vessel_characterization.py 文件源码

def build_training_net(self, features, timestamps, mmsis):
        self._build_model(features, timestamps, mmsis, is_training=True)

        trainers = []
        for i in range(len(self.training_objectives)):
            trainers.append(self.training_objectives[i].build_trainer(
                timestamps, mmsis))

        learning_rate = tf.train.exponential_decay(
            self.initial_learning_rate, slim.get_or_create_global_step(), 
            self.decay_examples, self.learning_decay_rate)

        optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)

        return TrainNetInfo(optimizer, trainers)