[clang-tidy] enable bugprone-incorrect-roundings check (#56747)

.clang-tidy

@@ -12,7 +12,7 @@ bugprone-exception-escape,
 -bugprone-fold-init-type,
 -bugprone-forwarding-reference-overload,
 -bugprone-inaccurate-erase,
--bugprone-incorrect-roundings,
+bugprone-incorrect-roundings,
 -bugprone-infinite-loop,
 bugprone-integer-division,
 -bugprone-macro-repeated-side-effects,

paddle/fluid/operators/detection/mask_util.cc

@@ -51,9 +51,9 @@ void Poly2Mask(const float* xy, int k, int h, int w, uint8_t* mask) {
   x = reinterpret_cast<int*>(xptr->ptr());
   y = x + (k + 1);
 
-  for (j = 0; j < k; j++) x[j] = static_cast<int>(scale * xy[j * 2 + 0] + .5);
+  for (j = 0; j < k; j++) x[j] = std::lround(scale * xy[j * 2 + 0]);
   x[k] = x[0];
-  for (j = 0; j < k; j++) y[j] = static_cast<int>(scale * xy[j * 2 + 1] + .5);
+  for (j = 0; j < k; j++) y[j] = std::lround(scale * xy[j * 2 + 1]);
   y[k] = y[0];
   for (j = 0; j < k; j++) {
     m += UMax(abs(x[j] - x[j + 1]), abs(y[j] - y[j + 1])) + 1;
@@ -82,7 +82,7 @@ void Poly2Mask(const float* xy, int k, int h, int w, uint8_t* mask) {
       for (d = 0; d <= dx; d++) {
         t = flip ? dx - d : d;
         u[m] = t + xs;
-        v[m] = static_cast<int>(ys + s * t + .5);
+        v[m] = std::lround(ys + s * t);
         m++;
       }
     } else {
@@ -90,7 +90,7 @@ void Poly2Mask(const float* xy, int k, int h, int w, uint8_t* mask) {
       for (d = 0; d <= dy; d++) {
         t = flip ? dy - d : d;
         v[m] = t + ys;
-        u[m] = static_cast<int>(xs + s * t + .5);
+        u[m] = std::lround(xs + s * t);
         m++;
       }
     }

paddle/phi/kernels/cpu/interpolate_grad_kernel.cc

@@ -359,17 +359,17 @@ static void NearestNeighbor3DInterpolateGrad(const DenseTensor& output_grad,
   auto output_grad_t = EigenTensor<T, 5>::From(output_grad);
 
   for (int d = 0; d < out_d; d++) {
-    int in_d = static_cast<int>(align_corners
-                                    ? (ratio_d * static_cast<float>(d) + 0.5f)
-                                    : (ratio_d * static_cast<float>(d)));
+    int in_d = static_cast<int>(
+        align_corners ? std::lround(ratio_d * static_cast<float>(d))
+                      : (ratio_d * static_cast<float>(d)));
     for (int k = 0; k < out_h; k++) {  // loop for images
-      int in_k = static_cast<int>(align_corners
-                                      ? (ratio_h * static_cast<float>(k) + 0.5f)
-                                      : (ratio_h * static_cast<float>(k)));
+      int in_k = static_cast<int>(
+          align_corners ? std::lround(ratio_h * static_cast<float>(k))
+                        : (ratio_h * static_cast<float>(k)));
 
       for (int l = 0; l < out_w; l++) {
         int in_l = static_cast<int>(
-            align_corners ? (ratio_w * static_cast<float>(l) + 0.5f)
+            align_corners ? std::lround(ratio_w * static_cast<float>(l))
                           : (ratio_w * static_cast<float>(l)));
 
         for (int i = 0; i < n; i++) {    // loop for batches

paddle/phi/kernels/cpu/interpolate_kernel.cc

@@ -232,12 +232,12 @@ static void NearestNeighborInterpolate(const DenseTensor& input,
 
   for (int k = 0; k < out_h; k++) {  // loop for images
     int in_k = (align_corners)
-                   ? static_cast<int>(ratio_h * static_cast<float>(k) + 0.5)
+                   ? std::lround(ratio_h * static_cast<float>(k))
                    : static_cast<int>(ratio_h * static_cast<float>(k));
 
     for (int l = 0; l < out_w; l++) {
       int in_l = (align_corners)
-                     ? static_cast<int>(ratio_w * static_cast<float>(l) + 0.5)
+                     ? std::lround(ratio_w * static_cast<float>(l))
                      : static_cast<int>(ratio_w * static_cast<float>(l));
 
       for (int i = 0; i < n; i++) {    // loop for batches
@@ -515,16 +515,16 @@ static void NearestNeighbor3DInterpolate(const DenseTensor& input,
   auto output_t = EigenTensor<T, 5>::From(*output);
   for (int d = 0; d < out_d; d++) {  // loop for images
     int in_d = (align_corners)
-                   ? static_cast<int>(ratio_d * static_cast<float>(d) + 0.5)
+                   ? std::lround(ratio_d * static_cast<float>(d))
                    : static_cast<int>(ratio_d * static_cast<float>(d));
     for (int k = 0; k < out_h; k++) {
       int in_k = (align_corners)
-                     ? static_cast<int>(ratio_h * static_cast<float>(k) + 0.5)
+                     ? std::lround(ratio_h * static_cast<float>(k))
                      : static_cast<int>(ratio_h * static_cast<float>(k));
 
       for (int l = 0; l < out_w; l++) {
         int in_l = (align_corners)
-                       ? static_cast<int>(ratio_w * static_cast<float>(l) + 0.5)
+                       ? std::lround(ratio_w * static_cast<float>(l))
                        : static_cast<int>(ratio_w * static_cast<float>(l));
 
         for (int i = 0; i < n; i++) {    // loop for batches

paddle/phi/kernels/cpu/roi_align_grad_kernel.cc

@@ -170,11 +170,11 @@ void RoiAlignGradKernel(const Context& dev_ctx,
           T count = roi_bin_grid_h * roi_bin_grid_w;
           for (int iy = 0; iy < roi_bin_grid_h; iy++) {
             const T y = roi_ymin + ph * bin_size_h +
-                        static_cast<T>(iy + .5f) * bin_size_h /
+                        static_cast<T>(iy + .5f) * bin_size_h /  // NOLINT
                             static_cast<T>(roi_bin_grid_h);
             for (int ix = 0; ix < roi_bin_grid_w; ix++) {
               const T x = roi_xmin + pw * bin_size_w +
-                          static_cast<T>(ix + .5f) * bin_size_w /
+                          static_cast<T>(ix + .5f) * bin_size_w /  // NOLINT
                               static_cast<T>(roi_bin_grid_w);
               bilinear_interpolate_gradient(height,
                                             width,

paddle/phi/kernels/cpu/roi_align_kernel.cc

@@ -79,12 +79,13 @@ std::vector<OffsetsAndRatios<T>> GetIndexesAndRatios(
     for (std::size_t px = 0; px < pooled_width; px++) {
       for (std::size_t iy = 0; iy < roi_bin_grid_h; iy++) {
         // calculate x of sample points
-        auto y = roi_ymin + bin_h * (py + static_cast<T>(iy + .5f) /
+        auto y = roi_ymin + bin_h * (py + static_cast<T>(iy + .5f) /  // NOLINT
                                               static_cast<T>(roi_bin_grid_h));
         for (std::size_t ix = 0; ix < roi_bin_grid_w; ix++) {
           // calculate x of sample points
-          auto x = roi_xmin + bin_w * (px + static_cast<T>(ix + .5f) /
-                                                static_cast<T>(roi_bin_grid_w));
+          auto x =
+              roi_xmin + bin_w * (px + static_cast<T>(ix + .5f) /  // NOLINT
+                                           static_cast<T>(roi_bin_grid_w));
 
           // deal with elements out of map
           if (y < -1.0 || y > height || x < -1.0 || x > width) {