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    在tensorflow中设置保存checkpoint的最大数量实例

    栏目:代码类 时间:2020-01-21 12:06

    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
       })

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