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diff --git a/tensorflow/core/kernels/relu_op.h b/tensorflow/core/kernels/relu_op.h
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+++ b/tensorflow/core/kernels/relu_op.h
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+#ifndef TENSORFLOW_KERNELS_RELU_OP_H_
+#define TENSORFLOW_KERNELS_RELU_OP_H_
+// Functor definition for ReluOp and ReluGradOp, 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 ReluOp to do the computations.
+template <typename Device, typename T>
+struct Relu {
+  // Computes Relu activation.
+  //
+  // features: any shape.
+  // activations: same shape as "features".
+  void operator()(const Device& d, typename TTypes<T>::ConstTensor features,
+                  typename TTypes<T>::Tensor activations) {
+    activations.device(d) = features.cwiseMax(static_cast<T>(0));
+  }
+};
+
+// Functor used by ReluGradOp to do the computations.
+template <typename Device, typename T>
+struct ReluGrad {
+  // Computes ReluGrad backprops.
+  //
+  // gradients: gradients backpropagated to the Relu op.
+  // features: inputs that where passed to the Relu op.
+  // backprops: gradients to backpropagate to the Relu inputs.
+  void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients,
+                  typename TTypes<T>::ConstTensor features,
+                  typename TTypes<T>::Tensor backprops) {
+    // NOTE: When the activation is exactly zero, we arbitrarily choose to not
+    // propagate the associated gradient value.
+    backprops.device(d) =
+        gradients * (features > features.constant(static_cast<T>(0)));
+  }
+};
+
+// Functor used by Relu6Op to do the computations.
+template <typename Device, typename T>
+struct Relu6 {
+  // Computes Relu6 activation.
+  //
+  // features: any shape.
+  // activations: same shape as "features".
+  void operator()(const Device& d, typename TTypes<T>::ConstTensor features,
+                  typename TTypes<T>::Tensor activations) {
+    activations.device(d) =
+        features.cwiseMax(static_cast<T>(0)).cwiseMin(static_cast<T>(6));
+  }
+};
+
+// Functor used by ReluGradOp to do the computations.
+template <typename Device, typename T>
+struct Relu6Grad {
+  // Computes Relu6Grad backprops.
+  //
+  // gradients: gradients backpropagated to the Relu6 op.
+  // features: inputs that where passed to the Relu6 op.
+  // backprops: gradients to backpropagate to the Relu6 inputs.
+  void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients,
+                  typename TTypes<T>::ConstTensor features,
+                  typename TTypes<T>::Tensor backprops) {
+    // NOTE: When the activation is exactly zero or six, we
+    // arbitrarily choose to not propagate the associated gradient
+    // value.
+    backprops.device(d) = gradients *
+                          (features > features.constant(static_cast<T>(0))) *
+                          (features < features.constant(static_cast<T>(6)));
+  }
+};
+
+}  // namespace functor
+}  // namespace tensorflow
+
+#endif  // TENSORFLOW_KERNELS_RELU_OP_H_