1 files changed, 69 insertions, 0 deletions
diff --git a/tensorflow/core/kernels/l2loss_op.cc b/tensorflow/core/kernels/l2loss_op.cc
new file mode 100644
index 0000000000..6f83f01676
--- /dev/null
+++ b/tensorflow/core/kernels/l2loss_op.cc
@@ -0,0 +1,69 @@
+// See docs in ../ops/nn_ops.cc.
+
+#define EIGEN_USE_THREADS
+
+#include "tensorflow/core/framework/numeric_op.h"
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/framework/register_types.h"
+#include "tensorflow/core/kernels/l2loss_op.h"
+#include "tensorflow/core/public/tensor.h"
+#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
+
+namespace tensorflow {
+
+typedef Eigen::ThreadPoolDevice CPUDevice;
+typedef Eigen::GpuDevice GPUDevice;
+
+template <typename Device, typename T>
+class L2LossOp : public OpKernel {
+ public:
+  explicit L2LossOp(OpKernelConstruction* context) : OpKernel(context) {}
+
+  void Compute(OpKernelContext* context) override {
+    // The input tensor can be of any number of dimensions, even though it's
+    // 2D in most typical applications.
+    const Tensor& input = context->input(0);
+    // The output is a single number.
+    Tensor* output = nullptr;
+    OP_REQUIRES_OK(context,
+                   context->allocate_output(0, TensorShape({}), &output));
+    functor::L2Loss<Device, T>()(context->eigen_device<Device>(),
+                                 input.flat<T>(), output->scalar<T>());
+  }
+};
+
+#define REGISTER_KERNEL(T)                                      \
+  REGISTER_KERNEL_BUILDER(                                      \
+      Name("L2Loss").Device(DEVICE_CPU).TypeConstraint<T>("T"), \
+      L2LossOp<CPUDevice, T>);
+
+REGISTER_KERNEL(float);
+REGISTER_KERNEL(double);
+#undef REGISTER_KERNEL
+
+#if GOOGLE_CUDA
+// Forward declarations of the functor specializations for GPU.
+namespace functor {
+#define DECLARE_GPU_SPEC(T)                                                    \
+  template <>                                                                  \
+  void L2Loss<GPUDevice, T>::operator()(const GPUDevice& d,                    \
+                                        typename TTypes<T>::ConstTensor input, \
+                                        typename TTypes<T>::Scalar output);    \
+  extern template struct L2Loss<GPUDevice, T>;
+
+DECLARE_GPU_SPEC(float);
+#undef DECLARE_GPU_SPEC
+}  // namespace functor
+
+// Registration of the GPU implementations.
+#define REGISTER_GPU_KERNEL(T)                                  \
+  REGISTER_KERNEL_BUILDER(                                      \
+      Name("L2Loss").Device(DEVICE_GPU).TypeConstraint<T>("T"), \
+      L2LossOp<GPUDevice, T>);
+
+REGISTER_GPU_KERNEL(float);
+#undef REGISTER_GPU_KERNEL
+
+#endif  // GOOGLE_CUDA
+
+}  // namespace tensorflow