diff --git a/paddle/phi/api/yaml/generator/sparse_api_gen.py b/paddle/phi/api/yaml/generator/sparse_api_gen.py
index 4236862e347b320d7f3fe3ff80f5720a16f014a5..f013fed1b3ce1c0fb7720791b29e8f2e80bfa3d6 100644
--- a/paddle/phi/api/yaml/generator/sparse_api_gen.py
+++ b/paddle/phi/api/yaml/generator/sparse_api_gen.py
@@ -238,7 +238,7 @@ class SparseAPI(ForwardAPI):
                 kernel_name, inplace_flag)
 
         return f"""
-PADDLE_API {self.get_return_type()} {api_func_name}({self.get_define_args()}) {{
+PADDLE_API {self.get_return_type(inplace_flag)} {api_func_name}({self.get_define_args(inplace_flag)}) {{
 {kernel_dispatch_code}
   PADDLE_THROW(phi::errors::Unimplemented(
           "The kernel of ({self.api}) for input tensors is unimplemented, please check the type of input tensors."));
diff --git a/paddle/phi/api/yaml/sparse_backward.yaml b/paddle/phi/api/yaml/sparse_backward.yaml
index c57a3cae8927f3e10d4874e0a77518b0a371ede5..ffb5406436faa2f37eb0c6108366594b778ddadc 100644
--- a/paddle/phi/api/yaml/sparse_backward.yaml
+++ b/paddle/phi/api/yaml/sparse_backward.yaml
@@ -368,7 +368,7 @@
            subtract_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
 
 - backward_op : sync_batch_norm_grad
-  forward : sync_batch_norm(Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
+  forward : sync_batch_norm_(Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
   args : (Tensor x, Tensor scale, Tensor bias, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
   output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
   infer_meta :
diff --git a/paddle/phi/api/yaml/sparse_ops.yaml b/paddle/phi/api/yaml/sparse_ops.yaml
index 7921f423d859d6a2bd7f669dcd55d9e5ce371e00..a7111e5dee3c6b70b2127e9ee1330b6be95a957b 100644
--- a/paddle/phi/api/yaml/sparse_ops.yaml
+++ b/paddle/phi/api/yaml/sparse_ops.yaml
@@ -95,6 +95,7 @@
   kernel :
     func : batch_norm_coo {sparse_coo, dense, dense, dense, dense -> sparse_coo, dense, dense, dense, dense, dense}
     data_type : x
+  view : (mean -> mean_out), (variance -> variance_out)
   backward : batch_norm_grad
 
 - op : cast
@@ -480,7 +481,7 @@
     layout : x
   backward : transpose_grad
 
-- op : sync_batch_norm
+- op : sync_batch_norm_
   args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
   output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
   infer_meta :
@@ -489,6 +490,7 @@
     func : sync_batch_norm_coo{sparse_coo, dense, dense, dense, dense -> sparse_coo, dense, dense, dense, dense, dense}
     data_type : x
   backward : sync_batch_norm_grad
+  inplace : (mean -> mean_out), (variance -> variance_out)
 
 - op : reshape
   args : (Tensor x,  IntArray shape)
diff --git a/python/paddle/incubate/sparse/nn/layer/norm.py b/python/paddle/incubate/sparse/nn/layer/norm.py
index 440a08953951f2fe6ec1f8e1cc65a6f7eca7cf21..b84db710d732e11aae486942d4fb8e96f7d38f5a 100644
--- a/python/paddle/incubate/sparse/nn/layer/norm.py
+++ b/python/paddle/incubate/sparse/nn/layer/norm.py
@@ -297,7 +297,7 @@ class SyncBatchNorm(paddle.nn.SyncBatchNorm):
 
     def forward(self, x):
         self._check_data_format()
-        sync_batch_norm_out, _, _, _, _, _ = _C_ops.sparse_sync_batch_norm(
+        sync_batch_norm_out, _, _, _, _, _ = _C_ops.sparse_sync_batch_norm_(
             x, self.weight, self.bias, self._mean, self._variance,
             self._momentum, self._epsilon, self._data_format, not self.training,
             False, False, False)