def apply_ema_weights(self):
"""
备份原模型权重，然后将平均权重应用到模型上去。
"""
self.old_weights = K.batch_get_value(self.model.weights)
ema_weights = K.batch_get_value(self.ema_weights)
K.batch_set_value(zip(self.model.weights, ema_weights))
def set_model(self, model):
"""
绑定模型，并初始化参数
"""
super(ExponentialMovingAverage, self).set_model(model)
self.ema_weights = [K.zeros(K.shape(w)) for w in model.weights]
self.old_weights = K.batch_get_value(model.weights)
K.batch_set_value(zip(self.ema_weights, self.old_weights))
self.updates = []
for w1, w2 in zip(self.ema_weights, model.weights):
op = K.moving_average_update(w1, w2, self.momentum)
self.updates.append(op)
def on_batch_end(self, batch, logs=None):
"""
每个batch后自动执行
"""
K.batch_get_value(self.updates)