See the guide: Training > Training Hooks
Hook that requests stop at a specified step.
__init__( num_steps=None, last_step=None )
This hook requests stop after either a number of steps have been executed or a last step has been reached. Only one of the two options can be specified.
num_steps is specified, it indicates the number of steps to execute
begin() is called. If instead
last_step is specified, it
indicates the last step we want to execute, as passed to the
num_steps: Number of steps to execute.
last_step: Step after which to stop.
ValueError: If one of the arguments is invalid.
after_create_session( session, coord )
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.