1、我就廢話不多說了，直接上程式碼吧！

 # Set up a RunConfig to only save checkpoints once per training cycle.
 run_config = tf.estimator.RunConfig(save_checkpoints_secs=1e9,keep_checkpoint_max = 10)
 model = tf.estimator.Estimator(
   model_fn=deeplab_model_focal_class_imbalance_loss_adaptive.deeplabv3_plus_model_fn,model_dir=FLAGS.model_dir,config=run_config,params={
     'output_stride': FLAGS.output_stride,'batch_size': FLAGS.batch_size,'base_architecture': FLAGS.base_architecture,'pre_trained_model': FLAGS.pre_trained_model,'batch_norm_decay': _BATCH_NORM_DECAY,'num_classes': _NUM_CLASSES,'tensorboard_images_max_outputs': FLAGS.tensorboard_images_max_outputs,'weight_decay': FLAGS.weight_decay,'learning_rate_policy': FLAGS.learning_rate_policy,'num_train': _NUM_IMAGES['train'],'initial_learning_rate': FLAGS.initial_learning_rate,'max_iter': FLAGS.max_iter,'end_learning_rate': FLAGS.end_learning_rate,'power': _POWER,'momentum': _MOMENTUM,'freeze_batch_norm': FLAGS.freeze_batch_norm,'initial_global_step': FLAGS.initial_global_step
   })

以上這篇在tensorflow中設定儲存checkpoint的最大數量例項就是小編分享給大家的全部內容了，希望能給大家一個參考，也希望大家多多支援我們。