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policy_kwargs not documented in DQN #2035

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pstahlhofen opened this issue Nov 6, 2024 · 5 comments
Open
2 tasks done

policy_kwargs not documented in DQN #2035

pstahlhofen opened this issue Nov 6, 2024 · 5 comments
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documentation Improvements or additions to documentation good first issue Good for newcomers help wanted Help from contributors is welcomed

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@pstahlhofen
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πŸ“š Documentation

Currently, the documentation of DQN on the policy_kwargs parameter states the following:

policy_kwargs (Dict[str, Any] | None) – additional arguments to be passed to the policy on creation

A list of policy keyword arguments and their default settings would be very helpful here. If you think that this would take to much space, please at least add a hint to the possible policy classes and document the keyword arguments there. Spending some time reading the source code, I found the following keyword arguments for MlpPolicy:

  • net_arch
  • activation_fn
  • featuers_extractor_class
  • features_extractor_kwargs
  • normalize_images
  • optimizer_class
  • optimizer_kwargs

For other people interested in customizing those parameters: In dqn/policies.py you will find the relevant code for DQN. This can be used as a starting point as long as the documentation is not complete.

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@pstahlhofen pstahlhofen added the documentation Improvements or additions to documentation label Nov 6, 2024
@pstahlhofen
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Okay, I agree that it's not completely unfindable. But yes, I still think a link would be helpful here.

@araffin
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araffin commented Nov 7, 2024

Could you do a PR that links the two ? (using rst command :ref: probably and for all algorithms)

@araffin araffin added the help wanted Help from contributors is welcomed label Nov 7, 2024
@pstahlhofen
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I've never done anything with rst before. I think it would be better if someone could do it who has experience with that

@araffin araffin added the good first issue Good for newcomers label Nov 8, 2024
@pstahlhofen
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I have never worked with rst before, so maybe someone more experienced could do it

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