diff --git a/paddle/fluid/pir/dialect/operator/interface/layout_transformation.cc b/paddle/fluid/pir/dialect/operator/interface/layout_transformation.cc
index a1fffa7991750d..231c8b26cdb1b6 100644
--- a/paddle/fluid/pir/dialect/operator/interface/layout_transformation.cc
+++ b/paddle/fluid/pir/dialect/operator/interface/layout_transformation.cc
@@ -39,13 +39,13 @@ std::vector<pir::Value> RelevantOutputsImpl<AddGroupNormSiluOp>(
 }
 
 template <>
-common::DataLayout PreferLayoutImpl<AddGroupNormSiluOp>(pir::Operation* op) {
+DataLayout PreferLayoutImpl<AddGroupNormSiluOp>(pir::Operation* op) {
   // Note(bukejiyu): add_group_norm_silu only supports NHWC layout now.
-  return common::DataLayout::NHWC;
+  return DataLayout::NHWC;
 }
 
 template <>
-common::DataLayout PreferLayoutImpl<Conv2dOp>(pir::Operation* op) {
+DataLayout PreferLayoutImpl<Conv2dOp>(pir::Operation* op) {
   auto data_format_attr = op->attribute<pir::StrAttribute>("data_format");
   if (!data_format_attr) {
     PADDLE_THROW(common::errors::InvalidArgument(
@@ -60,7 +60,7 @@ common::DataLayout PreferLayoutImpl<Conv2dOp>(pir::Operation* op) {
       if (in_type.isa<DenseTensorType>()) {
         if (auto tensor_type = in_type.dyn_cast<DenseTensorType>()) {
           if (tensor_type.dtype().isa<pir::Float16Type>()) {
-            return common::DataLayout::NHWC;
+            return DataLayout::NHWC;
           }
         }
       }
@@ -71,7 +71,7 @@ common::DataLayout PreferLayoutImpl<Conv2dOp>(pir::Operation* op) {
 }
 
 template <>
-common::DataLayout PreferLayoutImpl<Conv2dTransposeOp>(pir::Operation* op) {
+DataLayout PreferLayoutImpl<Conv2dTransposeOp>(pir::Operation* op) {
   auto data_format_attr = op->attribute<pir::StrAttribute>("data_format");
   if (!data_format_attr) {
     PADDLE_THROW(common::errors::InvalidArgument(
@@ -86,7 +86,7 @@ common::DataLayout PreferLayoutImpl<Conv2dTransposeOp>(pir::Operation* op) {
       if (in_type.isa<DenseTensorType>()) {
         if (auto tensor_type = in_type.dyn_cast<DenseTensorType>()) {
           if (tensor_type.dtype().isa<pir::Float16Type>()) {
-            return common::DataLayout::NHWC;
+            return DataLayout::NHWC;
           }
         }
       }
@@ -102,7 +102,7 @@ bool CanBeModifiedImpl<Conv2dOp>(pir::Operation* op) {
 }
 
 template <>
-common::DataLayout PreferLayoutImpl<FusedConv2dAddActOp>(pir::Operation* op) {
+DataLayout PreferLayoutImpl<FusedConv2dAddActOp>(pir::Operation* op) {
   auto data_format_attr = op->attribute<pir::StrAttribute>("data_format");
   if (!data_format_attr) {
     PADDLE_THROW(common::errors::InvalidArgument(
@@ -119,7 +119,7 @@ common::DataLayout PreferLayoutImpl<FusedConv2dAddActOp>(pir::Operation* op) {
               .at(kForceBackendAttr)
               .dyn_cast<pir::StrAttribute>()
               .AsString() == "gpu") {
-    return common::DataLayout::NHWC;
+    return DataLayout::NHWC;
   }
 
   auto concrete_op = op->dyn_cast<FusedConv2dAddActOp>();
@@ -146,7 +146,7 @@ common::DataLayout PreferLayoutImpl<FusedConv2dAddActOp>(pir::Operation* op) {
             auto dims = tensor_type.dims();
             if (dims.size() == 4 && (dims[0] % CUDNN_ALIGNMENT == 0) &&
                 (dims[1] % CUDNN_ALIGNMENT == 0)) {
-              return common::DataLayout::NHWC;
+              return DataLayout::NHWC;
             }
           }
         }
@@ -227,8 +227,7 @@ bool CanBeModifiedImpl<ReshapeOp>(pir::Operation* op) {
 }
 
 template <>
-void RewriteByLayoutImpl<SqueezeOp>(pir::Operation* op,
-                                    common::DataLayout new_layout) {
+void RewriteByLayoutImpl<SqueezeOp>(pir::Operation* op, DataLayout new_layout) {
   PADDLE_THROW(common::errors::Unimplemented(
       "Op %s should have a specialized RewriteByLayout function", op->name()));
   return;
@@ -275,8 +274,7 @@ std::vector<pir::Value> RelevantInputsImpl<ConcatOp>(pir::Operation* op) {
 }
 
 template <>
-void RewriteByLayoutImpl<ConcatOp>(pir::Operation* op,
-                                   common::DataLayout new_layout) {
+void RewriteByLayoutImpl<ConcatOp>(pir::Operation* op, DataLayout new_layout) {
   // we must the value of concat axis, but this is an input
   // which is really hard to process.
   // here we handle the simple case like pd_op.full and throw
@@ -313,8 +311,7 @@ void RewriteByLayoutImpl<ConcatOp>(pir::Operation* op,
 }
 
 template <>
-void RewriteByLayoutImpl<ReshapeOp>(pir::Operation* op,
-                                    common::DataLayout new_layout) {
+void RewriteByLayoutImpl<ReshapeOp>(pir::Operation* op, DataLayout new_layout) {
   auto concrete_op = op->dyn_cast<ReshapeOp>();
 
   auto shape = concrete_op.shape();
@@ -333,10 +330,10 @@ void RewriteByLayoutImpl<ReshapeOp>(pir::Operation* op,
                         "Reshape's shape size was expected as 4, but got %d",
                         value_attr.size()));
   std::vector<pir::Attribute> new_value_attr;
-  if (new_layout == common::DataLayout::NHWC) {
+  if (new_layout == DataLayout::NHWC) {
     new_value_attr = std::vector<pir::Attribute>{
         value_attr[0], value_attr[2], value_attr[3], value_attr[1]};
-  } else if (new_layout == common::DataLayout::NCHW) {
+  } else if (new_layout == DataLayout::NCHW) {
     new_value_attr = std::vector<pir::Attribute>{
         value_attr[0], value_attr[3], value_attr[1], value_attr[2]};
   } else {
@@ -353,8 +350,7 @@ void RewriteByLayoutImpl<ReshapeOp>(pir::Operation* op,
 }
 
 template <>
-void RewriteByLayoutImpl<ArgmaxOp>(pir::Operation* op,
-                                   common::DataLayout new_layout) {
+void RewriteByLayoutImpl<ArgmaxOp>(pir::Operation* op, DataLayout new_layout) {
   auto concrete_op = op->dyn_cast<ArgmaxOp>();
   auto axis = concrete_op.axis();
   if (!axis || !(axis.defining_op()->isa<FullOp>())) {
@@ -381,7 +377,7 @@ void RewriteByLayoutImpl<ArgmaxOp>(pir::Operation* op,
 
 template <>
 void RewriteByLayoutImpl<pir::CombineOp>(pir::Operation* op,
-                                         common::DataLayout new_layout) {
+                                         DataLayout new_layout) {
   auto concrete_op = op->dyn_cast<pir::CombineOp>();
   auto out = concrete_op.out();
   if (!out) return;
@@ -403,7 +399,7 @@ std::vector<pir::Value> RelevantInputsImpl<Pool2dOp>(pir::Operation* op) {
 }
 
 template <>
-common::DataLayout PreferLayoutImpl<Pool2dOp>(pir::Operation* op) {
+DataLayout PreferLayoutImpl<Pool2dOp>(pir::Operation* op) {
   auto concrete_op = op->dyn_cast<Pool2dOp>();
   auto data_format_attr = op->attribute<pir::StrAttribute>("data_format");
   auto origin_format = common::StringToDataLayout(data_format_attr.AsString());
@@ -420,11 +416,11 @@ common::DataLayout PreferLayoutImpl<Pool2dOp>(pir::Operation* op) {
 
   // get input dims h, w, c
   int32_t h, w, c;
-  if (origin_format == common::DataLayout::NHWC) {
+  if (origin_format == DataLayout::NHWC) {
     h = input.dims().at(1);
     w = input.dims().at(2);
     c = input.dims().at(3);
-  } else if (origin_format == common::DataLayout::NCHW) {
+  } else if (origin_format == DataLayout::NCHW) {
     h = input.dims().at(2);
     w = input.dims().at(3);
     c = input.dims().at(1);
@@ -453,61 +449,61 @@ common::DataLayout PreferLayoutImpl<Pool2dOp>(pir::Operation* op) {
     };
     // TODO(liujinnan): need to test the prefer layout if kernel_size is not
     // aligned.
-    if (!AllEqual(kernel_size)) return common::DataLayout::NCHW;
+    if (!AllEqual(kernel_size)) return DataLayout::NCHW;
 
     int k = kernel_size[0];
     // kernel size is all 1, prefer NCHW.
-    if (k == 1 || k == 2) return common::DataLayout::NCHW;
+    if (k == 1 || k == 2) return DataLayout::NCHW;
 
     if (pool_type == "max") {
       if (h * w <= 64 * 64) {
-        if (k <= 3) return common::DataLayout::NHWC;
-        return common::DataLayout::NCHW;
+        if (k <= 3) return DataLayout::NHWC;
+        return DataLayout::NCHW;
       } else {
         if (c <= 16) {
-          if (k <= 5) return common::DataLayout::NHWC;
-          return common::DataLayout::NCHW;
+          if (k <= 5) return DataLayout::NHWC;
+          return DataLayout::NCHW;
         }
         // when c > 16, all kernel_size return NHWC
-        return common::DataLayout::NHWC;
+        return DataLayout::NHWC;
       }
     } else if (pool_type == "avg") {
       if (h * w <= 64 * 64) {
         if (c <= 16) {
           if (k < 7)
-            return common::DataLayout::NCHW;
+            return DataLayout::NCHW;
           else
-            return common::DataLayout::NHWC;
+            return DataLayout::NHWC;
         } else if (c > 16 && c <= 32) {
           if (k <= 7)
-            return common::DataLayout::NHWC;
+            return DataLayout::NHWC;
           else
-            return common::DataLayout::NCHW;
+            return DataLayout::NCHW;
         } else if (c > 32 && c <= 64) {
           if (k < 5)
-            return common::DataLayout::NCHW;
+            return DataLayout::NCHW;
           else
-            return common::DataLayout::NHWC;
+            return DataLayout::NHWC;
         } else if (c > 64 && c <= 128) {
           if (k < 7)
-            return common::DataLayout::NHWC;
+            return DataLayout::NHWC;
           else
-            return common::DataLayout::NCHW;
+            return DataLayout::NCHW;
         }
         // when c > 128, all kernel_size return NHWC
-        return common::DataLayout::NHWC;
+        return DataLayout::NHWC;
       } else {
         if (c < 64) {
-          return common::DataLayout::NHWC;
+          return DataLayout::NHWC;
         } else {
           if (k < 7)
-            return common::DataLayout::NHWC;
+            return DataLayout::NHWC;
           else
-            return common::DataLayout::NCHW;
+            return DataLayout::NCHW;
         }
       }
     }
-    return common::DataLayout::NCHW;
+    return DataLayout::NCHW;
   };
   return PreferLayout(c, h, w, kernel_size, pool_type);
 }