From 0560c8babdaec0561e9cdb935802ce15d3e784a2 Mon Sep 17 00:00:00 2001
From: hanchao <chao1.han@intel.com>
Date: Mon, 2 Dec 2024 05:22:00 +0000
Subject: [PATCH] update

---
 torch/_C/_distributed_c10d.pyi        |  1 -
 torch/distributed/distributed_c10d.py | 10 +++-------
 2 files changed, 3 insertions(+), 8 deletions(-)

diff --git a/torch/_C/_distributed_c10d.pyi b/torch/_C/_distributed_c10d.pyi
index ab59afc88b610b..df065a68b8ef8b 100644
--- a/torch/_C/_distributed_c10d.pyi
+++ b/torch/_C/_distributed_c10d.pyi
@@ -687,4 +687,3 @@ class ProcessGroupXCCL(Backend):
         rank: int,
         size: int,
     ): ...
-    
\ No newline at end of file
diff --git a/torch/distributed/distributed_c10d.py b/torch/distributed/distributed_c10d.py
index 8d18edee42059e..18d1f418180f83 100644
--- a/torch/distributed/distributed_c10d.py
+++ b/torch/distributed/distributed_c10d.py
@@ -354,7 +354,7 @@ def register_backend(
                 "`cuda`. Please specify it via the `devices` argument of "
                 "`register_backend`."
             )
-            Backend.backend_capability[name.lower()] = ["cpu", "cuda", "xpu"]
+            Backend.backend_capability[name.lower()] = ["cpu", "cuda"]
         elif isinstance(devices, str):
             # Single device string specified. Simply convert to list.
             Backend.backend_capability[name.lower()] = [devices]
@@ -1910,10 +1910,6 @@ def _new_process_group_helper(
         elif backend_str == Backend.XCCL:
             if not is_xccl_available():
                 raise RuntimeError("Distributed package doesn't have XCCL built in")
-            if backend_options is not None:
-                assert isinstance(
-                    backend_options, ProcessGroupXCCL.Options
-                ), "Expected backend_options argument to be of type ProcessGroupXCCL.Options"
             backend_class = ProcessGroupXCCL(
                 backend_prefix_store, group_rank, group_size
             )
@@ -2726,7 +2722,7 @@ def all_reduce(tensor, op=ReduceOp.SUM, group=None, async_op=False):
             return _IllegalWork()
         else:
             return None
-        
+
     work = group.allreduce([tensor], opts)
 
     if async_op:
@@ -4091,7 +4087,7 @@ def reduce_scatter_tensor(output, input, op=ReduceOp.SUM, group=None, async_op=F
             return _IllegalWork()
         else:
             return None
-        
+
     work = group._reduce_scatter_base(output, input, opts)
 
     if async_op: