Fixed a number of compilation warnings generated by the cuda tests

3 files changed, 42 insertions, 9 deletions

diff --git a/unsupported/Eigen/CXX11/src/Core/util/EmulateArray.h b/unsupported/Eigen/CXX11/src/Core/util/EmulateArray.h
index 456b34d0b..89aeb03e7 100644
--- a/unsupported/Eigen/CXX11/src/Core/util/EmulateArray.h
+++ b/unsupported/Eigen/CXX11/src/Core/util/EmulateArray.h
@@ -25,6 +25,16 @@ template <typename T, size_t n> class array {
   EIGEN_DEVICE_FUNC
   EIGEN_STRONG_INLINE const T& operator[] (size_t index) const { return values[index]; }
 
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& front() { return values[0]; }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& front() const { return values[0]; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& back() { return values[n-1]; }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& back() const { return values[n-1]; }
+
   EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
   static std::size_t size() { return n; }
 
@@ -123,13 +133,33 @@ template <typename T> class array<T, 0> {
   EIGEN_DEVICE_FUNC
   EIGEN_STRONG_INLINE T& operator[] (size_t) {
     eigen_assert(false && "Can't index a zero size array");
-    return *static_cast<T*>(NULL);
+    return dummy;
   }
-
   EIGEN_DEVICE_FUNC
   EIGEN_STRONG_INLINE const T& operator[] (size_t) const {
     eigen_assert(false && "Can't index a zero size array");
-    return *static_cast<const T*>(NULL);
+    return dummy;
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& front() {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& front() const {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& back() {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& back() const {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
   }
 
   static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::size_t size() { return 0; }
@@ -142,6 +172,9 @@ template <typename T> class array<T, 0> {
     eigen_assert(l.size() == 0);
   }
 #endif
+
+ private:
+  T dummy;
 };
 
 namespace internal {
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h b/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
index 367a152a0..67c797802 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
@@ -21,7 +21,7 @@ namespace Eigen {
   */
 namespace internal {
 
-template <typename Index, typename InputDims, size_t NumKernelDims, int Layout>
+template <typename Index, typename InputDims, int NumKernelDims, int Layout>
 class IndexMapper {
  public:
   IndexMapper(const InputDims& input_dims, const array<Index, NumKernelDims>& kernel_dims,
@@ -123,7 +123,7 @@ class IndexMapper {
       }
       inputIndex += p * m_inputStrides[NumKernelDims];
     } else {
-      int limit = 0;
+      std::ptrdiff_t limit = 0;
       if (NumKernelDims < NumDims) {
         limit = NumDims - NumKernelDims - 1;
       }
@@ -147,7 +147,7 @@ class IndexMapper {
       }
       outputIndex += p * m_outputStrides[NumKernelDims];
     } else {
-      int limit = 0;
+      std::ptrdiff_t limit = 0;
       if (NumKernelDims < NumDims) {
         limit = NumDims - NumKernelDims - 1;
       }
@@ -206,7 +206,7 @@ class IndexMapper {
   }
 
  private:
-  static const size_t NumDims = internal::array_size<InputDims>::value;
+  static const int NumDims = internal::array_size<InputDims>::value;
   array<Index, NumDims> m_inputStrides;
   array<Index, NumDims> m_outputStrides;
   array<Index, NumDims> m_cudaInputStrides;
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h b/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
index a03b52629..22aea5ea4 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
@@ -463,7 +463,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
 	  m_outputStrides[i] = m_outputStrides[i - 1] * m_dimensions[i - 1];
 	}
       } else {
-	m_outputStrides[NumOutputDims - 1] = 1;
+	m_outputStrides.back() = 1;
 	for (int i = NumOutputDims - 2; i >= 0; --i) {
 	  m_outputStrides[i] = m_outputStrides[i + 1] * m_dimensions[i + 1];
 	}
@@ -479,7 +479,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
 	  input_strides[i] = input_strides[i-1] * input_dims[i-1];
 	}
       } else {
-	input_strides[NumInputDims - 1] = 1;
+	input_strides.back() = 1;
 	for (int i = NumInputDims - 2; i >= 0; --i) {
 	  input_strides[i] = input_strides[i + 1] * input_dims[i + 1];
 	}