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disable pytype for n-step replay
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@ -463,7 +463,7 @@ class NstepReplayBuffer(ReplayBuffer):
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# Memory inneficient version but fast computation
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self.log_probs[unique_indices] = log_prob.cpu().numpy().flatten()
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# Add entropy term, only for n-step > 1
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rewards[:, 1:] = rewards[:, 1:] - self.ent_coef * self.log_probs[indices[:, 1:]]
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rewards[:, 1:] = rewards[:, 1:] - self.ent_coef * self.log_probs[indices[:, 1:]] # pytype: disable=attribute-error
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# we filter through the indices.
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# The immediate indice, i.e. col 0 needs to be 1, so we ensure that it is here using np.ones
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