如何用Python编写一个早期停止函数

Question

我的损失是这样的

loss = np.sum(np.square(A-B))

如何编写帮助函数来执行"早期停止";比如在卡拉斯?

目的:

如果损失上升或波动不大，则停止并得到A和B。

Answer 1

我查看了Keras源代码并找到了earlystop的代码。我基于它做了自己的回调:

class EarlyStoppingByLossVal(Callback):
def __init__(self, monitor='val_loss', value=0.00001, verbose=0):
super(Callback, self).__init__()
self.monitor = monitor
self.value = value
self.verbose = verbose
def on_epoch_end(self, epoch, logs={}):
current = logs.get(self.monitor)
if current is None:
warnings.warn("Early stopping requires %s available!" % self.monitor, RuntimeWarning)
if current < self.value:
if self.verbose > 0:
print("Epoch %05d: early stopping THR" % epoch)
self.model.stop_training = True

和用法:

callbacks = [
EarlyStoppingByLossVal(monitor='val_loss', value=0.00001, verbose=1),
# EarlyStopping(monitor='val_loss', patience=2, verbose=0),
ModelCheckpoint(
kfold_weights_path, monitor='val_loss', save_best_only=True, 
verbose=0
)
]
model.fit(
X_train.astype('float32'), Y_train,
batch_size=batch_size, nb_epoch=nb_epoch,
shuffle=True, verbose=1, validation_data=(X_valid, Y_valid),
callbacks=callbacks
)