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def compute_loss(logits, actions, rewards, β=0.01):
π = F.softmax(logits, dim=-1)
log_π = F.log_softmax(logits, dim=-1)
log_π_taken = log_π.gather(-1, actions.unsqueeze(-1)).squeeze(-1)
H = -torch.sum(π * log_π, dim=-1)
return -(log_π_taken * rewards + β * H).mean()
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