Remove HashStr and HashStringPiece (a one-off).

Now that we have tensorflow::hash and it's the default hasher for
FlatMap and FlatSet, we can get rid of HashStr and HashStringPiece.

PiperOrigin-RevId: 161560034

5 files changed, 18 insertions, 15 deletions

diff --git a/tensorflow/core/common_runtime/executor.cc b/tensorflow/core/common_runtime/executor.cc
index ce6bbb0d65..e8a5b67546 100644
--- a/tensorflow/core/common_runtime/executor.cc
+++ b/tensorflow/core/common_runtime/executor.cc
@@ -363,7 +363,7 @@ class ExecutorImpl : public Executor {
   friend class ExecutorState;
 
   struct ControlFlowInfo {
-    gtl::FlatSet<string, HashStr> unique_frame_names;
+    gtl::FlatSet<string> unique_frame_names;
     std::vector<string> frame_names;
   };
 
@@ -423,7 +423,7 @@ class ExecutorImpl : public Executor {
   // Mapping from frame name to static information about the frame.
   // TODO(yuanbyu): We could cache it along with the graph so to avoid
   // the overhead of constructing it for each executor instance.
-  gtl::FlatMap<string, FrameInfo*, HashStr> frame_info_;
+  gtl::FlatMap<string, FrameInfo*> frame_info_;
 
   TF_DISALLOW_COPY_AND_ASSIGN(ExecutorImpl);
 };
@@ -1209,8 +1209,7 @@ class ExecutorState {
   // child frame is composed of the name of the parent frame, the iteration
   // number at which the parent frame is creating the new frame, and the
   // name of the new frame from nodedef.
-  gtl::FlatMap<string, FrameState*, HashStr> outstanding_frames_
-      GUARDED_BY(mu_);
+  gtl::FlatMap<string, FrameState*> outstanding_frames_ GUARDED_BY(mu_);
 
   // The unique name of a frame.
   inline string MakeFrameName(FrameState* frame, int64 iter_id,
diff --git a/tensorflow/core/framework/function.h b/tensorflow/core/framework/function.h
index 2342e08b38..059f2be629 100644
--- a/tensorflow/core/framework/function.h
+++ b/tensorflow/core/framework/function.h
@@ -354,9 +354,9 @@ class FunctionLibraryDefinition : public OpRegistryInterface {
   };
 
   const OpRegistryInterface* const default_registry_;
-  gtl::FlatMap<string, std::unique_ptr<FunctionDefAndOpRegistration>, HashStr>
+  gtl::FlatMap<string, std::unique_ptr<FunctionDefAndOpRegistration>>
       function_defs_;
-  gtl::FlatMap<string, string, HashStr> func_grad_;
+  gtl::FlatMap<string, string> func_grad_;
 
   // Helper function for GetAttr. Returns the FunctionDef* to get the
   // attr from.
diff --git a/tensorflow/core/lib/gtl/flatmap_test.cc b/tensorflow/core/lib/gtl/flatmap_test.cc
index d8e50830e6..bb65e5357a 100644
--- a/tensorflow/core/lib/gtl/flatmap_test.cc
+++ b/tensorflow/core/lib/gtl/flatmap_test.cc
@@ -588,7 +588,7 @@ TEST(FlatMap, ForwardIterator) {
 // or destructions will show up as errors under a sanitizer or
 // heap checker.
 TEST(FlatMap, ConstructDestruct) {
-  FlatMap<string, string, HashStr> map;
+  FlatMap<string, string> map;
   string k1 = "the quick brown fox jumped over the lazy dog";
   string k2 = k1 + k1;
   string k3 = k1 + k2;
diff --git a/tensorflow/core/lib/gtl/flatset_test.cc b/tensorflow/core/lib/gtl/flatset_test.cc
index 54def603c3..09fbbb1fb6 100644
--- a/tensorflow/core/lib/gtl/flatset_test.cc
+++ b/tensorflow/core/lib/gtl/flatset_test.cc
@@ -485,7 +485,7 @@ TEST(FlatSet, ForwardIterator) {
 // or destructions will show up as errors under a sanitizer or
 // heap checker.
 TEST(FlatSet, ConstructDestruct) {
-  FlatSet<string, HashStr> set;
+  FlatSet<string> set;
   string k1 = "the quick brown fox jumped over the lazy dog";
   string k2 = k1 + k1;
   string k3 = k1 + k2;
diff --git a/tensorflow/core/lib/hash/hash.h b/tensorflow/core/lib/hash/hash.h
index b45391fac5..73b7c94d1f 100644
--- a/tensorflow/core/lib/hash/hash.h
+++ b/tensorflow/core/lib/hash/hash.h
@@ -23,6 +23,7 @@ limitations under the License.
 
 #include <string>
 
+#include "tensorflow/core/lib/core/stringpiece.h"
 #include "tensorflow/core/platform/types.h"
 
 namespace tensorflow {
@@ -42,12 +43,6 @@ inline uint64 Hash64Combine(uint64 a, uint64 b) {
   return a ^ (b + 0x9e3779b97f4a7800ULL + (a << 10) + (a >> 4));
 }
 
-struct HashStr {
-  size_t operator()(const string& s) const {
-    return static_cast<size_t>(Hash64(s));
-  }
-};
-
 // Hash functor suitable for use with power-of-two sized hashtables.  Use
 // instead of std::hash<T>.
 //
@@ -70,7 +65,16 @@ struct hash<T*> {
 
 template <>
 struct hash<string> {
-  size_t operator()(const string& s) const { return HashStr()(s); }
+  size_t operator()(const string& s) const {
+    return static_cast<size_t>(Hash64(s));
+  }
+};
+
+template <>
+struct hash<StringPiece> {
+  size_t operator()(StringPiece sp) const {
+    return static_cast<size_t>(Hash64(sp.data(), sp.size()));
+  }
 };
 
 }  // namespace tensorflow