fix: fix broadcast_pyobj breaking VerlEngine (sgl-project#5997)

Author: ocss884

python/sglang/srt/entrypoints/verl_engine.py

@@ -37,6 +37,7 @@ def __init__(
         monkey_patch_torch_reductions()
         self._device_mesh_cpu = device_mesh_cpu
         self._tp_rank = device_mesh_cpu.get_local_rank()
+        self._rank = device_mesh_cpu.get_rank()
         self._tp_size = device_mesh_cpu.size()
         tp_size_per_node = self._tp_size // nnodes
         node_rank = self._tp_rank // tp_size_per_node
@@ -114,7 +115,7 @@ def generate(
         # Most naive implementation, can extract tensor and send via gloo if too slow
         [output] = broadcast_pyobj(
             data=[output],
-            rank=self._tp_rank,
+            rank=self._rank,
             dist_group=self._device_mesh_cpu.get_group(),
             src=self._device_mesh_cpu.mesh[0].item(),
             force_cpu_device=False,
@@ -157,7 +158,7 @@ def update_weights_from_tensor(
                 )
 
         if self._tp_rank == 0:
-            self._engine.tokenizer_manager.flush_cache()
+            self._engine.flush_cache()
 
     def release_memory_occupation(self):
         if self._tp_rank == 0:

python/sglang/srt/utils.py

@@ -897,7 +897,10 @@ def broadcast_pyobj(
     src: int = 0,
     force_cpu_device: bool = True,
 ):
-    """Broadcast inputs from rank=0 to all other ranks with torch.dist backend."""
+    """Broadcast inputs from src rank to all other ranks with torch.dist backend.
+    The `rank` here refer to the source rank on global process group (regardless
+    of dist_group argument).
+    """
     device = torch.device(
         "cuda" if torch.cuda.is_available() and not force_cpu_device else "cpu"
     )