TensorFlow: Minor updates to docs, BUILD, GPU config / perf, etc.

Changes:
- Updates to op documentation and index by Josh

- More changes to BUILD files for python 3 support by @girving

- Fix to Eigen to use DenseIndex everywhere by @jiayq

- Enable configuration for cuda compute capability by @zheng-xq,
  including updates to docs.

- Route aggregation method through optimizer by schuster

- Updates to install instructions for bazel 0.1.1.

Base CL: 107702099

1 files changed, 7 insertions, 6 deletions

diff --git a/tensorflow/core/kernels/tile_ops.h b/tensorflow/core/kernels/tile_ops.h
index 41c2deb42d..1a614fe4f1 100644
--- a/tensorflow/core/kernels/tile_ops.h
+++ b/tensorflow/core/kernels/tile_ops.h
@@ -31,8 +31,8 @@ template <typename Device, typename T, int NDIM>
 struct TileGrad {
   void operator()(const Device& d, typename TTypes<T, NDIM>::Tensor out,
                   typename TTypes<T, NDIM>::ConstTensor in,
-                  const Eigen::DSizes<ptrdiff_t, NDIM>& indices,
-                  const Eigen::DSizes<ptrdiff_t, NDIM>& sizes,
+                  const Eigen::DSizes<Eigen::DenseIndex, NDIM>& indices,
+                  const Eigen::DSizes<Eigen::DenseIndex, NDIM>& sizes,
                   bool first) const {
     if (first) {
       out.device(d) = in.slice(indices, sizes);
@@ -58,10 +58,11 @@ struct TileGrad<Device, T, 0> {
 
 template <typename Device, typename T, int NDIM, int REDUCEDNDIM>
 struct ReduceAndReshape {
-  void operator()(const Device& d, typename TTypes<T, NDIM>::Tensor out,
-                  typename TTypes<T, NDIM>::ConstTensor in,
-                  const Eigen::DSizes<ptrdiff_t, REDUCEDNDIM>& reduce_dim,
-                  const Eigen::DSizes<ptrdiff_t, NDIM>& reshape_dim) const {
+  void operator()(
+      const Device& d, typename TTypes<T, NDIM>::Tensor out,
+      typename TTypes<T, NDIM>::ConstTensor in,
+      const Eigen::DSizes<Eigen::DenseIndex, REDUCEDNDIM>& reduce_dim,
+      const Eigen::DSizes<Eigen::DenseIndex, NDIM>& reshape_dim) const {
     out.device(d) = in.sum(reduce_dim).reshape(reshape_dim);
   }
 };