diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/atomic_add.h b/mindspore/ccsrc/plugin/device/cpu/kernel/atomic_add.h
index 25e50b302d1..53b0c43a2b3 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/atomic_add.h
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/atomic_add.h
@@ -16,6 +16,9 @@
 
 #ifndef MINDSPORE_CCSRC_PLUGIN_DEVICE_CPU_KERNEL_ATOMIC_ADD_H_
 #define MINDSPORE_CCSRC_PLUGIN_DEVICE_CPU_KERNEL_ATOMIC_ADD_H_
+
+#include <stdint.h>
+
 #include "utils/log_adapter.h"
 
 namespace mindspore {
diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.cc
index 9b2ad4a8efa..74fdb63eaa8 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.cc
@@ -28,18 +28,25 @@ namespace {
 constexpr int kDyOutputDimIndex = 1;
 constexpr int kDyHeightIndex = 2;
 constexpr int kDyWidthIndex = 3;
+constexpr int INPUT_NUM = 2;
+constexpr int OUTPUT_NUM = 1;
+constexpr int OUT_PUT_SHAPE_SIZE = 4;
+constexpr int DY_SHAPE_SIZE = 4;
+constexpr int DX_SHAPE_SIZE = 4;
+constexpr int ROI_SHAPE_SIZE = 3;
+constexpr int ROIS_NUM_INDEX = 2;
 }  // namespace
 
 template <typename T>
 void PSROIPoolingGradCpuKernelMod::PSROIPoolBackward(size_t start, size_t end, const T *input_diff, T *output_diff,
-                                                     T *roi_boxes) {
+                                                     T *roi_boxes) const {
   auto output_channels = output_channels_;
   auto pooled_width = pooled_width_;
   auto pooled_height = pooled_height_;
   auto feature_channels = feature_channels_;
   auto feature_width = width_;
   auto feature_height = height_;
-  auto spatial_scale = (T)spatial_scale_;
+  auto spatial_scale = static_cast<T>(spatial_scale_);
   auto rois_num = rois_num_;
   auto elements_per_roi_box = 5;
   constexpr float zero = 0;
@@ -73,17 +80,21 @@ void PSROIPoolingGradCpuKernelMod::PSROIPoolBackward(size_t start, size_t end, c
     T roi_end_height = static_cast<T>(roundf(static_cast<float>(roi_end_height_before_round)));
 
     // let min roi len and width bigger than 0.1
-    T roi_width = std::max(roi_end_width - roi_start_width, (T)0.1);
-    T roi_height = std::max(roi_end_height - roi_start_height, (T)0.1);
+    T roi_width = std::max(roi_end_width - roi_start_width, static_cast<T>(0.1));
+    T roi_height = std::max(roi_end_height - roi_start_height, static_cast<T>(0.1));
 
     // Compute bin_width and bin_height
     T bin_height = roi_height / static_cast<T>(pooled_height);
     T bin_width = roi_width / static_cast<T>(pooled_width);
     // compute pooling area's position
-    int pooling_start_x = floor(static_cast<float>(static_cast<T>(height_offset_n) * bin_height + roi_start_height));
-    int pooling_start_y = floor(static_cast<float>(static_cast<T>(width_offset_n) * bin_width + roi_start_width));
-    int pooling_end_x = ceil(static_cast<float>(static_cast<T>(height_offset_n + 1) * bin_height + roi_start_height));
-    int pooling_end_y = ceil(static_cast<float>(static_cast<T>(width_offset_n + 1) * bin_width + roi_start_width));
+    int pooling_start_x =
+      static_cast<int>(floor(static_cast<float>(static_cast<T>(height_offset_n) * bin_height + roi_start_height)));
+    int pooling_start_y =
+      static_cast<int>(floor(static_cast<float>(static_cast<T>(width_offset_n) * bin_width + roi_start_width)));
+    int pooling_end_x =
+      static_cast<int>(ceil(static_cast<float>(static_cast<T>(height_offset_n + 1) * bin_height + roi_start_height)));
+    int pooling_end_y =
+      static_cast<int>(ceil(static_cast<float>(static_cast<T>(width_offset_n + 1) * bin_width + roi_start_width)));
     // Add roi offsets and clip to input boundaries
     pooling_start_x = std::min(std::max(pooling_start_x, 0), feature_height);
     pooling_end_x = std::min(std::max(pooling_end_x, 0), feature_height);
@@ -133,7 +144,7 @@ bool PSROIPoolingGradCpuKernelMod::IsSupportedDtype(TypeId type_id) {
   return false;
 }
 
-int PSROIPoolingGradCpuKernelMod::ResizeCheckInputs(const std::vector<KernelTensorPtr> &inputs) {
+int PSROIPoolingGradCpuKernelMod::ResizeCheckInputs(const std::vector<KernelTensorPtr> &inputs) const {
   size_t input_num = inputs.size();
   if (input_num != INPUT_NUM) {
     MS_LOG(ERROR) << "For '" << kernel_name_ << "', input number is expected to be " << input_num
@@ -233,11 +244,15 @@ int PSROIPoolingGradCpuKernelMod::Resize(const BaseOperatorPtr &base_operator,
   feature_channels_ = output_channels_ * group_size_ * group_size_;
 
   for (auto tensor_ptr : inputs) {
-    if (tensor_ptr->IsDynamicShape()) return KRET_UNKNOWN_SHAPE;
+    if (tensor_ptr->IsDynamicShape()) {
+      return KRET_UNKNOWN_SHAPE;
+    }
   }
 
   for (auto tensor_ptr : outputs) {
-    if (tensor_ptr->IsDynamicShape()) return KRET_UNKNOWN_OUT_SHAPE;
+    if (tensor_ptr->IsDynamicShape()) {
+      return KRET_UNKNOWN_OUT_SHAPE;
+    }
   }
 
   auto dy_shape = inputs[0]->GetShapeVector();
@@ -287,11 +302,11 @@ bool PSROIPoolingGradCpuKernelMod::Launch(const std::vector<AddressPtr> &inputs,
                                           const std::vector<AddressPtr> &outputs) {
   auto output_size = output_channels_ * pooled_height_ * pooled_width_ * output_n_;
   if (data_type_id_ == kNumberTypeFloat32) {
-    auto top_diff = reinterpret_cast<float *>(inputs[0]->addr);
+    auto top_diff = static_cast<float *>(inputs[0]->addr);
     MS_EXCEPTION_IF_NULL(top_diff);
-    auto rois = reinterpret_cast<float *>(inputs[1]->addr);
+    auto rois = static_cast<float *>(inputs[1]->addr);
     MS_EXCEPTION_IF_NULL(rois);
-    auto output_diff = reinterpret_cast<float *>(outputs[0]->addr);
+    auto output_diff = static_cast<float *>(outputs[0]->addr);
     MS_EXCEPTION_IF_NULL(output_diff);
 
     constexpr size_t unit_size = sizeof(float);
@@ -308,11 +323,11 @@ bool PSROIPoolingGradCpuKernelMod::Launch(const std::vector<AddressPtr> &inputs,
   }
 
   if (data_type_id_ == kNumberTypeFloat16) {
-    auto top_diff = reinterpret_cast<float16 *>(inputs[0]->addr);
+    auto top_diff = static_cast<float16 *>(inputs[0]->addr);
     MS_EXCEPTION_IF_NULL(top_diff);
-    auto rois = reinterpret_cast<float16 *>(inputs[1]->addr);
+    auto rois = static_cast<float16 *>(inputs[1]->addr);
     MS_EXCEPTION_IF_NULL(rois);
-    auto output_diff = reinterpret_cast<float16 *>(outputs[0]->addr);
+    auto output_diff = static_cast<float16 *>(outputs[0]->addr);
     MS_EXCEPTION_IF_NULL(output_diff);
 
     constexpr size_t unit_size = sizeof(float16);
diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.h b/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.h
index 6c9bad116d0..170ef32599a 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.h
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/ps_roi_pooling_grad_cpu_kernel.h
@@ -25,14 +25,6 @@
 
 namespace mindspore {
 namespace kernel {
-#define INPUT_NUM 2
-#define OUTPUT_NUM 1
-#define OUT_PUT_SHAPE_SIZE 4
-#define DY_SHAPE_SIZE 4
-#define DX_SHAPE_SIZE 4
-#define ROI_SHAPE_SIZE 3
-#define ROIS_NUM_INDEX 2
-
 class PSROIPoolingGradCpuKernelMod : public NativeCpuKernelMod {
  public:
   PSROIPoolingGradCpuKernelMod() = default;
@@ -71,9 +63,9 @@ class PSROIPoolingGradCpuKernelMod : public NativeCpuKernelMod {
   TypeId data_type_id_{kNumberTypeFloat32};
 
   template <typename T>
-  void PSROIPoolBackward(size_t start, size_t end, const T *input_diff, T *output_diff, T *roi_boxes);
+  void PSROIPoolBackward(size_t start, size_t end, const T *input_diff, T *output_diff, T *roi_boxes) const;
 
-  int ResizeCheckInputs(const std::vector<KernelTensorPtr> &inputs);
+  int ResizeCheckInputs(const std::vector<KernelTensorPtr> &inputs) const;
 };
 }  // namespace kernel
 }  // namespace mindspore
diff --git a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.cc b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.cc
index 24cc775a9be..ad88df9b56e 100644
--- a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.cc
@@ -22,6 +22,13 @@ namespace {
 constexpr int kDyOutputDimIndex = 1;
 constexpr int kDyHeightIndex = 2;
 constexpr int kDyWidthIndex = 3;
+constexpr int INPUT_NUM = 2;
+constexpr int OUTPUT_NUM = 1;
+constexpr int OUT_PUT_SHAPE_SIZE = 4;
+constexpr int DY_SHAPE_SIZE = 4;
+constexpr int DX_SHAPE_SIZE = 4;
+constexpr int ROI_SHAPE_SIZE = 3;
+constexpr int ROIS_NUM_INDEX = 2;
 }  // namespace
 
 bool PSROIPoolingBackV2GpuKernelMod::Init(const BaseOperatorPtr &base_operator,
@@ -149,11 +156,15 @@ int PSROIPoolingBackV2GpuKernelMod::Resize(const BaseOperatorPtr &base_operator,
   feature_channels_ = output_channels_ * group_size_ * group_size_;
 
   for (auto tensor_ptr : inputs) {
-    if (tensor_ptr->IsDynamicShape()) return KRET_UNKNOWN_SHAPE;
+    if (tensor_ptr->IsDynamicShape()) {
+      return KRET_UNKNOWN_SHAPE;
+    }
   }
 
   for (auto tensor_ptr : outputs) {
-    if (tensor_ptr->IsDynamicShape()) return KRET_UNKNOWN_OUT_SHAPE;
+    if (tensor_ptr->IsDynamicShape()) {
+      return KRET_UNKNOWN_OUT_SHAPE;
+    }
   }
 
   auto dy_shape = inputs[0]->GetShapeVector();
@@ -203,28 +214,28 @@ bool PSROIPoolingBackV2GpuKernelMod::Launch(const std::vector<AddressPtr> &input
                                             const std::vector<AddressPtr> &workspace,
                                             const std::vector<AddressPtr> &outputs, void *stream_ptr) {
   if (data_type_id_ == kNumberTypeFloat32) {
-    auto top_diff = reinterpret_cast<float *>(inputs[0]->addr);
+    auto top_diff = static_cast<float *>(inputs[0]->addr);
     MS_EXCEPTION_IF_NULL(top_diff);
-    auto rois = reinterpret_cast<float *>(inputs[1]->addr);
+    auto rois = static_cast<float *>(inputs[1]->addr);
     MS_EXCEPTION_IF_NULL(rois);
-    auto output_diff = reinterpret_cast<float *>(outputs[0]->addr);
+    auto output_diff = static_cast<float *>(outputs[0]->addr);
     MS_EXCEPTION_IF_NULL(output_diff);
     PSROIPoolBackwardV2Launcher(top_diff, batch_size_, output_n_, static_cast<float>(spatial_scale_), feature_channels_,
                                 height_, width_, pooled_width_, pooled_height_, output_channels_, output_diff, rois,
-                                reinterpret_cast<cudaStream_t>(stream_ptr), rois_num_, group_size_);
+                                static_cast<cudaStream_t>(stream_ptr), rois_num_, group_size_);
     return true;
   }
 
   if (data_type_id_ == kNumberTypeFloat16) {
-    auto top_diff = reinterpret_cast<half *>(inputs[0]->addr);
+    auto top_diff = static_cast<half *>(inputs[0]->addr);
     MS_EXCEPTION_IF_NULL(top_diff);
-    auto rois = reinterpret_cast<half *>(inputs[1]->addr);
+    auto rois = static_cast<half *>(inputs[1]->addr);
     MS_EXCEPTION_IF_NULL(rois);
-    auto output_diff = reinterpret_cast<half *>(outputs[0]->addr);
+    auto output_diff = static_cast<half *>(outputs[0]->addr);
     MS_EXCEPTION_IF_NULL(output_diff);
     PSROIPoolBackwardV2Launcher(top_diff, batch_size_, output_n_, static_cast<half>(spatial_scale_), feature_channels_,
                                 height_, width_, pooled_width_, pooled_height_, output_channels_, output_diff, rois,
-                                reinterpret_cast<cudaStream_t>(stream_ptr), rois_num_, group_size_);
+                                static_cast<cudaStream_t>(stream_ptr), rois_num_, group_size_);
     return true;
   }
 
diff --git a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.h b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.h
index c0485972ad8..607c03169c4 100644
--- a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.h
+++ b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/ps_roi_pooling_grad_v2_gpu_kernel.h
@@ -29,14 +29,6 @@
 #include "plugin/device/gpu/kernel/cuda_impl/cuda_ops/psroi_pooling_v2_impl.cuh"
 namespace mindspore {
 namespace kernel {
-#define INPUT_NUM 2
-#define OUTPUT_NUM 1
-#define OUT_PUT_SHAPE_SIZE 4
-#define DY_SHAPE_SIZE 4
-#define DX_SHAPE_SIZE 4
-#define ROI_SHAPE_SIZE 3
-#define ROIS_NUM_INDEX 2
-
 class PSROIPoolingBackV2GpuKernelMod : public NativeGpuKernelMod {
  public:
   PSROIPoolingBackV2GpuKernelMod() = default;