Removed old comments
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@ -247,7 +247,6 @@ class TRL_PG(OnPolicyAlgorithm):
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# p = self.policy(rollout_data.observations)
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# proj_p = self.projection(self.policy, p, b_q = (b_old_mean, b_old_std), self._global_step)
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# new_logpacs = self.policy.log_probability(proj_p, b_actions)
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# log_prob == new_pogpacs (i think)
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# src of evaluate_actions:
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# pol = self.policy
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@ -279,8 +278,6 @@ class TRL_PG(OnPolicyAlgorithm):
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values = self.policy.value_net(latent_vf)
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entropy = proj_p.entropy()
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# log_prob = p.log_prob(actions)
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values = values.flatten()
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# Normalize advantage
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advantages = rollout_data.advantages
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