A tfdbg hook that can be used with TensorBoard Debugger Plugin.
This hook is the same as
GrpcDebugHook, except that it uses a predefined
DebugIdentity debug ops with the
gated_grpc attribute set to
True, to allow the interactive enabling and disabling of tensor
2) watches all tensors in the graph.
This saves the need for the user to define a
__init__( grpc_debug_server_addresses, thread_name_filter=None, send_traceback_and_source_code=True, log_usage=True )
Constructor of TensorBoardDebugHook.
grpc_debug_server_addresses: gRPC address(es) of debug server(s), as a
strs. E.g., "localhost:2333", "grpc://localhost:2333", ["192.168.0.7:2333", "192.168.0.8:2333"].
thread_name_filter: Optional filter for thread names.
send_traceback_and_source_code: Whether traceback of graph elements and the source code are to be sent to the debug server(s).
log_usage: Whether the usage of this class is to be logged (if applicable).
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 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.
run_values: A SessionRunValues object.
Called right before a session is run.
run_context: A session_run_hook.SessionRunContext. Encapsulates information on the run.
A session_run_hook.SessionRunArgs object.
Called once before using the session.
When called, the default graph is the one that will be launched in the
session. The hook can modify the graph by adding new operations to it.
begin() call the graph will be finalized and the other callbacks
can not modify the graph anymore. Second call of
begin() on the same
graph, should not change the graph.
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.