Adds perceptive actor-critic class #114
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rsl_rl/networks/cnn.py
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| if self.flatten: | ||
| x = x.flatten(start_dim=1) | ||
| elif self.avgpool is not None: | ||
| x = self.avgpool(x) | ||
| x = x.flatten(start_dim=1) | ||
| return x |
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I don't get this logic. Why do we always flatten when we do avgpool and why do we not do avgpool when we also set the flatten flag?
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@pascal-roth I modified the CNN quite a bit to have more flexibility. Could you quickly check if this version works for you and maybe also give it a quick check? I also modified your perceptive environment configs to work with the changes here, it would be awesome if you could run the env to see if it still trains the same :) |
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Hello! I was following the progress of this PR and I had a question whether it makes sense to extend this ActorCriticPerceptive to have a shared CNN backbone for both critic and actor? Do you think it should be an option or should it be needed at all? I thought it can greatly simplify the complexity of neural network and speed up the training process. |
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Hi @lvjonok, I would assume the speedup is negligible. But if you want to test this please share the results :) |
Adds a new perceptive actor-critic class, that can define CNN layers for every 2D observation term.
Example usage shown in IsaacLab isaac-sim/IsaacLab#3467