diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_cpu_kernel.cc
index 2e0010881f0..5a3e1b77e2f 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_cpu_kernel.cc
@@ -177,31 +177,30 @@ void MirrorPadCpuKernelMod::LaunchKernel(const std::vector<AddressPtr> &inputs,
     int64_t matchval_y_index = padded_y;
     int64_t matchval_channel_index = padded_channel;
     int64_t matchval_batch_index = padded_batch;
-    int64_t equiv_block_num = 0;
 
     // update matching index in original tensor across all 4 dims
     if ((padded_x < ap1_x) || (padded_x > ap2_x)) {
       int64_t x_dist = (padded_x < ap1_x) ? (ap1_x - padded_x) : (padded_x - ap2_x);
-      matchval_x_index = (padded_x < ap1_x) ? (ap1_x + x_dist - mode) : (ap2_x - x_dist + mode);
+      matchval_x_index = (padded_x < ap1_x) ? ((ap1_x + x_dist) - mode) : ((ap2_x - x_dist) + mode);
     }
     if ((padded_y < ap1_y) || (padded_y > ap2_y)) {
       int64_t y_dist = (padded_y < ap1_y) ? (ap1_y - padded_y) : (padded_y - ap2_y);
-      matchval_y_index = (padded_y < ap1_y) ? (ap1_y + y_dist - mode) : (ap2_y - y_dist + mode);
+      matchval_y_index = (padded_y < ap1_y) ? ((ap1_y + y_dist) - mode) : ((ap2_y - y_dist) + mode);
     }
     if ((padded_channel < ap1_channel) || (padded_channel > ap2_channel)) {
       int64_t channel_dist =
         (padded_channel < ap1_channel) ? (ap1_channel - padded_channel) : (padded_channel - ap2_channel);
       matchval_channel_index =
-        (padded_channel < ap1_channel) ? (ap1_channel + channel_dist - mode) : (ap2_channel - channel_dist + mode);
+        (padded_channel < ap1_channel) ? ((ap1_channel + channel_dist) - mode) : ((ap2_channel - channel_dist) + mode);
     }
     if ((padded_batch < ap1_batch) || (padded_batch > ap2_batch)) {
       int64_t batch_dist = (padded_batch < ap1_batch) ? (ap1_batch - padded_batch) : (padded_batch - ap2_batch);
       matchval_batch_index =
-        (padded_batch < ap1_batch) ? (ap1_batch + batch_dist - mode) : (ap2_batch - batch_dist + mode);
+        (padded_batch < ap1_batch) ? ((ap1_batch + batch_dist) - mode) : ((ap2_batch - batch_dist) + mode);
     }
 
     // calculate equivalent block in input
-    equiv_block_num =
+    int64_t equiv_block_num =
       ((matchval_batch_index - paddings[BATCH]) * old_channel) + (matchval_channel_index - paddings[CHANNEL]);
 
     // copy data from equiv block and adjusted x and y values in unpadded tensor
diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_grad_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_grad_cpu_kernel.cc
index 37bd23a7e33..ec13e411ed9 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_grad_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/mirror_pad_grad_cpu_kernel.cc
@@ -95,7 +95,7 @@ void MirrorPadGradCpuKernelMod::InitKernel(const CNodePtr &kernel_node) {
     output_shape_.push_back(SizeToLong(x));
   }
 
-  for (int i = 0; i < 2; i++) {
+  for (size_t i = 0; i < 2; i++) {
     workspace_size_ *= output_shape[i];
     workspace_size_ *= input_shape[i + 2];
   }
@@ -195,10 +195,10 @@ void MirrorPadGradCpuKernelMod::MirrorPadGrad_Width_Height(const size_t size, co
     // copy position's own value into output
     dx[pos] = interim_dy[(dx_block_num * dy_height + grad_y) * dy_width + grad_x];
 
-    int64_t x_dist_1 = (ap1_x - grad_x - mode);
-    int64_t y_dist_1 = (ap1_y - grad_y - mode);
-    int64_t x_dist_2 = (ap2_x - grad_x + mode);
-    int64_t y_dist_2 = (ap2_y - grad_y + mode);
+    int64_t x_dist_1 = ((ap1_x - grad_x) - mode);
+    int64_t y_dist_1 = ((ap1_y - grad_y) - mode);
+    int64_t x_dist_2 = ((ap2_x - grad_x) + mode);
+    int64_t y_dist_2 = ((ap2_y - grad_y) + mode);
     int64_t axis_dist[] = {x_dist_1, x_dist_2, y_dist_1, y_dist_2};
     int64_t anch_point[] = {ap1_x, ap2_x, ap1_y, ap2_y};
     bool x_axis_check[] = {true, true, false, false};  // true - update X , false - update Y
@@ -272,8 +272,7 @@ void MirrorPadGradCpuKernelMod::MirrorPadGradBatchChannel(const size_t size, T1
     const int64_t equiv_dy_batch = interim_batch + paddings[BATCH];
     int64_t target_batch = 0;
     int64_t target_channel = 0;
-    int64_t equiv_block_num = 0;
-    equiv_block_num = ((equiv_dy_batch * dy_channels) + equiv_dy_channel);
+    int64_t equiv_block_num = ((equiv_dy_batch * dy_channels) + equiv_dy_channel);
     // generate values to sweep over all possible mirrored points
     int64_t batch_offsets[] = {2 * (ap1_batch - equiv_dy_batch) - mode, 0, 2 * (ap2_batch - equiv_dy_batch) + mode};
     int64_t channel_offsets[] = {2 * (ap1_channel - equiv_dy_channel) - mode, 0,
diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/pad_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/pad_cpu_kernel.cc
index a7d1ea14c24..a6fea3d5805 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/pad_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/pad_cpu_kernel.cc
@@ -28,8 +28,7 @@ constexpr size_t kPadElemSize = 2;
 void PadCpuKernelMod::InitKernel(const CNodePtr &kernel_node) {
   MS_EXCEPTION_IF_NULL(kernel_node);
   kernel_name_ = common::AnfAlgo::GetCNodeName(kernel_node);
-  std::vector<std::vector<int64_t>> paddings_ =
-    common::AnfAlgo::GetNodeAttr<std::vector<std::vector<int64_t>>>(kernel_node, "paddings");
+  paddings_ = common::AnfAlgo::GetNodeAttr<std::vector<std::vector<int64_t>>>(kernel_node, "paddings");
   dtype_ = AnfAlgo::GetInputDeviceDataType(kernel_node, 0);
   input_shape_ = common::AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
   std::vector<size_t> output_shape = AnfAlgo::GetOutputDeviceShape(kernel_node, 0);
@@ -53,8 +52,8 @@ void PadCpuKernelMod::InitKernel(const CNodePtr &kernel_node) {
 
   for (size_t i = 0; i < input_rank_; i++) {
     input_size_ *= input_shape_[i];
-    output_size_ *=
-      (input_shape_[i] + flattened_paddings_[kPadElemSize * i] + flattened_paddings_[(kPadElemSize * i) + 1]);
+    output_size_ *= (input_shape_[i] + IntToSize(flattened_paddings_[kPadElemSize * i]) +
+                     IntToSize(flattened_paddings_[(kPadElemSize * i) + 1]));
   }
 
   if (input_rank_ < 1) {
@@ -70,7 +69,8 @@ void PadCpuKernelMod::InitKernel(const CNodePtr &kernel_node) {
   strides_.resize(input_rank_);
   strides_[input_rank_ - 1] = 1;
   for (int32_t i = input_rank_ - 2; i >= 0; i--) {
-    strides_[i] = output_shape[i + 1] * strides_[i + 1];
+    size_t ind = IntToSize(i);
+    strides_[ind] = output_shape[ind + 1] * strides_[ind + 1];
   }
 }
 
@@ -109,7 +109,8 @@ bool PadCpuKernelMod::LaunchKernel(const std::vector<AddressPtr> &inputs, const
       for (size_t i = input_rank_; i >= 1; i--) {
         size_t unravel_dimension = input_shape_[i - 1];
         size_t unraveled_index = linear_index % unravel_dimension;
-        padded_linear_index += ((unraveled_index + flattened_paddings_[kPadElemSize * (i - 1)]) * strides_[i - 1]);
+        padded_linear_index +=
+          ((unraveled_index + IntToSize(flattened_paddings_[kPadElemSize * (i - 1)])) * strides_[i - 1]);
         linear_index -= unraveled_index;
         linear_index /= unravel_dimension;
       }
diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/resize_bilinear_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/resize_bilinear_cpu_kernel.cc
index 8b309d87a75..1e2ff3c3b0a 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/resize_bilinear_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/resize_bilinear_cpu_kernel.cc
@@ -44,8 +44,8 @@ void ResizeBilinearCpuKernelMod::InitKernel(const CNodePtr &kernel_node) {
   }
   size_t in_height = shape_[2];
   size_t in_width = shape_[3];
-  size_t out_height = size_[0];
-  size_t out_width = size_[1];
+  size_t out_height = LongToSize(size_[0]);
+  size_t out_width = LongToSize(size_[1]);
   height_scale = Scaling(in_height, out_height, align_corners_);
   width_scale = Scaling(in_width, out_width, align_corners_);
 }
@@ -105,8 +105,8 @@ bool ResizeBilinearCpuKernelMod::LaunchKernel(const std::vector<AddressPtr> &inp
   size_t channel = shape_[1];
   size_t in_height = shape_[2];
   size_t in_width = shape_[3];
-  size_t out_height = size_[0];
-  size_t out_width = size_[1];
+  size_t out_height = LongToSize(size_[0]);
+  size_t out_width = LongToSize(size_[1]);
   size_t out_hw_size = out_height * out_width;
   size_t in_hw_size = in_height * in_width;
   size_t bhwc_size = in_hw_size * channel * batch_size;
diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/resize_nearest_neighbor_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/resize_nearest_neighbor_cpu_kernel.cc
index 55c19a3b4c1..04218ccbaf1 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/resize_nearest_neighbor_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/resize_nearest_neighbor_cpu_kernel.cc
@@ -48,8 +48,8 @@ void ResizeNearestNeighborCpuKernelMod::InitKernel(const CNodePtr &kernel_node)
   channel_ = input_shape[1];
   in_height_ = input_shape[2];
   in_width_ = input_shape[3];
-  out_height_ = output_size[0];
-  out_width_ = output_size[1];
+  out_height_ = LongToSize(output_size[0]);
+  out_width_ = LongToSize(output_size[1]);
   height_scale_ = Scaling(in_height_, out_height_, align_corners_);
   width_scale_ = Scaling(in_width_, out_width_, align_corners_);
   output_size_ = batch_size_ * channel_ * out_height_ * out_width_;