[BugFix] fix import jit.marker.unified

fastdeploy/distributed/communication.py

@@ -77,22 +77,25 @@ def tensor_model_parallel_all_reduce(
 from paddle.distributed.communication import stream
 from paddle.distributed.communication.reduce import ReduceOp
 
+try:
+
+    def all_reduce(
+        tensor,
+        op,
+        group,
+        sync_op: bool = True,
+    ):
+        return stream.all_reduce(tensor, op=op, group=group, sync_op=sync_op, use_calc_stream=True)
 
-def all_reduce(
-    tensor,
-    op,
-    group,
-    sync_op: bool = True,
-):
-    return stream.all_reduce(tensor, op=op, group=group, sync_op=sync_op, use_calc_stream=True)
-
-
-@paddle.jit.marker.unified
-def tensor_model_parallel_all_reduce_custom(input_: paddle.Tensor) -> paddle.Tensor:
-    """All-reduce the input tensor across model parallel group on calc stream."""
-    if paddle.in_dynamic_mode():
-        hcg = dist.fleet.get_hybrid_communicate_group()
-        mp_group = hcg.get_model_parallel_group()
-        all_reduce(input_, op=ReduceOp.SUM, group=mp_group)
-    else:
-        dist.all_reduce(input_)
+    @paddle.jit.marker.unified
+    def tensor_model_parallel_all_reduce_custom(input_: paddle.Tensor) -> paddle.Tensor:
+        """All-reduce the input tensor across model parallel group on calc stream."""
+        if paddle.in_dynamic_mode():
+            hcg = dist.fleet.get_hybrid_communicate_group()
+            mp_group = hcg.get_model_parallel_group()
+            all_reduce(input_, op=ReduceOp.SUM, group=mp_group)
+        else:
+            dist.all_reduce(input_)
+
+except:
+    tensor_model_parallel_all_reduce_custom = None