helper.py 文件源码

def on_epoch_end(self, epoch, logs={}):
        loss = logs.items()[1][1]  # get loss
        print "loss: ", loss
        old_lr = self.model.optimizer.lr.get_value()  # get old lr
        new_lr = old_lr * np.exp(loss)  # lr*exp(loss)
        k.set_value(self.model.optimizer.lr, new_lr)


# decaylr=LearningRateScheduler(decay_sch)


# checkpoint=ModelCheckpoint("weights/adam_noep{0}_batch{1}_seq_{2}.hdf5".format(\
# no_epochs,batch, seq_length), monitor='loss', verbose=0,
# save_best_only=True, save_weights_only=False, mode='min')