diff --git a/paddle/pten/kernels/hybird/cpu/elementwise.h b/paddle/pten/kernels/hybird/cpu/elementwise.h
index e8213c8b45ddb1964f6861040fb2ec480cde950c..d503957a7626203aa930eba62bf4fee6d5b0cdb1 100644
--- a/paddle/pten/kernels/hybird/cpu/elementwise.h
+++ b/paddle/pten/kernels/hybird/cpu/elementwise.h
@@ -130,16 +130,15 @@ void CommonElementwiseBroadcastForward(
                                                  is_xsize_larger);
 }
 
-// It is a common implementation to compute binary calculation with the support
-// of broadcast, supporting both CPU and GPU.
-// - CPU implementation cannot support the case when x needs broadcast, thus
-//   this function need to be called with XxxFunctor and XxxInverseFunctor,
-//   like paddle/fluid/operators/elementwise/elementwise_add_op.h#L49 - L55.
-// - GPU implementation supports all the broadcast cases, thus there is no need
-//   to define and call with XxxInverseFunctor.
+// It is a common CPU implementation to compute binary calculation with the
+// support of broadcast. Note:
+// 1. CPU implementation cannot support the case when x needs broadcast, thus
+//    this function need to be called with XxxFunctor and XxxInverseFunctor,
+//    like AddFunctor and InverseAddFunctor.
+// 2. The corresponding GPU implementation supports all the broadcast cases,
+//    thus there is no need to define and call with XxxInverseFunctor.
 // TODO(liuyiqun): optimize the CPU implementation to support all broadcast
 // cases and avoid the need of XxxInverseFunctor.
-
 template <typename Functor, typename T, typename OutType = T>
 void ElementwiseCompute(const paddle::platform::CPUDeviceContext &dev_ctx,
                         const DenseTensor &x,