learning_rate_signal_handler.py

from chainer.training import extension
import signal


class LearningRateSignalHandler(extension.Extension):

    trigger = 1, 'epoch'

    def __init__(self, attr='lr', rate=0.1, signalnum=signal.SIGUSR1, optimizer=None):
        self.attr = attr
        self.rate = rate
        self.signalnum = signalnum
        self.optimizer = optimizer

        self.signal_received = False

    def initialize(self, trainer):
        def handler(_, __):
            self.signal_received = True

        signal.signal(self.signalnum, handler)

    def __call__(self, trainer):
        if not self.signal_received:
            return

        self.signal_received = False

        optimizer = self.optimizer or trainer.updater.get_optimizer('main')
        current_value = getattr(optimizer, self.attr)
        next_value = current_value * self.rate
        setattr(optimizer, self.attr, next_value)