diff --git a/paddle/fluid/framework/operator.cc b/paddle/fluid/framework/operator.cc
index 16e63e433e64038ea15f75895eef3d288d043f06..d317aac8594b4c9045f06a596fb3f9292604fcd6 100644
--- a/paddle/fluid/framework/operator.cc
+++ b/paddle/fluid/framework/operator.cc
@@ -23,7 +23,6 @@ limitations under the License. */
 #include "paddle/fluid/framework/data_type_transform.h"
 #include "paddle/fluid/framework/details/nan_inf_utils.h"
 #include "paddle/fluid/framework/op_call_stack.h"
-#include "paddle/fluid/framework/pten_utils.h"
 #include "paddle/fluid/framework/shape_inference.h"
 #include "paddle/fluid/framework/transfer_scope_cache.h"
 #include "paddle/fluid/framework/unused_var_check.h"
diff --git a/paddle/fluid/imperative/prepared_operator.cc b/paddle/fluid/imperative/prepared_operator.cc
index db26c66958140b9900c8848818bd313bffaf2e13..b2d55babc7e1c11ca8efa9d3a95d92e90c4967c4 100644
--- a/paddle/fluid/imperative/prepared_operator.cc
+++ b/paddle/fluid/imperative/prepared_operator.cc
@@ -16,7 +16,6 @@
 
 #include "paddle/fluid/framework/data_type_transform.h"
 #include "paddle/fluid/framework/details/nan_inf_utils.h"
-#include "paddle/fluid/framework/pten_utils.h"
 #include "paddle/fluid/imperative/infer_shape_context.h"
 #include "paddle/pten/common/scalar.h"
 #include "paddle/utils/small_vector.h"
diff --git a/paddle/pten/api/include/creation.h b/paddle/pten/api/include/creation.h
index d7311e6cd283b4a17b9bcfee1cda603a3bf9970d..9795d88f81880b9f84491ff4c9ebe9428391510f 100644
--- a/paddle/pten/api/include/creation.h
+++ b/paddle/pten/api/include/creation.h
@@ -14,5 +14,26 @@
 
 #pragma once
 
+#include "paddle/pten/api/include/infershape.h"
+#include "paddle/pten/hapi/lib/utils/allocator.h"
 #include "paddle/pten/kernels/cpu/creation.h"
 #include "paddle/pten/kernels/cuda/creation.h"
+
+namespace pten {
+
+// TODO(YuanRisheng) This function name should be same as User API name.
+// TODO(zyfncg) Automatic code generation
+template <typename T, typename ContextT>
+DenseTensor FillAnyLike(const ContextT& dev_ctx,
+                        const DenseTensor& x,
+                        const Scalar& val) {
+  auto out_meta = UnchangedInferShape(x.meta());
+  const auto allocator =
+      std::make_shared<paddle::experimental::DefaultAllocator>(
+          dev_ctx.GetPlace());
+  pten::DenseTensor dense_out(allocator, out_meta);
+  FillAnyLike<T>(dev_ctx, x, val, &dense_out);
+  return dense_out;
+}
+
+}  // namespace pten
diff --git a/paddle/pten/api/include/linalg.h b/paddle/pten/api/include/linalg.h
index d9798c3a2e0a8117bb84829200ad08deab0953a9..0d4c7a60fbc1456d0ec4dcc06f1e3af51117e3b6 100644
--- a/paddle/pten/api/include/linalg.h
+++ b/paddle/pten/api/include/linalg.h
@@ -15,5 +15,24 @@
 #pragma once
 
 // See Note: [ How do we organize the kernel directory ]
+#include "paddle/pten/api/include/infershape.h"
+#include "paddle/pten/hapi/lib/utils/allocator.h"
 #include "paddle/pten/kernels/cpu/linalg.h"
 #include "paddle/pten/kernels/cuda/linalg.h"
+
+namespace pten {
+
+template <typename T, typename ContextT>
+DenseTensor Dot(const ContextT& dev_ctx,
+                const DenseTensor& x,
+                const DenseTensor& y) {
+  auto out_meta = DotInferShape(x.meta(), y.meta());
+  const auto allocator =
+      std::make_shared<paddle::experimental::DefaultAllocator>(
+          dev_ctx.GetPlace());
+  pten::DenseTensor dense_out(allocator, out_meta);
+  Dot<T>(dev_ctx, x, y, &dense_out);
+  return dense_out;
+}
+
+}  // namespace pten
diff --git a/paddle/pten/api/include/manipulation.h b/paddle/pten/api/include/manipulation.h
index f2acad96499696ada9ec2e7d1c2b99380133c97a..1f867686a6eb7ee006ed6979939ca2e2e2531ad8 100644
--- a/paddle/pten/api/include/manipulation.h
+++ b/paddle/pten/api/include/manipulation.h
@@ -15,5 +15,25 @@
 #pragma once
 
 // See Note: [ How do we organize the kernel directory ]
+#include "paddle/pten/api/include/infershape.h"
+#include "paddle/pten/hapi/lib/utils/allocator.h"
 #include "paddle/pten/kernels/cpu/manipulation.h"
 #include "paddle/pten/kernels/cuda/manipulation.h"
+
+namespace pten {
+
+template <typename T, typename ContextT>
+DenseTensor Flatten(const ContextT& dev_ctx,
+                    const DenseTensor& x,
+                    int start_axis,
+                    int stop_axis) {
+  auto out_meta = FlattenInferShape(x.meta(), start_axis, stop_axis);
+  const auto allocator =
+      std::make_shared<paddle::experimental::DefaultAllocator>(
+          dev_ctx.GetPlace());
+  pten::DenseTensor dense_out(allocator, out_meta);
+  Flatten<T>(dev_ctx, x, start_axis, stop_axis, &dense_out);
+  return dense_out;
+}
+
+}  // namespace pten
diff --git a/paddle/pten/api/include/math.h b/paddle/pten/api/include/math.h
index 5145c823a5c6e07462477a3e04ba68e177a67dd3..fa512e8d6db0d7f8dfc28b642ecd91e51066b648 100644
--- a/paddle/pten/api/include/math.h
+++ b/paddle/pten/api/include/math.h
@@ -15,5 +15,62 @@ limitations under the License. */
 #pragma once
 
 // See Note: [ How do we organize the kernel directory ]
+#include "paddle/pten/api/include/infershape.h"
+#include "paddle/pten/hapi/lib/utils/allocator.h"
 #include "paddle/pten/kernels/cpu/math.h"
 #include "paddle/pten/kernels/cuda/math.h"
+
+namespace pten {
+
+template <typename T, typename ContextT>
+DenseTensor Sign(const ContextT& dev_ctx, const DenseTensor& x) {
+  auto out_meta = UnchangedInferShape(x.meta());
+  const auto allocator =
+      std::make_shared<paddle::experimental::DefaultAllocator>(
+          dev_ctx.GetPlace());
+  pten::DenseTensor dense_out(allocator, out_meta);
+  Sign<T>(dev_ctx, x, &dense_out);
+  return dense_out;
+}
+
+template <typename T, typename ContextT>
+DenseTensor Mean(const ContextT& dev_ctx, const DenseTensor& x) {
+  auto out_meta = ReductionInferShape(x.meta());
+  const auto allocator =
+      std::make_shared<paddle::experimental::DefaultAllocator>(
+          dev_ctx.GetPlace());
+  pten::DenseTensor dense_out(allocator, out_meta);
+  Mean<T>(dev_ctx, x, &dense_out);
+  return dense_out;
+}
+
+template <typename T, typename ContextT>
+DenseTensor Scale(const ContextT& dev_ctx,
+                  const DenseTensor& x,
+                  float scale,
+                  float bias,
+                  bool bias_after_scale) {
+  auto out_meta = UnchangedInferShape(x.meta());
+  const auto allocator =
+      std::make_shared<paddle::experimental::DefaultAllocator>(
+          dev_ctx.GetPlace());
+  pten::DenseTensor dense_out(allocator, out_meta);
+  Scale<T>(dev_ctx, x, scale, bias, bias_after_scale, &dense_out);
+  return dense_out;
+}
+
+template <typename T, typename ContextT>
+DenseTensor Scale(const ContextT& dev_ctx,
+                  const DenseTensor& x,
+                  const DenseTensor& scale,
+                  float bias,
+                  bool bias_after_scale) {
+  auto out_meta = UnchangedInferShape(x.meta());
+  const auto allocator =
+      std::make_shared<paddle::experimental::DefaultAllocator>(
+          dev_ctx.GetPlace());
+  pten::DenseTensor dense_out(allocator, out_meta);
+  ScaleHost<T>(dev_ctx, x, scale, bias, bias_after_scale, &dense_out);
+  return dense_out;
+}
+}  // namespace pten
diff --git a/paddle/pten/hapi/lib/utils/tensor_utils.cc b/paddle/pten/hapi/lib/utils/tensor_utils.cc
index a55c50db761a61f241fb74e6a4c482a836569896..f7641f424f4910d69c9ca71ddfa7968979a66c81 100644
--- a/paddle/pten/hapi/lib/utils/tensor_utils.cc
+++ b/paddle/pten/hapi/lib/utils/tensor_utils.cc
@@ -45,6 +45,7 @@ std::unique_ptr<pten::DenseTensor> MakePtenDenseTensor(
   SetLoD(&meta.lod, src.lod());
   auto shared_storage =
       pten::make_intrusive<SharedStorage>(src.Holder(), src.offset());
+
   return std::make_unique<pten::DenseTensor>(std::move(shared_storage),
                                              std::move(meta));
 }
diff --git a/paddle/pten/kernels/cpu/manipulation.cc b/paddle/pten/kernels/cpu/manipulation.cc
index c436e14e0caab74caf203fc1ef5ee3b7e2631987..87c76149f127feda0a9afdd00634d7767b0e5f7a 100644
--- a/paddle/pten/kernels/cpu/manipulation.cc
+++ b/paddle/pten/kernels/cpu/manipulation.cc
@@ -24,10 +24,9 @@ void Flatten(const CPUContext& dev_ctx,
              int start_axis,
              int stop_axis,
              DenseTensor* out) {
-  auto out_meta = FlattenInferShape(x.meta(), start_axis, stop_axis);
+  auto out_dims = out->dims();
   pten::Copy(dev_ctx, x, out);
-  out->set_lod(out_meta.lod);
-  out->Resize(out_meta.dims);
+  out->Resize(out_dims);
 }
 
 // TODO(yuanrisheng): this kernel is for training and xshape is a Intermediate
diff --git a/paddle/pten/kernels/cuda/manipulation.cu b/paddle/pten/kernels/cuda/manipulation.cu
index 43614f859c58bf3435d41249a9882f782bddb603..38111f2b8c02fd37ae4063fb6d752000c6e486fd 100644
--- a/paddle/pten/kernels/cuda/manipulation.cu
+++ b/paddle/pten/kernels/cuda/manipulation.cu
@@ -24,10 +24,9 @@ void Flatten(const CUDAContext& dev_ctx,
              int start_axis,
              int stop_axis,
              DenseTensor* out) {
-  auto out_meta = FlattenInferShape(x.meta(), start_axis, stop_axis);
+  auto out_dims = out->dims();
   pten::Copy(dev_ctx, x, out);
-  out->set_lod(out_meta.lod);
-  out->Resize(out_meta.dims);
+  out->Resize(out_dims);
 }
 
 // TODO(yuanrisheng): this kernel is for training and xshape is a Intermediate
diff --git a/paddle/pten/tests/CMakeLists.txt b/paddle/pten/tests/CMakeLists.txt
index 3dc779380527f14368da9c14d979a346e330023d..3d2da6a5afdd1a6b780074d6b272a93346c898f8 100644
--- a/paddle/pten/tests/CMakeLists.txt
+++ b/paddle/pten/tests/CMakeLists.txt
@@ -12,3 +12,4 @@ cc_test(test_matmul_api SRCS test_matmul_api.cc DEPS linalg_api pten_hapi_utils)
 cc_test(test_fill_api SRCS test_fill_api.cc DEPS creation_api pten_hapi_utils)
 cc_test(test_copy_api SRCS test_copy_api.cc DEPS utils_cpu pten_hapi_utils)
 cc_test(test_flatten_api SRCS test_flatten_api.cc DEPS utils_cpu manipulation_api pten_hapi_utils)
+cc_test(test_scale_api SRCS test_scale_api.cc DEPS math_api pten_hapi_utils)
diff --git a/paddle/pten/tests/test_dot_api.cc b/paddle/pten/tests/test_dot_api.cc
index 69e785904fe3c98fbc1e812f0b32729785b368f9..5401b66544473940938e8fdf55ab86ff580b2463 100644
--- a/paddle/pten/tests/test_dot_api.cc
+++ b/paddle/pten/tests/test_dot_api.cc
@@ -21,6 +21,8 @@ limitations under the License. */
 #include "paddle/pten/core/kernel_registry.h"
 #include "paddle/pten/hapi/lib/utils/allocator.h"
 
+#include "paddle/pten/api/include/linalg.h"
+
 PT_DECLARE_MODULE(LinalgCPU);
 
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
@@ -82,3 +84,55 @@ TEST(API, dot) {
   ASSERT_NEAR(expect_result[1], actual_result1, 1e-6f);
   ASSERT_NEAR(expect_result[2], actual_result2, 1e-6f);
 }
+
+// TODO(YuanRisheng) This unitest should be created in other file.
+//                   It is convenient to make compilation decoupling.
+TEST(DEV_API, dot) {
+  // 1. create tensor
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  pten::DenseTensor dense_x(alloc,
+                            pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                                  framework::make_ddim({3, 10}),
+                                                  pten::DataLayout::NCHW));
+  auto* dense_x_data = dense_x.mutable_data<float>();
+
+  pten::DenseTensor dense_y(alloc,
+                            pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                                  framework::make_ddim({3, 10}),
+                                                  pten::DataLayout::NCHW));
+  auto* dense_y_data = dense_y.mutable_data<float>();
+
+  float sum[3] = {0.0, 0.0, 0.0};
+  for (size_t i = 0; i < 3; ++i) {
+    for (size_t j = 0; j < 10; ++j) {
+      dense_x_data[i * 10 + j] = (i * 10 + j) * 1.0;
+      dense_y_data[i * 10 + j] = (i * 10 + j) * 1.0;
+      sum[i] += (i * 10 + j) * (i * 10 + j) * 1.0;
+    }
+  }
+
+  paddle::platform::DeviceContextPool& pool =
+      paddle::platform::DeviceContextPool::Instance();
+  auto* dev_ctx = pool.Get(paddle::platform::CPUPlace());
+
+  // 2. test API
+  auto out = pten::Dot<float>(
+      *(static_cast<paddle::platform::CPUDeviceContext*>(dev_ctx)),
+      dense_x,
+      dense_y);
+
+  // 3. check result
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.meta().type, pten::DataType::FLOAT32);
+  ASSERT_EQ(out.meta().layout, pten::DataLayout::NCHW);
+
+  auto expect_result = sum;
+  auto actual_result0 = out.data<float>()[0];
+  auto actual_result1 = out.data<float>()[1];
+  auto actual_result2 = out.data<float>()[2];
+  ASSERT_NEAR(expect_result[0], actual_result0, 1e-6f);
+  ASSERT_NEAR(expect_result[1], actual_result1, 1e-6f);
+  ASSERT_NEAR(expect_result[2], actual_result2, 1e-6f);
+}
diff --git a/paddle/pten/tests/test_fill_api.cc b/paddle/pten/tests/test_fill_api.cc
index 4f93e03aca2f3d5cc299b3db5348c79537829f83..5a788226086dcc6953357d32fec966493e2d6baa 100644
--- a/paddle/pten/tests/test_fill_api.cc
+++ b/paddle/pten/tests/test_fill_api.cc
@@ -21,6 +21,8 @@ limitations under the License. */
 #include "paddle/pten/core/kernel_registry.h"
 #include "paddle/pten/hapi/lib/utils/allocator.h"
 
+#include "paddle/pten/api/include/creation.h"
+
 PT_DECLARE_MODULE(CreationCPU);
 
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
@@ -131,3 +133,38 @@ TEST(API, ones_like) {
     ASSERT_EQ(actual_result[i], 1);
   }
 }
+
+TEST(DEV_API, fill_any_like) {
+  // 1. create tensor
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  pten::DenseTensor dense_x(alloc,
+                            pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                                  framework::make_ddim({3, 2}),
+                                                  pten::DataLayout::NCHW));
+  auto* dense_x_data = dense_x.mutable_data<float>();
+  dense_x_data[0] = 0;
+  float val = 1.0;
+
+  paddle::platform::DeviceContextPool& pool =
+      paddle::platform::DeviceContextPool::Instance();
+  auto* dev_ctx = pool.Get(paddle::platform::CPUPlace());
+
+  // 2. test API
+  auto out = pten::FillAnyLike<float>(
+      *(static_cast<paddle::platform::CPUDeviceContext*>(dev_ctx)),
+      dense_x,
+      val);
+
+  // 3. check result
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.numel(), 6);
+  ASSERT_EQ(out.meta().type, pten::DataType::FLOAT32);
+  ASSERT_EQ(out.meta().layout, pten::DataLayout::NCHW);
+
+  auto* actual_result = out.data<float>();
+  for (auto i = 0; i < 6; i++) {
+    ASSERT_NEAR(actual_result[i], val, 1e-6f);
+  }
+}
diff --git a/paddle/pten/tests/test_flatten_api.cc b/paddle/pten/tests/test_flatten_api.cc
index 48d2205c2ff4846de258d3d93fb2a4571eb56e34..dfb777678a94d05fbbf4ad401aa89cfdfad2decd 100644
--- a/paddle/pten/tests/test_flatten_api.cc
+++ b/paddle/pten/tests/test_flatten_api.cc
@@ -21,6 +21,8 @@ limitations under the License. */
 #include "paddle/pten/core/kernel_registry.h"
 #include "paddle/pten/hapi/lib/utils/allocator.h"
 
+#include "paddle/pten/api/include/manipulation.h"
+
 PT_DECLARE_MODULE(ManipulationCPU);
 
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
@@ -70,3 +72,47 @@ TEST(API, flatten) {
   }
   ASSERT_EQ(value_equal, true);
 }
+
+TEST(DEV_API, flatten) {
+  // 1. create tensor
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  pten::DenseTensor dense_x(
+      alloc,
+      pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                            framework::make_ddim({3, 2, 2, 3}),
+                            pten::DataLayout::NCHW));
+  auto* dense_x_data = dense_x.mutable_data<float>();
+
+  for (int i = 0; i < dense_x.numel(); i++) {
+    dense_x_data[i] = i;
+  }
+  int start_axis = 1, stop_axis = 2;
+  paddle::platform::DeviceContextPool& pool =
+      paddle::platform::DeviceContextPool::Instance();
+  auto* dev_ctx = pool.Get(paddle::platform::CPUPlace());
+
+  // 2. test API
+  auto out = pten::Flatten<float>(
+      *(static_cast<paddle::platform::CPUDeviceContext*>(dev_ctx)),
+      dense_x,
+      start_axis,
+      stop_axis);
+
+  // 3. check result
+  std::vector<int> expect_shape = {3, 4, 3};
+  ASSERT_EQ(out.dims()[0], expect_shape[0]);
+  ASSERT_EQ(out.dims()[1], expect_shape[1]);
+  ASSERT_EQ(out.dims()[2], expect_shape[2]);
+  ASSERT_EQ(out.numel(), 36);
+  ASSERT_EQ(out.meta().type, pten::DataType::FLOAT32);
+  ASSERT_EQ(out.meta().layout, pten::DataLayout::NCHW);
+
+  bool value_equal = true;
+  auto* dense_out_data = out.data<float>();
+  for (int i = 0; i < dense_x.numel(); i++) {
+    if (std::abs(dense_x_data[i] - dense_out_data[i]) > 1e-6f)
+      value_equal = false;
+  }
+  ASSERT_EQ(value_equal, true);
+}
diff --git a/paddle/pten/tests/test_mean_api.cc b/paddle/pten/tests/test_mean_api.cc
index ee8388671b7ebe5dc642d7ad3bb8a853d3bcbf56..b3da90659d005a0d9fbcd38b0cbfa947276ad03c 100644
--- a/paddle/pten/tests/test_mean_api.cc
+++ b/paddle/pten/tests/test_mean_api.cc
@@ -21,6 +21,8 @@ limitations under the License. */
 #include "paddle/pten/core/kernel_registry.h"
 #include "paddle/pten/hapi/lib/utils/allocator.h"
 
+#include "paddle/pten/api/include/math.h"
+
 PT_DECLARE_MODULE(MathCPU);
 
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
@@ -67,3 +69,36 @@ TEST(API, mean) {
   auto actual_result = dense_out->data<float>()[0];
   ASSERT_NEAR(expect_result, actual_result, 1e-6f);
 }
+
+TEST(DEV_API, mean) {
+  // 1. create tensor
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  pten::DenseTensor dense_x(alloc,
+                            pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                                  framework::make_ddim({3, 4}),
+                                                  pten::DataLayout::NCHW));
+  auto* dense_x_data = dense_x.mutable_data<float>();
+
+  float sum = 0.0;
+  for (size_t i = 0; i < 12; ++i) {
+    dense_x_data[i] = i * 1.0;
+    sum += i * 1.0;
+  }
+  paddle::platform::DeviceContextPool& pool =
+      paddle::platform::DeviceContextPool::Instance();
+  auto* dev_ctx = pool.Get(paddle::platform::CPUPlace());
+  // 2. test API
+  auto out = pten::Mean<float>(
+      *(static_cast<paddle::platform::CPUDeviceContext*>(dev_ctx)), dense_x);
+
+  // 3. check result
+  ASSERT_EQ(out.dims().size(), 1);
+  ASSERT_EQ(out.numel(), 1);
+  ASSERT_EQ(out.meta().type, pten::DataType::FLOAT32);
+  ASSERT_EQ(out.meta().layout, pten::DataLayout::NCHW);
+
+  auto expect_result = sum / 12;
+  auto actual_result = out.data<float>()[0];
+  ASSERT_NEAR(expect_result, actual_result, 1e-6f);
+}
diff --git a/paddle/pten/tests/test_scale_api.cc b/paddle/pten/tests/test_scale_api.cc
new file mode 100644
index 0000000000000000000000000000000000000000..9f80d6d2cc126bb4687626f267d537601bca7ff2
--- /dev/null
+++ b/paddle/pten/tests/test_scale_api.cc
@@ -0,0 +1,118 @@
+/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <gtest/gtest.h>
+#include <memory>
+
+#include "paddle/pten/hapi/include/math.h"
+
+#include "paddle/pten/core/dense_tensor.h"
+#include "paddle/pten/core/kernel_registry.h"
+#include "paddle/pten/hapi/lib/utils/allocator.h"
+
+#include "paddle/pten/api/include/math.h"
+
+PT_DECLARE_MODULE(MathCPU);
+
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
+PT_DECLARE_MODULE(MathCUDA);
+#endif
+
+namespace framework = paddle::framework;
+using DDim = paddle::framework::DDim;
+
+TEST(DEV_API, scale) {
+  // 1. create tensor
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  pten::DenseTensor dense_x(alloc,
+                            pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                                  framework::make_ddim({3, 4}),
+                                                  pten::DataLayout::NCHW));
+
+  auto* dense_x_data = dense_x.mutable_data<float>();
+  for (size_t i = 0; i < 12; ++i) {
+    dense_x_data[i] = i * 1.0;
+  }
+  float scale = 2;
+  float bias = 1;
+  bool bias_after_scale = true;
+
+  paddle::platform::DeviceContextPool& pool =
+      paddle::platform::DeviceContextPool::Instance();
+  auto* dev_ctx = pool.Get(paddle::platform::CPUPlace());
+
+  // 2. test API
+  auto out = pten::Scale<float>(
+      *(static_cast<paddle::platform::CPUDeviceContext*>(dev_ctx)),
+      dense_x,
+      scale,
+      bias,
+      bias_after_scale);
+
+  // 3. check result
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.numel(), 12);
+  ASSERT_EQ(out.meta().type, pten::DataType::FLOAT32);
+  ASSERT_EQ(out.meta().layout, pten::DataLayout::NCHW);
+
+  auto expect_result = 23;
+  auto actual_result = out.data<float>()[11];
+  ASSERT_NEAR(expect_result, actual_result, 1e-6f);
+}
+
+TEST(DEV_API, scale_host) {
+  // 1. create tensor
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  pten::DenseTensor dense_x(alloc,
+                            pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                                  framework::make_ddim({3, 4}),
+                                                  pten::DataLayout::NCHW));
+  auto* dense_x_data = dense_x.mutable_data<float>();
+  for (size_t i = 0; i < 12; ++i) {
+    dense_x_data[i] = i * 1.0;
+  }
+  const auto alloc2 = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  pten::DenseTensor scale(alloc2,
+                          pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                                framework::make_ddim({1}),
+                                                pten::DataLayout::NCHW));
+  scale.mutable_data<float>()[0] = 2;
+  float bias = 1;
+  bool bias_after_scale = true;
+
+  paddle::platform::DeviceContextPool& pool =
+      paddle::platform::DeviceContextPool::Instance();
+  auto* dev_ctx = pool.Get(paddle::platform::CPUPlace());
+
+  // 2. test API
+  auto out = pten::Scale<float>(
+      *(static_cast<paddle::platform::CPUDeviceContext*>(dev_ctx)),
+      dense_x,
+      scale,
+      bias,
+      bias_after_scale);
+
+  // 3. check result
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.numel(), 12);
+  ASSERT_EQ(out.meta().type, pten::DataType::FLOAT32);
+  ASSERT_EQ(out.meta().layout, pten::DataLayout::NCHW);
+
+  auto expect_result = 23;
+  auto actual_result = out.data<float>()[11];
+  ASSERT_NEAR(expect_result, actual_result, 1e-6f);
+}