diff --git a/paddle/phi/api/yaml/generator/generate_sparse_op.py b/paddle/phi/api/yaml/generator/generate_sparse_op.py
index 48ba0d81eca3d621fb3e39c317a93da675544da1..22c6ef0866b346d51166be9cdf2c7c71bbb152e2 100644
--- a/paddle/phi/api/yaml/generator/generate_sparse_op.py
+++ b/paddle/phi/api/yaml/generator/generate_sparse_op.py
@@ -84,6 +84,8 @@ def main(
     backward_api_dict = to_named_dict(backward_apis)
 
     for api in apis:
+        if api['name'][-1] == '_':
+            api['name'] = api['name'][:-1]
         api['op_name'] = SPARSE_OP_PREFIX + api['name']
         api['name'] = api['op_name']
         if api["backward"] is not None:
diff --git a/paddle/phi/api/yaml/sparse_backward.yaml b/paddle/phi/api/yaml/sparse_backward.yaml
index 6503dbb46e85765c57945d2e02e9c8b707f3f233..d8250867398613c5da4593b1195a538428313c73 100644
--- a/paddle/phi/api/yaml/sparse_backward.yaml
+++ b/paddle/phi/api/yaml/sparse_backward.yaml
@@ -101,7 +101,7 @@
            atanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
 
 - backward_op : batch_norm_grad
-  forward : 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 : 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 mean_out, Tensor variance_out, 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 015e7aef0ff0b01f8655f059671eb9f29d19aea4..c3b39e5dc3d1fab8d11ea6c8d3fc78e36ad4e141 100644
--- a/paddle/phi/api/yaml/sparse_ops.yaml
+++ b/paddle/phi/api/yaml/sparse_ops.yaml
@@ -87,7 +87,7 @@
     layout : x
   backward : atanh_grad
 
-- op : batch_norm
+- op : 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 :
@@ -95,7 +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)
+  inplace : (mean -> mean_out), (variance -> variance_out)
   backward : batch_norm_grad
 
 - op : cast
diff --git a/paddle/phi/kernels/sparse/batch_norm_kernel.h b/paddle/phi/kernels/sparse/batch_norm_kernel.h
index 282a8de7b39d4cba940fc1dda140fffe5ce2b376..a94a1203c8cdc19870b2440e8772bc9853990d83 100644
--- a/paddle/phi/kernels/sparse/batch_norm_kernel.h
+++ b/paddle/phi/kernels/sparse/batch_norm_kernel.h
@@ -23,25 +23,25 @@ namespace phi {
 namespace sparse {
 
 template <typename T, typename Context>
-void BatchNormKernel(const Context& dev_ctx,
-                     const SparseCooTensor& x,
-                     const DenseTensor& scale,
-                     const DenseTensor& bias,
-                     const DenseTensor& mean,
-                     const DenseTensor& variance,
-                     float momentum,
-                     float epsilon,
-                     const std::string& data_layout,
-                     bool is_test,
-                     bool use_global_stats,
-                     bool trainable_statistics,
-                     bool fuse_with_relu,
-                     SparseCooTensor* y,
-                     DenseTensor* mean_out,
-                     DenseTensor* variance_out,
-                     DenseTensor* saved_mean,
-                     DenseTensor* saved_variance,
-                     DenseTensor* reserve_space);
+void BatchNormCooKernel(const Context& dev_ctx,
+                        const SparseCooTensor& x,
+                        const DenseTensor& scale,
+                        const DenseTensor& bias,
+                        const DenseTensor& mean,
+                        const DenseTensor& variance,
+                        float momentum,
+                        float epsilon,
+                        const std::string& data_layout,
+                        bool is_test,
+                        bool use_global_stats,
+                        bool trainable_statistics,
+                        bool fuse_with_relu,
+                        SparseCooTensor* y,
+                        DenseTensor* mean_out,
+                        DenseTensor* variance_out,
+                        DenseTensor* saved_mean,
+                        DenseTensor* saved_variance,
+                        DenseTensor* reserve_space);
 
 }  // namespace sparse
 }  // namespace phi
diff --git a/python/paddle/sparse/nn/layer/norm.py b/python/paddle/sparse/nn/layer/norm.py
index 34ed96f9e434cec316fc3a27cd2eae5eff686464..987e1835ecd0377d15501dab9a7dbe66b88b0dae 100644
--- a/python/paddle/sparse/nn/layer/norm.py
+++ b/python/paddle/sparse/nn/layer/norm.py
@@ -138,7 +138,7 @@ class BatchNorm(paddle.nn.BatchNorm1D):
         data_format = 'NCHW' if self._data_format[1] == 'C' else 'NHWC'
 
         if in_dynamic_mode():
-            batch_norm_out, _, _, _, _, _ = _C_ops.sparse_batch_norm(
+            batch_norm_out, _, _, _, _, _ = _C_ops.sparse_batch_norm_(
                 input,
                 self.weight,
                 self.bias,