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[rllib] Improve model config documentation #2538

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pschafhalter opened this issue Aug 1, 2018 · 5 comments
Closed

[rllib] Improve model config documentation #2538

pschafhalter opened this issue Aug 1, 2018 · 5 comments

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@pschafhalter
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pschafhalter commented Aug 1, 2018

I've been trying to use the model config as much as possible to avoid writing custom models, but often the documentation is difficult to understand.

For example, to understand the conv_filters option, the documentation says that the model config is documented in the model catalog. In the source code, the model catalog documentation for conv_filters says "conv_filters", # Filter configuration. I had to grep the source code before finding out that conv_filters is a list of [out_channels, kernel, stride] from visionnet.py.

@ericl
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ericl commented Aug 1, 2018

Would you mind submitting any quick fixes as a PR?

Note that in general for customizations it's better to just write a custom model instead, it amounts to copying the model source code and registering it. The amount of stuff we can support in a config is limited.

@drozzy
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drozzy commented Jul 23, 2019

Related question on SO:

ValueError: No default configuration for obs shape [6, 94], you must specify `conv_filters` manually as a model option. Default configurations are only available for inputs of shape [42, 42, K] and [84, 84, K]. You may alternatively want to use a custom model or preprocessor.

"For the (6,94) case, is the "dim" supposed to be 6 or 94? Is the conv_filters fine leaving as is, or is a certain network architecture necessary for each shape? If so, where is the link?"

https://stackoverflow.com/questions/57151612/what-is-the-appropriate-conv-filter-specifications-for-custom-observation-space

@dano000
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dano000 commented Aug 18, 2019

I'm having the same issue here:

ValueError: No default configuration for obs shape [1, 5], you must specify `conv_filters` manually as a model option. Default configurations are only available for inputs of shape [42, 42, K] and [84, 84, K]. You may alternatively want to use a custom model or preprocessor.

@ericl
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ericl commented Aug 18, 2019 via email

@FruechteBini
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Hey guys, just found this thread. I am having a hard time implementing this aswell. I am a RL beginner.
My observation space is of shape = (4,5,5)
I found this regarding the observation shape:
image

I guess the "dim" would be 5 in my case but how do I calculate the "conv_filters"?

Thanks in advance, cheers!

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