[CI][Nixl] Check kv cache layout during handshake

tests/v1/kv_connector/unit/test_nixl_connector.py

@@ -419,6 +419,52 @@ def test_concurrent_load_kv(
                     return
         raise TimeoutError("Took too long to complete async handshake.")
 
+    @patch(
+        "vllm.distributed.kv_transfer.kv_connector.v1.nixl_connector.NixlWrapper",
+        FakeNixlWrapper)
+    def test_handshake_fails_on_kv_cache_layout_mismatch(self, dist_init):
+        """
+        Verify that adding a remote agent fails if kv_cache_layout differs.
+        This test is only relevant for heterogeneous TP.
+        """
+        vllm_config = create_vllm_config()
+
+        # Mock TP world size to 2 to force heterogeneous TP when
+        # remote_tp_size=1
+        with patch(
+                "vllm.distributed.kv_transfer.kv_connector.v1.nixl_connector.get_tensor_model_parallel_world_size",  # noqa: E501
+                return_value=2):
+            # Initialize connector and worker (with fake NIXL wrapper)
+            connector = NixlConnector(vllm_config, KVConnectorRole.WORKER)
+            connector.connector_worker = FakeNixlConnectorWorker(
+                vllm_config, connector.engine_id, hand_shake_latency=0)
+            worker = connector.connector_worker
+
+            # Minimal local registration params used by add_remote_agent
+            worker.slot_size_bytes = 4096
+            worker.block_len = worker.slot_size_bytes * worker.block_size
+            worker.num_blocks = 1
+            worker.dst_num_blocks[worker.engine_id] = worker.num_blocks
+
+            # Metadata with different kv_cache_layout than local worker
+            mismatched_layout = "HND" if worker.kv_cache_layout != "HND" \
+                else "NHD"
+            meta = NixlAgentMetadata(
+                engine_id=FakeNixlConnectorWorker.REMOTE_ENGINE_ID,
+                agent_metadata=FakeNixlWrapper.AGENT_METADATA,
+                kv_caches_base_addr=[0],
+                num_blocks=1,
+                block_len=worker.block_len,
+                attn_backend_name=worker.backend_name,
+                kv_cache_layout=mismatched_layout,
+            )
+
+            # We don't check layout for homogeneous TP and MLA for now, as the
+            # whole block is moved.
+            worker.add_remote_agent(meta, remote_tp_size=2)
+            with pytest.raises(AssertionError):
+                worker.add_remote_agent(meta, remote_tp_size=1)
+
 
 # NOTE: resource cleanup in mp backend is a bit finicky, so the order in which
 # we put here is important. First run ray, it will clean up the resources, then

vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py

@@ -30,6 +30,7 @@
 from vllm.logger import init_logger
 from vllm.platforms import _Backend, current_platform
 from vllm.utils import make_zmq_path, make_zmq_socket
+from vllm.v1.attention.backends.utils import get_kv_cache_layout
 from vllm.v1.core.sched.output import SchedulerOutput
 from vllm.v1.request import RequestStatus
 
@@ -73,6 +74,7 @@ class NixlAgentMetadata(
     num_blocks: int
     block_len: int
     attn_backend_name: str
+    kv_cache_layout: str
 
 
 @dataclass
@@ -538,7 +540,9 @@ def __init__(self, vllm_config: VllmConfig, engine_id: str):
         attn_backend = backend_name_to_enum(self.backend_name)
         self._use_flashinfer = attn_backend == _Backend.FLASHINFER_VLLM_V1
         self._use_pallas_v1 = attn_backend == _Backend.PALLAS_VLLM_V1
+        self.kv_cache_layout = get_kv_cache_layout()
         logger.debug("Detected attention backend %s", self.backend_name)
+        logger.debug("Detected kv cache layout %s", self.kv_cache_layout)
 
         self._tp_size: dict[EngineId, int] = {self.engine_id: self.world_size}
         # With heterogeneous TP, P must wait for all assigned D TP workers to
@@ -839,7 +843,8 @@ def register_kv_caches(self, kv_caches: dict[str, torch.Tensor]):
             kv_caches_base_addr=self.kv_caches_base_addr[self.engine_id],
             num_blocks=self.num_blocks,
             block_len=self.block_len,
-            attn_backend_name=self.backend_name)
+            attn_backend_name=self.backend_name,
+            kv_cache_layout=self.kv_cache_layout)
         ready_event = threading.Event()
         self._nixl_handshake_listener_t = threading.Thread(
             target=self._nixl_handshake_listener,
@@ -900,8 +905,7 @@ def add_remote_agent(self,
             self._tp_size[engine_id] = remote_tp_size
         else:
             assert self._tp_size[engine_id] == remote_tp_size
-        # We may eventually enable this after asserting equality in cache
-        # layout and close outputs.
+        # TODO We may eventually want to skip enforcing the same attn backend.
         assert nixl_agent_meta.attn_backend_name == self.backend_name
 
         remote_agent_name = self.nixl_wrapper.add_remote_agent(
@@ -930,6 +934,9 @@ def add_remote_agent(self,
             if self._use_flashinfer:
                 # Account for joint KV in FlashInfer.
                 remote_block_size //= 2
+            if tp_ratio > 1:
+                # Heterogeneous TP expects same kv_cache_layout.
+                assert nixl_agent_meta.kv_cache_layout == self.kv_cache_layout
 
             assert nixl_agent_meta.block_len == self.block_len * tp_ratio, (
                 "Remote P worker KV layer cache must be of shape [2, N, "