fix(nyz): fix marl nstep td compatibility bug

Author: PaParaZz1

ding/policy/madqn.py

@@ -198,7 +198,7 @@ def _forward_learn(self, data: dict) -> Dict[str, Any]:
             td_error_per_sample = []
             for t in range(self._cfg.collect.unroll_len):
                 v_data = v_nstep_td_data(
-                    total_q[t], target_total_q[t], data['reward'][t], data['done'][t], data['weight'], self._gamma
+                    total_q[t], target_total_q[t], data['reward'][t], data['done'][t], data['weight'], None
                 )
                 # calculate v_nstep_td critic_loss
                 loss_i, td_error_per_sample_i = v_nstep_td_error(v_data, self._gamma, self._nstep)
@@ -231,8 +231,12 @@ def _forward_learn(self, data: dict) -> Dict[str, Any]:
             cooperation_loss_all = []
             for t in range(self._cfg.collect.unroll_len):
                 v_data = v_nstep_td_data(
-                    cooperation_total_q[t], cooperation_target_total_q[t], data['reward'][t], data['done'][t],
-                    data['weight'], self._gamma
+                    cooperation_total_q[t],
+                    cooperation_target_total_q[t],
+                    data['reward'][t],
+                    data['done'][t],
+                    data['weight'],
+                    None,
                 )
                 cooperation_loss, _ = v_nstep_td_error(v_data, self._gamma, self._nstep)
                 cooperation_loss_all.append(cooperation_loss)