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diff --git a/tensorflow/core/kernels/l2loss_op.h b/tensorflow/core/kernels/l2loss_op.h
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+++ b/tensorflow/core/kernels/l2loss_op.h
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+#ifndef TENSORFLOW_KERNELS_L2LOSS_OP_H_
+#define TENSORFLOW_KERNELS_L2LOSS_OP_H_
+// Functor definition for L2LossOp, must be compilable by nvcc.
+#include "tensorflow/core/framework/tensor_types.h"
+#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
+
+namespace tensorflow {
+namespace functor {
+
+// Functor used by L2LossOp to do the computations.
+template <typename Device, typename T>
+struct L2Loss {
+  void operator()(const Device& d, typename TTypes<T>::ConstTensor input,
+                  typename TTypes<T>::Scalar output) {
+    // We flatten the input tensor and reduce on dimension 0, producing
+    // a single number which is Mul(Sum(x^2), 0.5).
+    output.device(d) = input.square().sum() * static_cast<T>(0.5);
+  }
+};
+
+}  // namespace functor
+}  // namespace tensorflow
+
+#endif  // TENSORFLOW_KERNELS_L2LOSS_OP_H_