tfdbg.LocalCLIDebugHook

Class LocalCLIDebugHook

Inherits From: SessionRunHook

Defined in tensorflow/python/debug/wrappers/hooks.py.

See the guide: TensorFlow Debugger > Session wrapper class and SessionRunHook implementations

Command-line-interface debugger hook.

Can be used as a hook for tf.train.MonitoredSessions and tf.estimator.Estimators. Provides a substitute for tfdbg.LocalCLIDebugWrapperSession in cases where the session is not directly available.

Methods

__init__

__init__(
    ui_type='curses',
    dump_root=None,
    thread_name_filter=None
)

Create a local debugger command-line interface (CLI) hook.

Args:

  • ui_type: (str) requested user-interface type. Currently supported: (curses | readline).
  • dump_root: (str) optional path to the dump root directory. Must be a directory that does not exist or an empty directory. If the directory does not exist, it will be created by the debugger core during debug run() calls and removed afterwards.
  • thread_name_filter: Regular-expression white list for threads on which the wrapper session will be active. See doc of BaseDebugWrapperSession for more details.

add_tensor_filter

add_tensor_filter(
    filter_name,
    tensor_filter
)

Add a tensor filter.

See doc of LocalCLIDebugWrapperSession.add_tensor_filter() for details. Override default behavior to accommodate the possibility of this method being called prior to the initialization of the underlying LocalCLIDebugWrapperSession object.

Args:

  • filter_name: See doc of LocalCLIDebugWrapperSession.add_tensor_filter() for details.
  • tensor_filter: See doc of LocalCLIDebugWrapperSession.add_tensor_filter() for details.

after_create_session

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.

Args:

  • session: A TensorFlow Session that has been created.
  • coord: A Coordinator object which keeps track of all threads.

after_run

after_run(
    run_context,
    run_values
)

before_run

before_run(run_context)

begin

begin()

end

end(session)

Called at the end of session.

The session argument can be used in case the hook wants to run final ops, such as saving a last checkpoint.

If session.run() raises exception other than OutOfRangeError or StopIteration then end() is not called. Note the difference between end() and after_run() behavior when session.run() raises OutOfRangeError or StopIteration. In that case end() is called but after_run() is not called.

Args:

  • session: A TensorFlow Session that will be soon closed.