hunk.code_window:             )
               vf_loss_clipped = torch.clamp(vf_loss, 0, self.config["vf_clip_param"])
               mean_vf_loss = reduce_mean_valid(vf_loss_clipped)
           # Ignore the value function.
           else:
               value_fn_out = torch.tensor(0.0).to(mean_policy_loss.device)
               vf_loss_clipped = mean_vf_loss = torch.tensor(0.0).to(
                   mean_policy_loss.device
               )
           total_loss = reduce_mean_valid(
               -surrogate_loss
               + self.config["vf_loss_coeff"] * vf_loss_clipped
  
hunk.labels: keep keep keep keep keep replace replace replace replace keep keep keep keep
hunk.after_edit:             value_fn_out = torch.tensor(0.0).to(surrogate_loss.device)
               vf_loss_clipped = mean_vf_loss = torch.tensor(0.0).to(surrogate_loss.device)
  
hunk.file_path: rllib/algorithms/ppo/ppo_torch_policy.py
hunk.type: replace
file: Avg placement group creating time: 0.2691924729741867 ms
  Avg placement group removing time: 0.8786630945927776 ms
  Stress Test succeed.