Fix several integer conversion and sign-compare warnings

4 files changed, 52 insertions, 53 deletions

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h
index 24a6343e8..aa500eb70 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h
@@ -212,11 +212,11 @@ class TensorBlockIO {
         num_size_one_inner_dims, NumDims - num_size_one_inner_dims - 1);
     const StorageIndex block_dim_for_tensor_stride1_dim =
         NumDims == 0 ? 1 : tensor_to_block_dim_map[tensor_stride1_dim];
-    size_t block_inner_dim_size =
+    StorageIndex block_inner_dim_size =
         NumDims == 0 ? 1
                      : block.block_sizes()[block_dim_for_tensor_stride1_dim];
-    for (int i = num_size_one_inner_dims + 1; i < NumDims; ++i) {
-      const int dim = cond<Layout>()(i, NumDims - i - 1);
+    for (Index i = num_size_one_inner_dims + 1; i < NumDims; ++i) {
+      const Index dim = cond<Layout>()(i, NumDims - i - 1);
       const StorageIndex block_stride =
           block.block_strides()[tensor_to_block_dim_map[dim]];
       if (block_inner_dim_size == block_stride &&
@@ -258,8 +258,8 @@ class TensorBlockIO {
 
     // Initialize block iterator state. Squeeze away any dimension of size 1.
     int num_squeezed_dims = 0;
-    for (int i = num_size_one_inner_dims; i < NumDims - 1; ++i) {
-      const int dim = cond<Layout>()(i + 1, NumDims - i - 2);
+    for (Index i = num_size_one_inner_dims; i < NumDims - 1; ++i) {
+      const Index dim = cond<Layout>()(i + 1, NumDims - i - 2);
       const StorageIndex size = block.block_sizes()[tensor_to_block_dim_map[dim]];
       if (size == 1) {
         continue;
@@ -626,7 +626,7 @@ class TensorBlockMapper {
                     const TensorBlockShapeType block_shape,
                     Index min_target_size)
       : m_dimensions(dims),
-        m_block_dim_sizes(BlockDimensions(dims, block_shape, min_target_size)) {
+        m_block_dim_sizes(BlockDimensions(dims, block_shape, internal::convert_index<StorageIndex>(min_target_size))) {
     // Calculate block counts by dimension and total block count.
     DSizes<StorageIndex, NumDims> block_count;
     for (Index i = 0; i < block_count.rank(); ++i) {
@@ -717,8 +717,8 @@ class TensorBlockMapper {
  private:
   static Dimensions BlockDimensions(const Dimensions& tensor_dims,
                                     const TensorBlockShapeType block_shape,
-                                    Index min_target_size) {
-    min_target_size = numext::maxi<Index>(1, min_target_size);
+                                    StorageIndex min_target_size) {
+    min_target_size = numext::maxi<StorageIndex>(1, min_target_size);
 
     // If tensor fully fits into the target size, we'll treat it a single block.
     Dimensions block_dim_sizes = tensor_dims;
@@ -735,16 +735,15 @@ class TensorBlockMapper {
       if (block_shape == kUniformAllDims) {
         // Tensor will not fit within 'min_target_size' budget: calculate tensor
         // block dimension sizes based on "square" dimension size target.
-        const size_t dim_size_target = static_cast<const size_t>(
+        const StorageIndex dim_size_target = internal::convert_index<StorageIndex>(
             std::pow(static_cast<float>(min_target_size),
                      1.0f / static_cast<float>(block_dim_sizes.rank())));
-        for (size_t i = 0; i < block_dim_sizes.rank(); ++i) {
+        for (Index i = 0; i < block_dim_sizes.rank(); ++i) {
           // TODO(andydavis) Adjust the inner most 'block_dim_size' to make it
           // a multiple of the packet size. Note that reducing
           // 'block_dim_size' in this manner can increase the number of
           // blocks, and so will amplify any per-block overhead.
-          block_dim_sizes[i] = numext::mini(
-              dim_size_target, static_cast<size_t>(tensor_dims[i]));
+          block_dim_sizes[i] = numext::mini(dim_size_target, tensor_dims[i]);
         }
         // Add any un-allocated coefficients to inner dimension(s).
         StorageIndex total_size = block_dim_sizes.TotalSize();
@@ -781,7 +780,7 @@ class TensorBlockMapper {
 
     eigen_assert(
         block_dim_sizes.TotalSize() >=
-        numext::mini<size_t>(min_target_size, tensor_dims.TotalSize()));
+        numext::mini<Index>(min_target_size, tensor_dims.TotalSize()));
 
     return block_dim_sizes;
   }
@@ -824,7 +823,7 @@ class TensorSliceBlockMapper {
         m_total_block_count(1) {
     // Calculate block counts by dimension and total block count.
     DSizes<StorageIndex, NumDims> block_count;
-    for (size_t i = 0; i < block_count.rank(); ++i) {
+    for (Index i = 0; i < block_count.rank(); ++i) {
       block_count[i] = divup(m_tensor_slice_extents[i], m_block_dim_sizes[i]);
     }
     m_total_block_count = array_prod(block_count);
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h b/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
index 4f973a5b7..ce91bc2a6 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
@@ -32,12 +32,12 @@ namespace Eigen {
 // Boilerplate code
 namespace internal {
 
-template<std::size_t n, typename Dimension> struct dget {
+template<std::ptrdiff_t n, typename Dimension> struct dget {
   static const std::ptrdiff_t value = get<n, Dimension>::value;
 };
 
 
-template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor>
+template<typename Index, std::ptrdiff_t NumIndices, std::ptrdiff_t n, bool RowMajor>
 struct fixed_size_tensor_index_linearization_helper
 {
   template <typename Dimensions> EIGEN_DEVICE_FUNC
@@ -50,7 +50,7 @@ struct fixed_size_tensor_index_linearization_helper
   }
 };
 
-template<typename Index, std::size_t NumIndices, bool RowMajor>
+template<typename Index, std::ptrdiff_t NumIndices, bool RowMajor>
 struct fixed_size_tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor>
 {
   template <typename Dimensions> EIGEN_DEVICE_FUNC
@@ -60,7 +60,7 @@ struct fixed_size_tensor_index_linearization_helper<Index, NumIndices, 0, RowMaj
   }
 };
 
-template<typename Index, std::size_t n>
+template<typename Index, std::ptrdiff_t n>
 struct fixed_size_tensor_index_extraction_helper
 {
   template <typename Dimensions> EIGEN_DEVICE_FUNC
@@ -94,7 +94,7 @@ struct Sizes {
   typedef internal::numeric_list<std::ptrdiff_t, Indices...> Base;
   const Base t = Base();
   static const std::ptrdiff_t total_size = internal::arg_prod(Indices...);
-  static const size_t count = Base::count;
+  static const ptrdiff_t count = Base::count;
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t rank() const {
     return Base::count;
@@ -121,16 +121,16 @@ struct Sizes {
     return *this;
   }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t operator[] (const std::size_t index) const {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t operator[] (const std::ptrdiff_t index) const {
     return internal::fixed_size_tensor_index_extraction_helper<std::ptrdiff_t, Base::count>::run(index, t);
   }
 
   template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-  size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
+  ptrdiff_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
     return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, false>::run(indices, t);
   }
   template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-  size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
+  ptrdiff_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
     return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, t);
   }
 };
@@ -144,25 +144,25 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_prod(const Sizes<Indi
 
 #else
 
-template <std::size_t n>
+template <std::ptrdiff_t n>
 struct non_zero_size {
-  typedef internal::type2val<std::size_t, n> type;
+  typedef internal::type2val<std::ptrdiff_t, n> type;
 };
 template <>
 struct non_zero_size<0> {
   typedef internal::null_type type;
 };
 
-template <std::size_t V1=0, std::size_t V2=0, std::size_t V3=0, std::size_t V4=0, std::size_t V5=0> struct Sizes {
+template <std::ptrdiff_t V1=0, std::ptrdiff_t V2=0, std::ptrdiff_t V3=0, std::ptrdiff_t V4=0, std::ptrdiff_t V5=0> struct Sizes {
   typedef typename internal::make_type_list<typename non_zero_size<V1>::type, typename non_zero_size<V2>::type, typename non_zero_size<V3>::type, typename non_zero_size<V4>::type, typename non_zero_size<V5>::type >::type Base;
-  static const size_t count = Base::count;
-  static const std::size_t total_size = internal::arg_prod<Base>::value;
+  static const std::ptrdiff_t count = Base::count;
+  static const std::ptrdiff_t total_size = internal::arg_prod<Base>::value;
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t rank() const {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ptrdiff_t rank() const {
     return count;
   }
 
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t TotalSize() {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ptrdiff_t TotalSize() {
     return internal::arg_prod<Base>::value;
   }
 
@@ -178,7 +178,7 @@ template <std::size_t V1=0, std::size_t V2=0, std::size_t V3=0, std::size_t V4=0
 
 #if EIGEN_HAS_VARIADIC_TEMPLATES
   template <typename... DenseIndex> Sizes(DenseIndex... /*indices*/) { }
-  explicit Sizes(std::initializer_list<std::size_t>) {
+  explicit Sizes(std::initializer_list<std::ptrdiff_t>) {
     // todo: add assertion
   }
 #else
@@ -213,18 +213,18 @@ template <std::size_t V1=0, std::size_t V2=0, std::size_t V3=0, std::size_t V4=0
   }
 
   template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-  size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
+  ptrdiff_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
     return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, false>::run(indices, *reinterpret_cast<const Base*>(this));
   }
   template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-  size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
+  ptrdiff_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
     return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *reinterpret_cast<const Base*>(this));
   }
 };
 
 namespace internal {
-template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t array_prod(const Sizes<V1, V2, V3, V4, V5>&) {
+template <std::ptrdiff_t V1, std::ptrdiff_t V2, std::ptrdiff_t V3, std::ptrdiff_t V4, std::ptrdiff_t V5>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_prod(const Sizes<V1, V2, V3, V4, V5>&) {
   return Sizes<V1, V2, V3, V4, V5>::total_size;
 }
 }
@@ -233,7 +233,7 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t array_prod(const Sizes<V1, V2,
 
 // Boilerplate
 namespace internal {
-template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor>
+template<typename Index, std::ptrdiff_t NumIndices, std::ptrdiff_t n, bool RowMajor>
 struct tensor_index_linearization_helper
 {
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -245,7 +245,7 @@ struct tensor_index_linearization_helper
   }
 };
 
-template<typename Index, std::size_t NumIndices, bool RowMajor>
+template<typename Index, std::ptrdiff_t NumIndices, bool RowMajor>
 struct tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor>
 {
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -264,7 +264,7 @@ struct DSizes : array<DenseIndex, NumDims> {
   typedef array<DenseIndex, NumDims> Base;
   static const int count = NumDims;
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t rank() const {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rank() const {
     return NumDims;
   }
 
@@ -298,7 +298,7 @@ struct DSizes : array<DenseIndex, NumDims> {
     }
   }
 #else
-  template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5>
+  template <std::ptrdiff_t V1, std::ptrdiff_t V2, std::ptrdiff_t V3, std::ptrdiff_t V4, std::ptrdiff_t V5>
   EIGEN_DEVICE_FUNC DSizes(const Sizes<V1, V2, V3, V4, V5>& a) {
     for (int i = 0 ; i < NumDims; ++i) {
       (*this)[i] = a[i];
@@ -359,7 +359,7 @@ struct DSizes : array<DenseIndex, NumDims> {
 
 // Boilerplate
 namespace internal {
-template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor>
+template<typename Index, std::ptrdiff_t NumIndices, std::ptrdiff_t n, bool RowMajor>
 struct tensor_vsize_index_linearization_helper
 {
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -371,7 +371,7 @@ struct tensor_vsize_index_linearization_helper
   }
 };
 
-template<typename Index, std::size_t NumIndices, bool RowMajor>
+template<typename Index, std::ptrdiff_t NumIndices, bool RowMajor>
 struct tensor_vsize_index_linearization_helper<Index, NumIndices, 0, RowMajor>
 {
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -386,10 +386,10 @@ struct tensor_vsize_index_linearization_helper<Index, NumIndices, 0, RowMajor>
 namespace internal {
 
 template <typename DenseIndex, int NumDims> struct array_size<const DSizes<DenseIndex, NumDims> > {
-  static const size_t value = NumDims;
+  static const ptrdiff_t value = NumDims;
 };
 template <typename DenseIndex, int NumDims> struct array_size<DSizes<DenseIndex, NumDims> > {
-  static const size_t value = NumDims;
+  static const ptrdiff_t value = NumDims;
 };
 #ifndef EIGEN_EMULATE_CXX11_META_H
 template <typename std::ptrdiff_t... Indices> struct array_size<const Sizes<Indices...> > {
@@ -399,33 +399,33 @@ template <typename std::ptrdiff_t... Indices> struct array_size<Sizes<Indices...
 static const std::ptrdiff_t value = Sizes<Indices...>::count;
 };
 template <std::ptrdiff_t n, typename std::ptrdiff_t... Indices> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_get(const Sizes<Indices...>&) {
-  return get<n, internal::numeric_list<std::size_t, Indices...> >::value;
+  return get<n, internal::numeric_list<std::ptrdiff_t, Indices...> >::value;
 }
 template <std::ptrdiff_t n> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_get(const Sizes<>&) {
   eigen_assert(false && "should never be called");
   return -1;
 }
 #else
-template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> struct array_size<const Sizes<V1,V2,V3,V4,V5> > {
-  static const size_t value = Sizes<V1,V2,V3,V4,V5>::count;
+template <std::ptrdiff_t V1, std::ptrdiff_t V2, std::ptrdiff_t V3, std::ptrdiff_t V4, std::ptrdiff_t V5> struct array_size<const Sizes<V1,V2,V3,V4,V5> > {
+  static const ptrdiff_t value = Sizes<V1,V2,V3,V4,V5>::count;
 };
-template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> struct array_size<Sizes<V1,V2,V3,V4,V5> > {
-  static const size_t value = Sizes<V1,V2,V3,V4,V5>::count;
+template <std::ptrdiff_t V1, std::ptrdiff_t V2, std::ptrdiff_t V3, std::ptrdiff_t V4, std::ptrdiff_t V5> struct array_size<Sizes<V1,V2,V3,V4,V5> > {
+  static const ptrdiff_t value = Sizes<V1,V2,V3,V4,V5>::count;
 };
-template <std::size_t n, std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t array_get(const Sizes<V1,V2,V3,V4,V5>&) {
+template <std::ptrdiff_t n, std::ptrdiff_t V1, std::ptrdiff_t V2, std::ptrdiff_t V3, std::ptrdiff_t V4, std::ptrdiff_t V5> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_get(const Sizes<V1,V2,V3,V4,V5>&) {
   return get<n, typename Sizes<V1,V2,V3,V4,V5>::Base>::value;
 }
 
 #endif
 
 
-template <typename Dims1, typename Dims2, size_t n, size_t m>
+template <typename Dims1, typename Dims2, ptrdiff_t n, ptrdiff_t m>
 struct sizes_match_below_dim {
   static EIGEN_DEVICE_FUNC  EIGEN_STRONG_INLINE bool run(Dims1&, Dims2&) {
     return false;
   }
 };
-template <typename Dims1, typename Dims2, size_t n>
+template <typename Dims1, typename Dims2, ptrdiff_t n>
 struct sizes_match_below_dim<Dims1, Dims2, n, n> {
   static EIGEN_DEVICE_FUNC  EIGEN_STRONG_INLINE bool run(Dims1& dims1, Dims2& dims2) {
     return (array_get<n-1>(dims1) == array_get<n-1>(dims2)) &
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h b/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
index 9b9587de5..b756be3b3 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
@@ -256,8 +256,8 @@ class TensorExecutor<Expression, ThreadPoolDevice, Vectorizable, /*Tileable*/ tr
     typedef TensorBlockMapper<ScalarNoConst, StorageIndex, NumDims, Evaluator::Layout> TensorBlockMapper;
 
     Evaluator evaluator(expr, device);
-    StorageIndex total_size = array_prod(evaluator.dimensions());
-    StorageIndex cache_size = device.firstLevelCacheSize() / sizeof(Scalar);
+    Index total_size = array_prod(evaluator.dimensions());
+    Index cache_size = device.firstLevelCacheSize() / sizeof(Scalar);
     if (total_size < cache_size) {
       // TODO(andydavis) Reduce block management overhead for small tensors.
       internal::TensorExecutor<Expression, ThreadPoolDevice, Vectorizable,
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h b/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
index 98ad661ca..3f7d26b18 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
@@ -84,7 +84,7 @@ template<DenseIndex n> struct NumTraits<type2index<n> >
 namespace internal {
 template <typename T>
 EIGEN_DEVICE_FUNC void update_value(T& val, DenseIndex new_val) {
-  val = new_val;
+  val = internal::convert_index<T>(new_val);
 }
 template <DenseIndex n>
 EIGEN_DEVICE_FUNC void update_value(type2index<n>& val, DenseIndex new_val) {