diff --git a/tensorflow/core/kernels/image_resizer_state.h b/tensorflow/core/kernels/image_resizer_state.h
index 591acfb444a..1b1550fd47a 100644
--- a/tensorflow/core/kernels/image_resizer_state.h
+++ b/tensorflow/core/kernels/image_resizer_state.h
@@ -48,6 +48,7 @@ inline float CalculateResizeScale(int64 in_size, int64 out_size,
 // Half pixel scaler scales assuming that the pixel centers are at 0.5, i.e. the
 // floating point coordinates of the top,left pixel is 0.5,0.5.
 struct HalfPixelScaler {
+  HalfPixelScaler(){};
   inline float operator()(const int x, const float scale) const {
     // Note that we subtract 0.5 from the return value, as the existing bilinear
     // sampling code etc assumes pixels are in the old coordinate system.
@@ -59,6 +60,7 @@ struct HalfPixelScaler {
 // translation leading to inconsistent results. For example, a flip then a
 // resize gives different results then a resize then a flip.
 struct LegacyScaler {
+  LegacyScaler(){};
   inline float operator()(const int x, const float scale) const {
     return static_cast<float>(x) * scale;
   }
diff --git a/tensorflow/core/kernels/redux_functor.h b/tensorflow/core/kernels/redux_functor.h
index 05a867ab007..24dc876ef8e 100644
--- a/tensorflow/core/kernels/redux_functor.h
+++ b/tensorflow/core/kernels/redux_functor.h
@@ -37,6 +37,7 @@ namespace functor {
 //   output: [Di, ... , DN] where i belongs to set [1,N]
 template <typename T, typename AccumT, typename BinaryFunctor>
 struct ReduceOuterDimensions {
+  ReduceOuterDimensions(){};
   template <int num_dims>
   void operator()(const CPUDevice& device,
                   const Eigen::DSizes<Eigen::Index, num_dims>& input_dims,
@@ -198,6 +199,7 @@ struct ReduceOuterDimensions {
 //   output: [Di, ... , Dj] where i & j belongs to set [1,N].
 template <typename T, typename AccumT, typename BinaryFunctor, typename Reducer>
 struct ReduceMiddleDimensions {
+  ReduceMiddleDimensions(){};
   template <int num_dims>
   void operator()(const CPUDevice& device,
                   const Eigen::DSizes<Eigen::Index, num_dims>& input_dims,
@@ -256,7 +258,7 @@ struct ReduceMiddleDimensions {
     using Input = Eigen::TensorMap<Eigen::Tensor<const T, 1>>;
 
     Eigen::array<Eigen::Index, 1> reduction_axis = {0};
-    const Reducer reducer;
+    Reducer reducer;
     const BinaryFunctor binary_op;
 
     const auto compute = [inner_dim, middle_dim, input_data, buffer_data,