From 0db590d22db198154f4302d85fbbd892316d36da Mon Sep 17 00:00:00 2001
From: Rasmus Munk Larsen <rmlarsen@google.com>
Date: Thu, 13 Sep 2018 16:20:57 -0700
Subject: [PATCH] Backed out changeset 01197e44527941c95f9a63e4f60ab3a989f12cbe

---
 unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h | 2 ++
 unsupported/test/cxx11_tensor_executor.cpp           | 8 ++++----
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h b/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
index 8d93aacee..e8c47c5b5 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
@@ -1205,6 +1205,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>,
       const Index max_coeff_count,
       const DSizes<Index, NumInputDims>& input_slice_sizes,
       DSizes<Index, NumInputDims>* target_input_block_sizes) const {
+    typedef typename internal::packet_traits<Scalar>::type Packet;
     typedef internal::BlockReducer<Self, Op> BlockReducer;
     // TODO(andydavis) Compute reducer overhead correctly for the case where
     // we are preserving the inner most dimension, and a single reducer
@@ -1232,6 +1233,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>,
       } else if (!first_preserved_dim_allocated) {
         // TODO(andydavis) Include output block size in this L1 working set
         // calculation.
+        const Index allocated = max_coeff_count - coeff_to_allocate;
         const Index alloc_size = numext::maxi(
             static_cast<Index>(1), coeff_to_allocate / reducer_overhead);
         (*target_input_block_sizes)[dim] =
diff --git a/unsupported/test/cxx11_tensor_executor.cpp b/unsupported/test/cxx11_tensor_executor.cpp
index 1bb99854c..8639e7b38 100644
--- a/unsupported/test/cxx11_tensor_executor.cpp
+++ b/unsupported/test/cxx11_tensor_executor.cpp
@@ -27,7 +27,7 @@ static array<Index, NumDims> RandomDims(int min_dim = 1, int max_dim = 20) {
     dims[i] = internal::random<int>(min_dim, max_dim);
   }
   return dims;
-}
+};
 
 template <typename T, int NumDims, typename Device, bool Vectorizable,
           bool Tileable, int Layout>
@@ -117,7 +117,7 @@ static void test_execute_broadcasting(Device d)
   for (Index i = 0; i < dst.dimensions().TotalSize(); ++i) {
     VERIFY_IS_EQUAL(dst.coeff(i), golden.coeff(i));
   }
-}
+};
 
 template <typename T, int NumDims, typename Device, bool Vectorizable,
           bool Tileable, int Layout>
@@ -155,7 +155,7 @@ static void test_execute_chipping_rvalue(Device d) {
   TEST_CHIPPING(5)
 
 #undef TEST_CHIPPING
-}
+};
 
 template <typename T, int NumDims, typename Device, bool Vectorizable,
     bool Tileable, int Layout>
@@ -207,7 +207,7 @@ static void test_execute_chipping_lvalue(Device d) {
   TEST_CHIPPING(5)
 
 #undef TEST_CHIPPING
-}
+};
 
 template <typename T, int NumDims, typename Device, bool Vectorizable,
           bool Tileable, int Layout>