add qwen3

vllm-v0.6.2/vllm/distributed/device_communicators/xpu_communicator.py

@@ -0,0 +1,47 @@
+import torch
+import torch.distributed as dist
+from torch.distributed import ProcessGroup
+
+from vllm.platforms import current_platform
+
+
+class XpuCommunicator:
+
+    def __init__(self, group: ProcessGroup):
+        if not current_platform.is_xpu():
+            self.disabled = True
+            return
+        self.disabled = False
+        self.group = group
+        self.world_size = dist.get_world_size(self.group)
+
+    def all_reduce(self, x: torch.Tensor) -> torch.Tensor:
+        dist.all_reduce(x, group=self.group)
+        return x
+
+    def gather(self,
+               input_: torch.Tensor,
+               rank_in_group: int,
+               dst: int = 0,
+               dim: int = -1):
+        # For xpu path, gather doesn't work properly together with ray
+        # cluster so we use all_gather instead for now.
+        input_size = input_.size()
+        # Allocate output tensor.
+        output_tensor = torch.empty((self.world_size, ) + input_size,
+                                    dtype=input_.dtype,
+                                    device=input_.device)
+        # All-gather.
+        torch.distributed.all_gather_into_tensor(output_tensor,
+                                                 input_,
+                                                 group=self.group)
+        if rank_in_group == dst:
+            # Reshape
+            output_tensor = output_tensor.movedim(0, dim)
+            output_tensor = output_tensor.reshape(input_size[:dim] +
+                                                  (self.world_size *
+                                                   input_size[dim], ) +
+                                                  input_size[dim + 1:])
+        else:
+            output_tensor = None
+        return output_tensor