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kid's Issues

Question about the KL penalty

In compute_reward() function in kid_policy.py kl penalty is calculated as below.
kl_penalty = self.kl_scale * ( (kid_last_probs * (kid_last_probs / norm_last_probs).log()).sum() )
But the equation in the paper is
image
I am a little bit confused because, as the comment of the function says norm_last_probs is pi, it is considered kid_last_probs and norm_last_probs should be changed. If I am wrong, please let me know.

How to train?

Nice work. Would the training code be open sourced?

Evaluate Scripts

Hi,
This paper is very interesting, can you share the evaluation scripts?
I find some trouble in the evaluation stage.

Thanks

Spacy EntityRuler

Hi, I try to use Spacy V3, but I got a warning that "The component 'entity_ruler' does not have any patterns defined."
So, should I specify a specific pattern for entity_ruler?

Thanks

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