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It would be nice to make modelfree.hyperparams.train_rl a tune.Trainable rather than a function, adding checkpointing support. This would let us use the HyperBand and Population Based Training schedulers. Conceptually this is easy enough: we already supporting saving models via save_callbacks, and can restore using load_path. However, the interfaces don't quite line up: Ray expects _train to perform one small training step, with _save called in between. There's no good way to make Stable Baselines return part-way. We could call it repeatedly with small total_timesteps, but this would make the progress be wrong, breaking annealers.
The text was updated successfully, but these errors were encountered:
It would be nice to make
modelfree.hyperparams.train_rl
a tune.Trainable rather than a function, adding checkpointing support. This would let us use the HyperBand and Population Based Training schedulers. Conceptually this is easy enough: we already supporting saving models viasave_callbacks
, and can restore usingload_path
. However, the interfaces don't quite line up: Ray expects_train
to perform one small training step, with_save
called in between. There's no good way to make Stable Baselines return part-way. We could call it repeatedly with smalltotal_timesteps
, but this would make the progress be wrong, breaking annealers.The text was updated successfully, but these errors were encountered: