docs: stopping-based variant of adaptive search
@@ -629,6 +629,14 @@ large-scale experiments with hundreds or thousands of trials.
not explore as many configurations given the same budget. We
recommend using either ``aggressive`` or ``standard`` mode.
+``stop_once``
+ If ``stop_once`` is set to ``true``, we will use a variant of ASHA
+ that will not resume trials once stopped. This variant defaults to
+ continuing training and will only stop trials if there is enough
+ evidence to terminate training. We recommend using this version of
+ ASHA when training a trial for the max length as fast as possible is
+ important or when fault tolerance is too expensive.
+
``divisor``
The fraction of trials to keep at each rung, and also determines the
training length for each rung. The default setting is ``4``; only
