I'm looking for some more detailed documentation about flyte checkpoints from the doc it appears

current_context().checkpoint

returns a file like object - but no further details are provided specifically I'd like to know if there are integrations with frameworks like keras (the native keras checkpointing mechanism expects a directory, not a single file) and if not, is there a mechanism to write a new file instead of appending to a single file

Cc @boundless-pizza-95864 did you have an integration with huggingface

We're checkpointing directories (coming from the huggingface trainer in our case). You can use the save/restore methods on a

Checkpoint

instance they work with directories

Do you happen to have an example?

Here’s what we essentially do for saving. I haven’t used Keras for a while but if you can get the path of the current checkpoint in a callback, you should be able to do the same:

cp: Checkpoint = flytekit.current_context().checkpoint
checkpoint_path = <your_local_checkpoint_path>
cp.save(checkpoint_path)