[fix]修复开并行解码后，speculative-disable-by-batch-size设的比测试的batch小的话可能出现的数组越界问题

vllm/sequence.py

@@ -1300,17 +1300,36 @@ class HiddenStates(msgspec.Struct, array_like=True,
         """Update hidden states from target model invocation. Only used for
         decode steps"""
         assert len(seq_group_metadata_list) == len(hidden_states)
-        self._seq_ids.extend(get_all_seq_ids(seq_group_metadata_list))
+        # self._seq_ids.extend(get_all_seq_ids(seq_group_metadata_list))
+
+        # self.hidden_states = torch.cat([self.hidden_states, hidden_states])
+
+        # if self.second_last_token_hidden_states is not None:
+        #     # Adding dummy hidden_states to this to maintain same shape
+        #     self.second_last_token_hidden_states = torch.cat([
+        #         self.second_last_token_hidden_states,
+        #         torch.zeros_like(hidden_states)
+        #         if second_last_token_hidden_states is None else
+        #         second_last_token_hidden_states
+        #     ])
+        seq_ids = get_all_seq_ids(seq_group_metadata_list)
+        diff_seq_ids = [item for item in self._seq_ids if item not in seq_ids]
+        index = [self._seq_ids.index(seq_id) for seq_id in diff_seq_ids]
+        self._seq_ids = diff_seq_ids
+        self.hidden_states = self.hidden_states[index]
         self.hidden_states = torch.cat([self.hidden_states, hidden_states])
 
         if self.second_last_token_hidden_states is not None:
             # Adding dummy hidden_states to this to maintain same shape
+            self.second_last_token_hidden_states = self.second_last_token_hidden_states[index]
             self.second_last_token_hidden_states = torch.cat([
                 self.second_last_token_hidden_states,
                 torch.zeros_like(hidden_states)
                 if second_last_token_hidden_states is None else
                 second_last_token_hidden_states
             ])
+        self._seq_ids.extend(seq_ids)
+
 
     def prune(self,
               seq_group_metadata_list: List[SequenceGroupMetadata]) -> None:

vllm/spec_decode/spec_decode_worker.py

@@ -691,7 +691,6 @@ class SpecDecodeWorker(LoraNotSupportedWorkerBase):
                     torch.where(sampler_output.sampled_token_ids -
                                 VLLM_INVALID_TOKEN_ID)[0]]
             
-            if not skip_proposer:
             if self.previous_hidden_states is None and len(
                     seq_group_meta_with_hidden):
                 self.previous_hidden_states = HiddenStates(