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update target network weight during episode after x timesteps #2110

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Mdhvince
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@Mdhvince Mdhvince commented Nov 2, 2022

Currently the target network remain fixed during the entire episode.
In this PR I have moved the update of the weigths inside the inner loop of the training. So the update can occure during the episode.

Without this change, if the episode is too long, the target network will be too different from the behavior network.

cc @vmoens @nairbv

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@svekars svekars added the rl Issues related to reinforcement learning tutorial, DQN, and so on label Nov 3, 2022
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LGTM thanks for spotting this!

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Mdhvince commented Nov 3, 2022

You welcome, thanks to you 🔥

@svekars svekars merged commit 83d6fec into pytorch:master Nov 8, 2022
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4 participants