Remove Old Files in ModelCheckpoint

[tpinetz]

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My problem with the current ModelCheckpoint callback is that when I pass in the validation accuracy as a parameter in the filename I get flooded with model checkpoints. To combat this I would propose a flag in the ModelCheckpoint called keep_only_last_file that checks if the old save should be deleted. In combination with the save_best_only flag only the best model is kept.

I would propose following API: keras.callbacks.ModelCheckpoint(filepath, monitor='val_loss', verbose=0, save_best_only=False, save_weights_only=False, keep_only_last_file=False, mode='auto', period=1). I am targeting everyone who wants to use the formatting options in the ModelCheckpoint without saving multiple models.

I can implement this myself.

[Zlash92]

Agreed. Would be very convenient to not store multiple checkpoints

[stale]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed after 30 days if no further activity occurs, but feel free to re-open a closed issue if needed.

[felix-hilden]

This can be achieved with using a file name with no formatting for epoch or loss. It's a suboptimal solution for the time being, but does work.

[Zlash92]

True, but the formatting options are pretty nice to have.

[liyxi]

And people may want to save more than only one checkpoints. I suppose we can have a feature just like keep_checkpoint_max in tf estimator:

tf.estimator.RunConfig(model_dir=model_dir,
                       keep_checkpoint_max=3)

[stefan-falk]

This really seems like an issue for a lot of people e.g.

• ModelCheckpoint should have a way to delete non-best model checkpoints as it goes tensorflow/tensorflow#30695
• Better (simpler!) model checkpointing tensorflow/tensorflow#33763

and of course this one.

I wonder, why is there no simple argument such as keep_checkpoint_max for the ModelCheckpoint?