Fix indexing issue

ml-agents/mlagents/trainers/optimizer/torch_optimizer.py

         init_values, _mem = self.critic.critic_pass(
             seq_obs, _mem, sequence_length=self.policy.sequence_length
         )
-        # Trim out padded part
+        # Trim out padded part, i.e. get last leftover number of elements
-            signal_name: [init_values[signal_name][leftover:]]
+            signal_name: [init_values[signal_name][-leftover:]]
             for signal_name in init_values.keys()
         }
 
                     next_value_estimate[k] = 0.0
             if agent_id in self.critic_memory_dict:
                 self.critic_memory_dict.pop(agent_id)
-        assert len(value_estimates["extrinsic"]) == batch.num_experiences
         return value_estimates, next_value_estimate, all_next_memories