chainer.training.triggers.EarlyStoppingTrigger¶
-
class
chainer.training.triggers.
EarlyStoppingTrigger
(check_trigger=(1, 'epoch'), monitor='main/loss', patients=3, mode='auto', verbose=False, max_trigger=(100, 'epoch'))[source]¶ Trigger for Early Stopping
It can be used as a stop trigger of
Trainer
to realize early stopping technique.This trigger works as follows. Within each check interval defined by the
check_trigger
argument, it monitors and accumulates the reported value at each iteration. At the end of each interval, it computes the mean of the accumulated values and compares it to the previous ones to maintain the best value. When it finds that the best value is not updated for some periods (defined by patients), this trigger fires.- Parameters
monitor (str) – The metric you want to monitor
check_trigger – Trigger that decides the comparison interval between current best value and new value. This must be a tuple in the form of
<int>, 'epoch'
or<int>, 'iteration'
which is passed toIntervalTrigger
.patients (int) – Counts to let the trigger be patient. The trigger will not fire until the condition is met for successive
patient
checks.mode (str) –
'max'
,'min'
, or'auto'
. It is used to determine how to compare the monitored values.verbose (bool) – Enable verbose output. If verbose is true, you can get more information
max_trigger – Upper bound of the number of training loops
Methods
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__eq__
()¶ Return self==value.
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__ne__
()¶ Return self!=value.
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__lt__
()¶ Return self<value.
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__le__
()¶ Return self<=value.
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__gt__
()¶ Return self>value.
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__ge__
()¶ Return self>=value.