feat: kvpress新增 runner 侧 KV 压缩状态/位置打通

vllm/v1/worker/gpu_model_runner.py

@@ -313,6 +313,14 @@ class GPUModelRunnerBase(LoRAModelRunnerMixin):
                                          device="cpu",
                                          pin_memory=self.pin_memory)
         self.positions_np = self.positions_cpu.numpy()
+        # KV positions are decoupled from logical positions when KV compression
+        # is enabled. We keep a separate buffer to avoid recomputing or
+        # overwriting `positions_np` (used for RoPE / input token lookup).
+        self.kv_positions_cpu = torch.zeros(self.max_num_tokens,
+                                            dtype=torch.int64,
+                                            device="cpu",
+                                            pin_memory=self.pin_memory)
+        self.kv_positions_np = self.kv_positions_cpu.numpy()
         self.query_start_loc_cpu = torch.zeros(self.max_num_reqs + 1,
                                                dtype=torch.int32,
                                                device="cpu",
@@ -448,6 +456,7 @@ class GPUModelRunnerBase(LoRAModelRunnerMixin):
                 generator=generator,
                 block_ids=new_req_data.block_ids,
                 num_computed_tokens=new_req_data.num_computed_tokens,
+                num_kv_tokens=new_req_data.num_kv_tokens,
                 output_token_ids=[],
                 lora_request=new_req_data.lora_request,
             )
@@ -497,11 +506,13 @@ class GPUModelRunnerBase(LoRAModelRunnerMixin):
         for i, req_id in enumerate(req_data.req_ids):
             req_state = self.requests[req_id]
             num_computed_tokens = req_data.num_computed_tokens[i]
+            num_kv_tokens = req_data.num_kv_tokens[i]
             new_block_ids = req_data.new_block_ids[i]
             resumed_from_preemption = req_data.resumed_from_preemption[i]
 
             # Update the cached states.
             req_state.num_computed_tokens = num_computed_tokens
+            req_state.num_kv_tokens = num_kv_tokens
             spec_token_ids = (
                 scheduler_output.scheduled_spec_decode_tokens.get(req_id, ()))
 
@@ -545,7 +556,11 @@ class GPUModelRunnerBase(LoRAModelRunnerMixin):
             # Update the persistent batch.
             self.input_batch.num_computed_tokens_cpu[req_index] = (
                 num_computed_tokens)
-            self.input_batch.block_table.append_row(new_block_ids, req_index)
+            self.input_batch.num_kv_tokens_cpu[req_index] = num_kv_tokens
+            if resumed_from_preemption:
+                self.input_batch.block_table.add_row(new_block_ids, req_index)
+            else:
+                self.input_batch.block_table.append_row(new_block_ids, req_index)
 
             # For the last rank, we don't need to update the token_ids_cpu
             # because the sampled tokens are already cached.