fix compiling werror (#43337)

paddle/fluid/operators/detection/locality_aware_nms_op.cc

@@ -316,7 +316,7 @@ class LocalityAwareNMSKernel : public framework::OpKernel<T> {
     auto* boxes_input = ctx.Input<LoDTensor>("BBoxes");
     auto* scores_input = ctx.Input<LoDTensor>("Scores");
     auto* outs = ctx.Output<LoDTensor>("Out");
-    auto score_dims = scores_input->dims();
+    auto& score_dims = scores_input->dims();
     auto score_size = score_dims.size();
     auto& dev_ctx = ctx.template device_context<platform::CPUDeviceContext>();
 

paddle/fluid/operators/detection/retinanet_detection_output_op.cc

@@ -471,7 +471,7 @@ class RetinanetDetectionOutputKernel : public framework::OpKernel<T> {
       std::vector<Tensor> box_per_batch_list(boxes_list.size());
       std::vector<Tensor> score_per_batch_list(scores_list.size());
       for (size_t j = 0; j < boxes_list.size(); ++j) {
-        auto score_dims = scores_list[j].dims();
+        const auto& score_dims = scores_list[j].dims();
         score_per_batch_list[j] = scores_list[j].Slice(i, i + 1);
         score_per_batch_list[j].Resize({score_dims[1], score_dims[2]});
         box_per_batch_list[j] = boxes_list[j].Slice(i, i + 1);

paddle/fluid/operators/math/softmax_impl.h

@@ -262,7 +262,7 @@ class SoftmaxFunctor<DeviceContext, float, true, enable_if_CPU<DeviceContext>> {
  public:
   void operator()(const DeviceContext& context, const int axis_dim,
                   const framework::Tensor* X, framework::Tensor* Y) {
-    auto in_dims = X->dims();
+    const auto& in_dims = X->dims();
     const float* in_data = X->data<float>();
     float* out_data = Y->data<float>();
     const int kBatchDim = 0;
@@ -387,7 +387,7 @@ class SoftmaxGradFunctor<DeviceContext, T, enable_if_CPU<DeviceContext>> {
   void operator()(const DeviceContext& context, const int axis_dim,
                   const framework::Tensor* y, const framework::Tensor* y_grad,
                   framework::Tensor* x_grad) {
-    auto out_dims = y->dims();
+    const auto& out_dims = y->dims();
     constexpr int kBatchDim = 0;
     constexpr int kClassDim = 1;
     const int num_classes = out_dims[kClassDim];

paddle/fluid/operators/shuffle_channel_op.h

@@ -27,7 +27,7 @@ class ShuffleChannelOpKernel : public framework::OpKernel<T> {
     auto* output = ctx.Output<framework::Tensor>("Out");
     int group = ctx.Attr<int>("group");
 
-    auto input_dims = input->dims();
+    const auto& input_dims = input->dims();
     auto num = input_dims[0];
     auto channel = input_dims[1];
     auto height = input_dims[2];

paddle/phi/kernels/impl/lerp_kernel_impl.h

@@ -28,7 +28,7 @@ static void LerpFunction(const Context& ctx,
                          DenseTensor* out) {
   ctx.template Alloc<T>(out);
 
-  auto out_dims = out->dims();
+  const auto& out_dims = out->dims();
   auto x_dims = phi::funcs::ExtendDims2Rank(x.dims(), D);
   auto y_dims = phi::funcs::ExtendDims2Rank(y.dims(), D);
   auto w_dims = phi::funcs::ExtendDims2Rank(weight.dims(), D);