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fix: logical error in gradient shaping algorithm #2

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fix: logical error in gradient shaping algorithm #2

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2 changes: 1 addition & 1 deletion GradS/fsrl/policy/lagrangian_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -250,7 +250,7 @@ def safety_loss(self, values: List, required_GS = True) -> Tuple[torch.tensor, d

for index_j in index_list:
sim_ij = torch.mean(cos(safety_loss_grad_list[index_i], safety_loss_grad_list[index_j])).item()
sim_list.append(sim_ij)
sim_list.append(sim_ij)

if np.max(np.array(sim_list)) < self.sim_threshold and np.min(np.array(sim_list)) > -1 * self.conflicting_threshold:
index_list.append(index_i)
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