在tensorflow中设置保存checkpoint的最大数量实例

技术  /  管理员 发布于 7年前   157

1、我就废话不多说了，直接上代码吧！

 # 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   })

以上这篇在tensorflow中设置保存checkpoint的最大数量实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。