tfdbg.LocalCLIDebugHook

class tfdbg.LocalCLIDebugHook

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

Command-line-interface debugger hook.

Can be used as a monitor/hook for tf.train.MonitoredSessions and tf.contrib.learn's Estimators and Experiments.

Properties

graph

sess_str

session

Methods

__init__(ui_type='curses')

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

Args:

• ui_type: (str) user-interface type.

add_tensor_filter(filter_name, tensor_filter)

Add a tensor filter.

Args:

• filter_name: (str) name of the filter.
• tensor_filter: (callable) the filter callable. See the doc string of DebugDumpDir.find() for more details about its signature.

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(run_context, run_values)

before_run(run_context)

begin()

close()

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.

Args:

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

invoke_node_stepper(node_stepper, restore_variable_values_on_exit=True)

Overrides method in base class to implement interactive node stepper.

Args:

• node_stepper: (stepper.NodeStepper) The underlying NodeStepper API object.
• restore_variable_values_on_exit: (bool) Whether any variables whose values have been altered during this node-stepper invocation should be restored to their old values when this invocation ends.

Returns:

The same return values as the Session.run() call on the same fetches as the NodeStepper.

on_run_end(request)

Overrides on-run-end callback.

Actions taken: 1) Load the debug dump. 2) Bring up the Analyzer CLI.

Args:

• request: An instance of OnSessionInitRequest.

Returns:

An instance of OnSessionInitResponse.

on_run_start(request)

Overrides on-run-start callback.

Invoke the CLI to let user choose what action to take: run / invoke_stepper.

Args:

• request: An instance of OnSessionInitRequest.

Returns:

An instance of OnSessionInitResponse.

Raises:

• RuntimeError: If user chooses to prematurely exit the debugger.

on_session_init(request)

Overrides on-session-init callback.

Args:

• request: An instance of OnSessionInitRequest.

Returns:

An instance of OnSessionInitResponse.

partial_run(handle, fetches, feed_dict=None)

partial_run_setup(fetches, feeds=None)

Sets up the feeds and fetches for partial runs in the session.

run(fetches, feed_dict=None, options=None, run_metadata=None)

Wrapper around Session.run() that inserts tensor watch options.

Args:

• fetches: Same as the fetches arg to regular Session.run().
• feed_dict: Same as the feed_dict arg to regular Session.run().
• options: Same as the options arg to regular Session.run().
• run_metadata: Same as the run_metadata arg to regular Session.run().

Returns:

Simply forwards the output of the wrapped Session.run() call.

Raises:

• ValueError: On invalid OnRunStartAction value.

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