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otouat avatar otouat commented on July 22, 2024 1

In the sample_normal method from ActorNetwork, we compute log_probs using log(1-actions+epsilon), however, action was defined before to be equal to tanh(actions)*max_actions, which may be superior to 0. By computing log_probs with tanh(actions) instead of tanh(actions)*max_actions, it may work ( it solves the same issue you have in my case using the Pendulum-v0 env)

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otouat avatar otouat commented on July 22, 2024 1

In the sample_normal method from ActorNetwork, we compute log_probs using log(1-actions+epsilon), however, action was defined before to be equal to tanh(actions)*max_actions, which may be superior to 0. By computing log_probs with tanh(actions) instead of tanh(actions)*max_actions, it may work ( it solves the same issue you have in my case using the Pendulum-v0 env)

Edit : tanh(actions)*max_actions may be superior to 1, which in return could mean that we get NaN

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peter890331 avatar peter890331 commented on July 22, 2024

Thanks @otouat, I just had the same problem with tensor([[nan]]), and here is a big THANK after two years !

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