1 files changed, 16 insertions, 20 deletions

diff --git a/tensorflow/core/kernels/non_max_suppression_op.cc b/tensorflow/core/kernels/non_max_suppression_op.cc
index dc95f67ff0..9ffe71e031 100644
--- a/tensorflow/core/kernels/non_max_suppression_op.cc
+++ b/tensorflow/core/kernels/non_max_suppression_op.cc
@@ -90,24 +90,20 @@ static inline float ComputeIOU(typename TTypes<float, 2>::ConstTensor boxes,
   return intersection_area / (area_i + area_j - intersection_area);
 }
 
-void DoNonMaxSuppressionOp(OpKernelContext* context,
-                           const Tensor& boxes,
-                           const Tensor& scores,
-                           const Tensor& max_output_size,
+void DoNonMaxSuppressionOp(OpKernelContext* context, const Tensor& boxes,
+                           const Tensor& scores, const Tensor& max_output_size,
                            const float iou_threshold) {
   OP_REQUIRES(context, iou_threshold >= 0 && iou_threshold <= 1,
-      errors::InvalidArgument("iou_threshold must be in [0, 1]"));
-  
+              errors::InvalidArgument("iou_threshold must be in [0, 1]"));
+
   int num_boxes = 0;
   ParseAndCheckBoxSizes(context, boxes, scores, &num_boxes);
   if (!context->status().ok()) {
     return;
   }
 
-  const int output_size =
-      std::min(max_output_size.scalar<int>()(), num_boxes);
-  typename TTypes<float, 2>::ConstTensor boxes_data =
-      boxes.tensor<float, 2>();
+  const int output_size = std::min(max_output_size.scalar<int>()(), num_boxes);
+  typename TTypes<float, 2>::ConstTensor boxes_data = boxes.tensor<float, 2>();
 
   std::vector<float> scores_data(num_boxes);
   std::copy_n(scores.flat<float>().data(), num_boxes, scores_data.begin());
@@ -127,7 +123,7 @@ void DoNonMaxSuppressionOp(OpKernelContext* context,
     for (int j = i + 1; j < num_boxes; ++j) {
       if (active[j]) {
         float iou =
-          ComputeIOU(boxes_data, sorted_indices[i], sorted_indices[j]);
+            ComputeIOU(boxes_data, sorted_indices[i], sorted_indices[j]);
         if (iou > iou_threshold) {
           active[j] = false;
           num_active--;
@@ -145,7 +141,7 @@ void DoNonMaxSuppressionOp(OpKernelContext* context,
   std::copy_n(selected.begin(), selected.size(), selected_indices_data.data());
 }
 
-} // namespace
+}  // namespace
 
 template <typename Device>
 class NonMaxSuppressionOp : public OpKernel {
@@ -167,7 +163,8 @@ class NonMaxSuppressionOp : public OpKernel {
         errors::InvalidArgument("max_output_size must be 0-D, got shape ",
                                 max_output_size.shape().DebugString()));
 
-    DoNonMaxSuppressionOp(context, boxes, scores, max_output_size, iou_threshold_);
+    DoNonMaxSuppressionOp(context, boxes, scores, max_output_size,
+                          iou_threshold_);
   }
 
  private:
@@ -178,8 +175,7 @@ template <typename Device>
 class NonMaxSuppressionV2Op : public OpKernel {
  public:
   explicit NonMaxSuppressionV2Op(OpKernelConstruction* context)
-      : OpKernel(context) {
-  }
+      : OpKernel(context) {}
 
   void Compute(OpKernelContext* context) override {
     // boxes: [num_boxes, 4]
@@ -194,14 +190,14 @@ class NonMaxSuppressionV2Op : public OpKernel {
                                 max_output_size.shape().DebugString()));
     // iou_threshold: scalar
     const Tensor& iou_threshold = context->input(3);
-    OP_REQUIRES(
-        context, TensorShapeUtils::IsScalar(iou_threshold.shape()),
-        errors::InvalidArgument("iou_threshold must be 0-D, got shape ",
-                                iou_threshold.shape().DebugString()));
+    OP_REQUIRES(context, TensorShapeUtils::IsScalar(iou_threshold.shape()),
+                errors::InvalidArgument("iou_threshold must be 0-D, got shape ",
+                                        iou_threshold.shape().DebugString()));
 
     const float iou_threshold_val = iou_threshold.scalar<float>()();
 
-    DoNonMaxSuppressionOp(context, boxes, scores, max_output_size, iou_threshold_val);
+    DoNonMaxSuppressionOp(context, boxes, scores, max_output_size,
+                          iou_threshold_val);
   }
 };