diff --git a/paddle/fluid/operators/detection/multiclass_nms_op.cc b/paddle/fluid/operators/detection/multiclass_nms_op.cc
index 9dc6a8cc1f29ecb574804f0916c91620f9c73376..ed5fca119cf9ee94a1ad1aa2b7959e485eb143a0 100644
--- a/paddle/fluid/operators/detection/multiclass_nms_op.cc
+++ b/paddle/fluid/operators/detection/multiclass_nms_op.cc
@@ -361,7 +361,7 @@ class MultiClassNMSKernel : public framework::OpKernel<T> {
     auto index = ctx.Output<phi::DenseTensor>("Index");
     bool has_roisnum = ctx.HasInput("RoisNum") ? true : false;
     auto rois_num = ctx.Input<phi::DenseTensor>("RoisNum");
-    auto score_dims = scores->dims();
+    auto score_dims = phi::vectorize<int>(scores->dims());
     auto score_size = score_dims.size();
     auto& dev_ctx = ctx.template device_context<phi::CPUContext>();
 
diff --git a/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc b/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc
index fcbc3237cc0fae8f3bf20794bba9d382f44f8cb4..b42c52cf5cabaf78150e8869c104b25571e4c545 100644
--- a/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc
+++ b/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc
@@ -153,7 +153,7 @@ class FusionRepeatedFCReluKernel : public framework::OpKernel<T> {
     auto place = ctx.GetPlace();
     int weight_sz = static_cast<int>(weights.size());
 
-    auto i_dims = in->dims();
+    auto i_dims = phi::vectorize<int>(in->dims());
     const auto& w_dims = weights[0]->dims();
     phi::jit::matmul_attr_t attr;
     attr.m = i_dims[0];
diff --git a/paddle/fluid/pybind/tensor_py.h b/paddle/fluid/pybind/tensor_py.h
index 607aa5a894cc3e8fa25e4d04c1e912d031dc1dd6..ea024205faf3935d29ce7daf8b2d9c805d5e6e4d 100644
--- a/paddle/fluid/pybind/tensor_py.h
+++ b/paddle/fluid/pybind/tensor_py.h
@@ -689,7 +689,7 @@ void _sliceCompute(const phi::DenseTensor *in,
                    const std::vector<int> &axes,
                    const std::vector<int> &starts) {
   auto &eigen_place = *ctx.eigen_device();
-  auto out_dims = out->dims();
+  auto out_dims = phi::vectorize<int>(out->dims());
   auto in_dims = in->dims();
 
   auto offsets = Eigen::DSizes<Eigen::DenseIndex, D>();
diff --git a/paddle/phi/kernels/cpu/matrix_nms_kernel.cc b/paddle/phi/kernels/cpu/matrix_nms_kernel.cc
index 3c51468e7c713ea86e4d5e75e6f7c22c8e5cfa34..942b7fabf6af56f7431e6e7516c753aaadfafe97 100644
--- a/paddle/phi/kernels/cpu/matrix_nms_kernel.cc
+++ b/paddle/phi/kernels/cpu/matrix_nms_kernel.cc
@@ -255,7 +255,7 @@ void MatrixNMSKernel(const Context& ctx,
                      DenseTensor* out,
                      DenseTensor* index,
                      DenseTensor* roisnum) {
-  auto score_dims = scores.dims();
+  auto score_dims = phi::vectorize<int>(scores.dims());
   auto batch_size = score_dims[0];
   auto num_boxes = score_dims[2];
   auto box_dim = bboxes.dims()[2];
diff --git a/paddle/phi/kernels/cpu/multiclass_nms3_kernel.cc b/paddle/phi/kernels/cpu/multiclass_nms3_kernel.cc
index dc82ffbea8791c46190c7d381e5d35507e9f9693..d7772e1c3be621e80129a563315a3b8f45511d16 100644
--- a/paddle/phi/kernels/cpu/multiclass_nms3_kernel.cc
+++ b/paddle/phi/kernels/cpu/multiclass_nms3_kernel.cc
@@ -496,7 +496,7 @@ void MultiClassNMSKernel(const Context& ctx,
                          DenseTensor* nms_rois_num) {
   bool return_index = index != nullptr;
   bool has_roisnum = rois_num.get_ptr() != nullptr;
-  auto score_dims = scores.dims();
+  auto score_dims = phi::vectorize<int>(scores.dims());
   auto score_size = score_dims.size();
 
   std::vector<std::map<int, std::vector<int>>> all_indices;
diff --git a/paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc b/paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc
index dcb4399aa28627f894132ed52d24568a5dcd6252..99ccb878e425425368b2653b4caa5d8b6ed7298f 100644
--- a/paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc
+++ b/paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc
@@ -258,7 +258,7 @@ void CooToDenseCPUKernel(const CPUContext& dev_ctx,
   const auto dense_dims = x.dims();
   const auto indices = x.indices();
   const auto values = x.values();
-  const auto indices_dims = indices.dims();
+  const auto indices_dims = phi::vectorize<int>(indices.dims());
   int64_t sparse_dim = indices_dims[0];
   if (indices_dims.size() == 1) {
     sparse_dim = 1;