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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