make GPU headers C++03 compatible

INSTALL

@@ -177,7 +177,9 @@ requires:
 
 See the example makefile on how to set the flags.
 
-The nvcc-specific flags to pass to the compiler:
+The nvcc-specific flags to pass to the compiler, based on your desired
+compute capability. Only compute capability 3.5+ is supported. For
+example:
 
    -gencode arch=compute_35,code="compute_35"
    -gencode arch=compute_52,code="compute_52"
@@ -261,4 +263,3 @@ to be visible in the PYTHONPATH or in the current directory.
 Then Faiss can be used in python with
 
   import faiss
-

docs/Doxyfile

 
+
 # Doxyfile 1.8.5
 
 # This file describes the settings to be used by the documentation system
@@ -131,7 +132,7 @@ INLINE_INHERITED_MEMB  = NO
 # shortest path that makes the file name unique will be used
 # The default value is: YES.
 
-FULL_PATH_NAMES        = NO
+FULL_PATH_NAMES        = YES
 
 # The STRIP_FROM_PATH tag can be used to strip a user-defined part of the path.
 # Stripping is only done if one of the specified strings matches the left-hand

gpu/IndexProxy.h

@@ -80,7 +80,7 @@ class IndexProxy : public faiss::Index {
  private:
   /// Collection of Index instances, with their managing worker thread
   mutable std::vector<std::pair<faiss::Index*,
-                                std::unique_ptr<WorkerThread>>> indices_;
+                                std::unique_ptr<WorkerThread> > > indices_;
 };
 
 

gpu/StandardGpuResources.h

@@ -64,7 +64,7 @@ class StandardGpuResources : public GpuResources {
   std::unordered_map<int, cudaStream_t> defaultStreams_;
 
   /// Other streams we can use, per each device
-  std::unordered_map<int, std::vector<cudaStream_t>> alternateStreams_;
+  std::unordered_map<int, std::vector<cudaStream_t> > alternateStreams_;
 
   /// Async copy stream to use for GPU <-> CPU pinned memory copies
   std::unordered_map<int, cudaStream_t> asyncCopyStreams_;
@@ -73,7 +73,7 @@ class StandardGpuResources : public GpuResources {
   std::unordered_map<int, cublasHandle_t> blasHandles_;
 
   /// Temporary memory provider, per each device
-  std::unordered_map<int, std::unique_ptr<StackDeviceMemory>> memory_;
+  std::unordered_map<int, std::unique_ptr<StackDeviceMemory> > memory_;
 
   /// Pinned memory allocation for use with this GPU
   void* pinnedMemAlloc_;