[DeepEP] Gate DeepEP MNNVL on fabric support (#28942)

python/sglang/srt/layers/moe/token_dispatcher/deepep.py

@@ -68,6 +68,15 @@ _use_aiter = get_bool_env_var("SGLANG_USE_AITER") and is_hip()
 logger = logging.getLogger(__name__)
 
 
+def _is_mnnvl_fabric_supported() -> bool:
+    if not is_flashinfer_available():
+        return False
+
+    from flashinfer.comm.mnnvl import is_mnnvl_fabric_supported
+
+    return is_mnnvl_fabric_supported(torch.cuda.current_device())
+
+
 def _deepep_precompile_tp_barrier() -> None:
     # DeepEP's all-to-all operation has a much shorter timeout compared to torch.distributed,
     # so if different ranks compile at different speeds, it may quickly trigger a timeout.
@@ -234,11 +243,11 @@ class DeepEPBuffer:
                     f"Consider using --deepep-config to change the behavior."
                 )
 
+        use_mnnvl_fabric = _is_mnnvl_fabric_supported()
         buffer_kwargs = dict(
             low_latency_mode=deepep_mode.enable_low_latency(),
             num_qps_per_rank=num_qps_per_rank,
-            # TODO can be false when unneeded
-            allow_mnnvl=True,
+            allow_mnnvl=use_mnnvl_fabric,
         )
         # Use CU_MEM_HANDLE_TYPE_FABRIC on hardware that advertises MNNVL fabric
         # support, so cross-pod GB200/GB300 EP groups use
@@ -251,11 +260,8 @@ class DeepEPBuffer:
         #            auto-enables fabric in C++ when supported, so we skip it:
         #            https://github.com/fzyzcjy/DeepEP/blob/814e508537c6ffc775d59f6f1b9ba43f3a65968c/csrc/deep_ep.cpp#L52
         is_cu12 = get_cuda_version()[0] == 12
-        if not is_cu12 and is_flashinfer_available():
-            from flashinfer.comm.mnnvl import is_mnnvl_fabric_supported
-
-            if is_mnnvl_fabric_supported(torch.cuda.current_device()):
-                buffer_kwargs["use_fabric"] = True
+        if not is_cu12 and use_mnnvl_fabric:
+            buffer_kwargs["use_fabric"] = True
 
         cls._buffer = Buffer(group, num_nvl_bytes, num_rdma_bytes, **buffer_kwargs)
         return cls._buffer