diff --git a/src/ATen/native/xpu/sycl/GroupNormKernels.cpp b/src/ATen/native/xpu/sycl/GroupNormKernels.cpp
index 935ab99f7..4038007e6 100644
--- a/src/ATen/native/xpu/sycl/GroupNormKernels.cpp
+++ b/src/ATen/native/xpu/sycl/GroupNormKernels.cpp
@@ -6,6 +6,7 @@
 #include <ATen/native/xpu/sycl/GroupReduceUtils.h>
 #include <ATen/native/xpu/sycl/Loops.h>
 #include <ATen/native/xpu/sycl/SharedReduceOps.h>
+#include <ATen/ops/ones.h>
 #include <comm/MemoryFormat.h>
 #include <comm/XPUMathCompat.h>
 #include <comm/xpu_aten.h>
@@ -1408,7 +1409,7 @@ void group_norm_backward_kernel_impl(
     Tensor c3 = at::empty({N, G}, X.options().dtype(kAccType));
     T_ACC* c2_data = c2.mutable_data_ptr<T_ACC>();
     T_ACC* c3_data = c3.mutable_data_ptr<T_ACC>();
-
+    Tensor dummy_gamma = at::ones({1, G, D}, X.options().dtype(kAccType));
     if (gamma.defined()) {
       auto iter = TensorIteratorConfig()
                       .check_all_same_dtype(std::is_same<T, T_ACC>::value)
@@ -1417,6 +1418,14 @@ void group_norm_backward_kernel_impl(
                       .add_owned_const_input(gamma.view({1, G, D}))
                       .build();
       gpu_kernel(iter, GroupNormBackwardC1Functor<T, T_ACC>());
+    } else {
+      auto iter = TensorIteratorConfig()
+                      .check_all_same_dtype(std::is_same<T, T_ACC>::value)
+                      .add_output(c1)
+                      .add_owned_const_input(rstd.view({N, G, 1}))
+                      .add_owned_const_input(dummy_gamma.view({1, G, D}))
+                      .build();
+      gpu_kernel(iter, GroupNormBackwardC1Functor<T, T_ACC>());
     }
 
     wg_size = (C / G) < get_group_reduce_group_size(simd)
@@ -1440,31 +1449,17 @@ void group_norm_backward_kernel_impl(
         c2_data,
         c3_data);
 
-    if (gamma.defined()) {
-      auto iter = TensorIteratorConfig()
-                      .check_all_same_dtype(std::is_same<T, T_ACC>::value)
-                      .resize_outputs(false)
-                      .add_owned_output(dX.view({N * G, D, HxW}))
-                      .add_owned_const_input(dY.view({N * G, D, HxW}))
-                      .add_owned_const_input(X.view({N * G, D, HxW}))
-                      .add_owned_const_input(c1.view({N * G, D, 1}))
-                      .add_owned_const_input(c2.view({N * G, 1, 1}))
-                      .add_owned_const_input(c3.view({N * G, 1, 1}))
-                      .build();
-      gpu_kernel(iter, GroupNormBackwardDXFunctor<T, T_ACC>());
-    } else {
-      auto iter = TensorIteratorConfig()
-                      .check_all_same_dtype(std::is_same<T, T_ACC>::value)
-                      .resize_outputs(false)
-                      .add_owned_output(dX.view({N * G, D * HxW}))
-                      .add_owned_const_input(dY.view({N * G, D * HxW}))
-                      .add_owned_const_input(X.view({N * G, D * HxW}))
-                      .add_owned_const_input(rstd.view({N * G, 1}))
-                      .add_owned_const_input(c2.view({N * G, 1}))
-                      .add_owned_const_input(c3.view({N * G, 1}))
-                      .build();
-      gpu_kernel(iter, GroupNormBackwardDXFunctor<T, T_ACC>());
-    }
+    auto iter = TensorIteratorConfig()
+                    .check_all_same_dtype(std::is_same<T, T_ACC>::value)
+                    .resize_outputs(false)
+                    .add_owned_output(dX.view({N * G, D, HxW}))
+                    .add_owned_const_input(dY.view({N * G, D, HxW}))
+                    .add_owned_const_input(X.view({N * G, D, HxW}))
+                    .add_owned_const_input(c1.view({N * G, D, 1}))
+                    .add_owned_const_input(c2.view({N * G, 1, 1}))
+                    .add_owned_const_input(c3.view({N * G, 1, 1}))
+                    .build();
+    gpu_kernel(iter, GroupNormBackwardDXFunctor<T, T_ACC>());
   }
 
   if (dgamma.defined() || dbeta.defined()) {