CLI) hook.
session_root: See doc of
watch_fn: See doc of
thread_name_filter: Regular-expression white list for threads on which the wrapper session will be active. See doc of
BaseDebugWrapperSessionfor more details.
log_usage: (bool) Whether usage is to be logged.
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.
session: A TensorFlow Session that has been created.
coord: A Coordinator object which keeps track of all threads.
after_run( run_context, run_values )
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.run() raises exception other than OutOfRangeError or
end() is not called.
Note the difference between
after_run() behavior when
session.run() raises OutOfRangeError or StopIteration. In that case
end() is called but
after_run() is not called.
session: A TensorFlow Session that will be soon closed.