在tensorflow中设置保存checkpoint的最大数量实例

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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原文链接：https://blog.csdn.net/lfs666666/article/details/85377406