TensorFlow: more features, performance improvements, and doc fixes.

Changes:
- Add Split/Concat() methods to TensorUtil (meant for convenience, not
  speed) by Chris.

- Changes to linear algebra ops interface by Rasmus

- Tests for tensorboard by Daniel

- Fix bug in histogram calculation by Cassandra

- Added tool for backwards compatibility of OpDefs.  Tool
  Checks in history of opdefs and their changes, checks for
  backwards-incompatible changes.  All done by @josh11b

- Fix some protobuf example proto docs by Oliver

- Add derivative of MatrixDeterminant by @yaroslavvb

- Add a priority queue queue by @ebrevdo

- Doc and typo fixes by Aurelien and @dave-andersen

- Speed improvements to ConvBackwardFilter by @andydavis

- Improve speed of Alexnet on TitanX by @zheng-xq

- Add some host memory annotations to some GPU kernels by Yuan.

- Add support for doubles in histogram summary by @jmchen-g

Base CL: 108158338

2 files changed, 24 insertions, 24 deletions

diff --git a/tensorflow/core/example/example.proto b/tensorflow/core/example/example.proto
index 194d1e7c24..4acd8ccd72 100644
--- a/tensorflow/core/example/example.proto
+++ b/tensorflow/core/example/example.proto
@@ -11,29 +11,29 @@ package tensorflow;
 //   features {
 //     feature {
 //       key: "age"
-//       float_list {
+//       value { float_list {
 //         value: 29.0
-//       }
+//       }}
 //     }
 //     feature {
 //       key: "movie"
-//       bytes_list {
+//       value { bytes_list {
 //         value: "The Shawshank Redemption"
 //         value: "Fight Club"
-//       }
+//       }}
 //     }
 //     feature {
 //       key: "movie_ratings"
-//       float_list {
+//       value { float_list {
 //         value: 9.0
 //         value: 9.7
-//       }
+//       }}
 //     }
 //     feature {
 //       key: "suggestion"
-//       bytes_list {
+//       value { bytes_list {
 //         value: "Inception"
-//       }
+//       }}
 //     }
 //     # Note that this feature exists to be used as a label in training.
 //     # E.g., if training a logistic regression model to predict purchase
@@ -41,9 +41,9 @@ package tensorflow;
 //     # "suggestion_purchased".
 //     feature {
 //       key: "suggestion_purchased"
-//       float_list {
+//       value { float_list {
 //         value: 1.0
-//       }
+//       }}
 //     }
 //     # Similar to "suggestion_purchased" above this feature exists to be used
 //     # as a label in training.
@@ -52,9 +52,9 @@ package tensorflow;
 //     # "purchase_price".
 //     feature {
 //       key: "purchase_price"
-//       float_list {
+//       value { float_list {
 //         value: 9.99
-//       }
+//       }}
 //     }
 //  }
 //
diff --git a/tensorflow/core/example/feature.proto b/tensorflow/core/example/feature.proto
index 5a3a9dd4bf..69f1923360 100644
--- a/tensorflow/core/example/feature.proto
+++ b/tensorflow/core/example/feature.proto
@@ -14,41 +14,41 @@
 // Example Features for a movie recommendation application:
 //   feature {
 //     key: "age"
-//     float_list {
+//     value { float_list {
 //       value: 29.0
-//     }
+//     }}
 //   }
 //   feature {
 //     key: "movie"
-//     bytes_list {
+//     value { bytes_list {
 //       value: "The Shawshank Redemption"
 //       value: "Fight Club"
-//     }
+//     }}
 //   }
 //   feature {
 //     key: "movie_ratings"
-//     float_list {
+//     value { float_list {
 //       value: 9.0
 //       value: 9.7
-//     }
+//     }}
 //   }
 //   feature {
 //     key: "suggestion"
-//     bytes_list {
+//     value { bytes_list {
 //       value: "Inception"
-//     }
+//     }}
 //   }
 //   feature {
 //     key: "suggestion_purchased"
-//     int64_list {
+//     value { int64_list {
 //       value: 1
-//     }
+//     }}
 //   }
 //   feature {
 //     key: "purchase_price"
-//     float_list {
+//     value { float_list {
 //       value: 9.99
-//     }
+//     }}
 //   }
 
 syntax = "proto3";