diff --git a/paddle/phi/core/tensor_utils.cc b/paddle/phi/core/tensor_utils.cc
index 7ba4cd55183fafb6e25816c5a28ccc4db78b2d9f..65b90c88085f816030641fdcf2b8216f1503e462 100644
--- a/paddle/phi/core/tensor_utils.cc
+++ b/paddle/phi/core/tensor_utils.cc
@@ -912,4 +912,40 @@ template phi::dtype::complex<float> GetValue(const phi::DenseTensor* x);
 
 template phi::dtype::complex<double> GetValue(const phi::DenseTensor* x);
 
+template <typename T>
+std::vector<T> GetVectorFromTensor(const phi::DenseTensor* x) {
+  std::vector<T> vec_new_data;
+  if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT32) {
+    auto* data = x->data<int>();
+    phi::DenseTensor cpu_attr_tensor;
+    if (x->place().GetType() != phi::AllocationType::CPU) {
+      phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance();
+      auto dev_ctx = pool.Get(x->place());
+      phi::Copy(*dev_ctx, *x, CPUPlace(), true, &cpu_attr_tensor);
+      data = cpu_attr_tensor.data<int>();
+    }
+    vec_new_data = std::vector<T>(data, data + x->numel());
+  } else if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT64) {
+    auto* data = x->data<int64_t>();
+    phi::DenseTensor cpu_attr_tensor;
+    if (x->place().GetType() != phi::AllocationType::CPU) {
+      phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance();
+      auto dev_ctx = pool.Get(x->place());
+      phi::Copy(*dev_ctx, *x, CPUPlace(), true, &cpu_attr_tensor);
+      data = cpu_attr_tensor.data<int64_t>();
+    }
+    // NOTE: Converting int64 to int32 may cause data overflow.
+    vec_new_data = std::vector<T>(data, data + x->numel());
+  } else {
+    PADDLE_THROW(phi::errors::InvalidArgument(
+        "The dtype of Tensor must be int32 or int64, but received: %s",
+        phi::TransToProtoVarType(x->dtype())));
+  }
+  return vec_new_data;
+}
+
+template std::vector<int32_t> GetVectorFromTensor(const phi::DenseTensor* x);
+
+template std::vector<int64_t> GetVectorFromTensor(const phi::DenseTensor* x);
+
 }  // namespace phi
diff --git a/paddle/phi/core/tensor_utils.h b/paddle/phi/core/tensor_utils.h
index 9203621931963a8aa60a5a674efa0f3faf391c01..e122cdb954640440c655f57ac5ebdcd7e5e21ca9 100644
--- a/paddle/phi/core/tensor_utils.h
+++ b/paddle/phi/core/tensor_utils.h
@@ -14,17 +14,12 @@ limitations under the License. */
 
 #pragma once
 
-#include "paddle/phi/backends/all_context.h"
-#include "paddle/phi/backends/cpu/cpu_context.h"
-#include "paddle/phi/common/place.h"
 #include "paddle/phi/core/dense_tensor.h"
 #include "paddle/phi/core/device_context.h"
 #include "paddle/phi/core/selected_rows.h"
 #include "paddle/phi/core/sparse_coo_tensor.h"
 #include "paddle/phi/core/sparse_csr_tensor.h"
 #include "paddle/phi/core/tensor_meta.h"
-#include "paddle/phi/core/utils/data_type.h"
-
 namespace phi {
 
 class DenseTensorUtils {
@@ -149,35 +144,6 @@ inline T GetValue(const Context& dev_ctx, const DenseTensor& x) {
 }
 
 template <typename T = int32_t>
-inline std::vector<T> GetVectorFromTensor(const phi::DenseTensor* x) {
-  std::vector<T> vec_new_data;
-  if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT32) {
-    auto* data = x->data<int>();
-    phi::DenseTensor cpu_attr_tensor;
-    if (!paddle::platform::is_cpu_place(x->place())) {
-      phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance();
-      auto dev_ctx = pool.Get(x->place());
-      phi::Copy(*dev_ctx, *x, CPUPlace(), true, &cpu_attr_tensor);
-      data = cpu_attr_tensor.data<int>();
-    }
-    vec_new_data = std::vector<T>(data, data + x->numel());
-  } else if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT64) {
-    auto* data = x->data<int64_t>();
-    phi::DenseTensor cpu_attr_tensor;
-    if (!paddle::platform::is_cpu_place(x->place())) {
-      phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance();
-      auto dev_ctx = pool.Get(x->place());
-      phi::Copy(*dev_ctx, *x, CPUPlace(), true, &cpu_attr_tensor);
-      data = cpu_attr_tensor.data<int64_t>();
-    }
-    // NOTE: Converting int64 to int32 may cause data overflow.
-    vec_new_data = std::vector<T>(data, data + x->numel());
-  } else {
-    PADDLE_THROW(phi::errors::InvalidArgument(
-        "The dtype of Tensor must be int32 or int64, but received: %s",
-        phi::TransToProtoVarType(x->dtype())));
-  }
-  return vec_new_data;
-}
+std::vector<T> GetVectorFromTensor(const phi::DenseTensor* x);
 
 }  // namespace phi