tensorflow 在优化器后面添加bn的ops依赖

# 构建训练节点 train_op = create_optimizer( total_loss, lr, optimizer_params, 1., variables_to_train, use_fp16=FLAGS.use_fp16)# 将优化器ops添加进依赖 update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS) update_ops.append(train_op) update_op = tf.group(*update_ops) with tf.control_dependencies([update_op]): train_tensor = tf.identity(total_loss, name='train_op') # 构建hook avg_logging_hooks = LogSessionRunHook(FLAGS.train_batch_size, 400) # 构建训练spec output_spec = tf.estimator.EstimatorSpec( mode=mode, loss=total_loss, train_op=train_tensor, scaffold=scaffold_fn, training_hooks=[avg_logging_hooks])