kmeans.py 文件源码

def _get_train_ops(self, features, _):
    (_,
     _,
     losses,
     training_op) = clustering_ops.KMeans(
         self._parse_tensor_or_dict(features),
         self._num_clusters,
         self._training_initial_clusters,
         self._distance_metric,
         self._use_mini_batch,
         random_seed=self._random_seed,
         kmeans_plus_plus_num_retries=self.kmeans_plus_plus_num_retries
     ).training_graph()
    incr_step = tf.assign_add(tf.contrib.framework.get_global_step(), 1)
    self._loss = tf.reduce_sum(losses)
    training_op = with_dependencies([training_op, incr_step], self._loss)
    return training_op, self._loss