Added support for mean reductions on fp16

unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h b/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
index 7368768..f9ce243 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
@@ -230,13 +230,15 @@
 #endif
 
 
-template <typename Self, typename Op>
+template <typename Self, typename Op, typename OutputType, bool PacketAccess>
 struct FullReductionLauncher {
-  template <typename OutputType>
   static void run(const Self&, Op&, const GpuDevice&, OutputType*, typename Self::Index) {
     assert(false && "Should only be called on floats and half floats");
   }
+};
 
+template <typename Self, typename Op, bool PacketAccess>
+struct FullReductionLauncher<Self, Op, float, PacketAccess> {
   static void run(const Self& self, Op& reducer, const GpuDevice& device, float* output, typename Self::Index num_coeffs) {
     typedef typename Self::Index Index;
     typedef typename Self::CoeffReturnType Scalar;
@@ -254,8 +256,18 @@
     LAUNCH_CUDA_KERNEL((FullReductionKernel<block_size, num_per_thread, Self, Op, Index>),
                        num_blocks, block_size, 0, device, reducer, self, num_coeffs, output);
   }
+};
 
 #ifdef EIGEN_HAS_CUDA_FP16
+template <typename Self, typename Op>
+struct FullReductionLauncher<Self, Op, Eigen::half, false> {
+  static void run(const Self&, Op&, const GpuDevice&, half*, typename Self::Index) {
+    assert(false && "Should not be called since there is no packet accessor");
+  }
+};
+
+template <typename Self, typename Op>
+struct FullReductionLauncher<Self, Op, Eigen::half, true> {
   static void run(const Self& self, Op& reducer, const GpuDevice& device, half* output, typename Self::Index num_coeffs) {
     typedef typename Self::Index Index;
 
@@ -279,8 +291,8 @@
                          1, 1, 0, device, reducer, output, scratch);
     }
   }
-#endif
 };
+#endif
 
 
 template <typename Self, typename Op, bool Vectorizable>
@@ -306,7 +318,7 @@
       return;
     }
 
-    FullReductionLauncher<Self, Op>::run(self, reducer, device, output, num_coeffs);
+    FullReductionLauncher<Self, Op, OutputType, Op::PacketAccess>::run(self, reducer, device, output, num_coeffs);
   }
 };
 
@@ -473,14 +485,16 @@
 
 #endif
 
-template <typename Self, typename Op>
+template <typename Self, typename Op, typename OutputType, bool PacketAccess>
 struct InnerReductionLauncher {
-  template <typename OutputType>
   static EIGEN_DEVICE_FUNC bool run(const Self&, Op&, const GpuDevice&, OutputType*, typename Self::Index, typename Self::Index) {
     assert(false && "Should only be called to reduce floats and half floats on a gpu device");
     return true;
   }
+};
 
+template <typename Self, typename Op, bool PacketAccess>
+struct InnerReductionLauncher<Self, Op, float, PacketAccess> {
   static bool run(const Self& self, Op& reducer, const GpuDevice& device, float* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
     typedef typename Self::Index Index;
 
@@ -509,8 +523,18 @@
 
     return false;
   }
+};
 
 #ifdef EIGEN_HAS_CUDA_FP16
+template <typename Self, typename Op>
+struct InnerReductionLauncher<Self, Op, Eigen::half, false> {
+  static bool run(const Self&, Op&, const GpuDevice&, half*, typename Self::Index, typename Self::Index) {
+    assert(false && "Should not be called since there is no packet accessor");
+  }
+};
+
+template <typename Self, typename Op>
+struct InnerReductionLauncher<Self, Op, Eigen::half, true> {
   static bool run(const Self& self, Op& reducer, const GpuDevice& device, half* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
     typedef typename Self::Index Index;
 
@@ -543,8 +567,8 @@
 
     return false;
   }
-#endif
 };
+#endif
 
 
 template <typename Self, typename Op>
@@ -574,7 +598,7 @@
       return true;
     }
 
-    return InnerReductionLauncher<Self, Op>::run(self, reducer, device, output, num_coeffs_to_reduce, num_preserved_vals);
+    return InnerReductionLauncher<Self, Op, OutputType, Op::PacketAccess>::run(self, reducer, device, output, num_coeffs_to_reduce, num_preserved_vals);
   }
 };