Merge pull request flann-lib#1 from BaltashovIlia/master

CUDA, testing, and other fixes

cmake/flann_utils.cmake

@@ -100,18 +100,4 @@ macro(flann_add_pyunit file)
     # add dependency to 'test' target
     add_dependencies(pyunit_${_testname} flann)
     add_dependencies(test pyunit_${_testname})
-endmacro(flann_add_pyunit)
-
-
-
-macro(flann_download_test_data _name _md5)
-    string(REPLACE "/" "_" _dataset_name dataset_${_name})
-
-    add_custom_target(${_dataset_name}
-        COMMAND ${PYTHON_EXECUTABLE} ${PROJECT_SOURCE_DIR}/bin/download_checkmd5.py https://www.cs.ubc.ca/research/flann/uploads/FLANN/datasets/${_name} ${TEST_OUTPUT_PATH}/${_name} ${_md5}
-        VERBATIM)
-
-    # Also make sure that downloads are done before we run any tests
-    add_dependencies(tests ${_dataset_name})
-
-endmacro(flann_download_test_data)
+endmacro(flann_add_pyunit)

src/cpp/CMakeLists.txt

@@ -16,7 +16,7 @@ endif()
 set_property(TARGET flann_cpp_s PROPERTY COMPILE_DEFINITIONS FLANN_STATIC FLANN_USE_CUDA)
 
 if (BUILD_CUDA_LIB)
-    SET(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS};-DFLANN_USE_CUDA")
+    SET(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS};-DFLANN_USE_CUDA;-Xcudafe \"--diag_suppress=partial_override\" ;-gencode=arch=compute_52,code=\"sm_52,compute_52\";-gencode=arch=compute_61,code=\"sm_61,compute_61\"")
     if(CMAKE_COMPILER_IS_GNUCC)
 		set(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS};-Xcompiler;-fPIC;" )
         if (NVCC_COMPILER_BINDIR)

src/cpp/flann/algorithms/hierarchical_clustering_index.h

@@ -381,7 +381,7 @@ class HierarchicalClusteringIndex : public NNIndex<Distance>
         	for(size_t i=0; i<childs.size(); i++){
         		childs[i]->~Node();
 				pivot = NULL;
-				pivot_index = -1;
+				pivot_index = SIZE_MAX;
         	}
         };
 

src/cpp/flann/algorithms/kdtree_cuda_3d_index.h

@@ -87,7 +87,7 @@ class KDTreeCuda3dIndex : public NNIndex<Distance>
      *          params = parameters passed to the kdtree algorithm
      */
     KDTreeCuda3dIndex(const Matrix<ElementType>& inputData, const IndexParams& params = KDTreeCuda3dIndexParams(),
-                      Distance d = Distance() ) : BaseClass(params,d), dataset_(inputData), leaf_count_(0), visited_leafs(0), node_count_(0), current_node_count_(0)
+                      Distance d = Distance() ) : BaseClass(params,d), visited_leafs(0), dataset_(inputData), leaf_count_(0), node_count_(0), current_node_count_(0)
     {
         size_ = dataset_.rows;
         dim_ = dataset_.cols;

src/cpp/flann/algorithms/nn_index.h

@@ -361,7 +361,7 @@ class NNIndex : public IndexBase
      * @param params
      * @return
      */
-    int knnSearch(const Matrix<ElementType>& queries,
+	virtual int knnSearch(const Matrix<ElementType>& queries,
                                  Matrix<int>& indices,
                                  Matrix<DistanceType>& dists,
                                  size_t knn,
@@ -388,7 +388,7 @@ class NNIndex : public IndexBase
      * @param[in] knn Number of nearest neighbors to return
      * @param[in] params Search parameters
      */
-    int knnSearch(const Matrix<ElementType>& queries,
+	virtual int knnSearch(const Matrix<ElementType>& queries,
 					std::vector< std::vector<size_t> >& indices,
 					std::vector<std::vector<DistanceType> >& dists,
     				size_t knn,
@@ -459,7 +459,7 @@ class NNIndex : public IndexBase
      * @param params
      * @return
      */
-    int knnSearch(const Matrix<ElementType>& queries,
+	virtual int knnSearch(const Matrix<ElementType>& queries,
                                  std::vector< std::vector<int> >& indices,
                                  std::vector<std::vector<DistanceType> >& dists,
                                  size_t knn,
@@ -484,7 +484,7 @@ class NNIndex : public IndexBase
      * @param[in] params Search parameters
      * @return Number of neighbors found
      */
-    int radiusSearch(const Matrix<ElementType>& queries,
+	virtual int radiusSearch(const Matrix<ElementType>& queries,
     		Matrix<size_t>& indices,
     		Matrix<DistanceType>& dists,
     		float radius,
@@ -567,7 +567,7 @@ class NNIndex : public IndexBase
      * @param params
      * @return
      */
-    int radiusSearch(const Matrix<ElementType>& queries,
+	virtual int radiusSearch(const Matrix<ElementType>& queries,
                                     Matrix<int>& indices,
                                     Matrix<DistanceType>& dists,
                                     float radius,
@@ -594,7 +594,7 @@ class NNIndex : public IndexBase
      * @param[in] params Search parameters
      * @return Number of neighbors found
      */
-    int radiusSearch(const Matrix<ElementType>& queries,
+	virtual int radiusSearch(const Matrix<ElementType>& queries,
     		std::vector< std::vector<size_t> >& indices,
     		std::vector<std::vector<DistanceType> >& dists,
     		float radius,
@@ -673,7 +673,7 @@ class NNIndex : public IndexBase
      * @param params
      * @return
      */
-    int radiusSearch(const Matrix<ElementType>& queries,
+	virtual int radiusSearch(const Matrix<ElementType>& queries,
                                     std::vector< std::vector<int> >& indices,
                                     std::vector<std::vector<DistanceType> >& dists,
                                     float radius,

src/cpp/flann/util/result_set.h

@@ -107,7 +107,7 @@ class KNNSimpleResultSet : public ResultSet<DistanceType>
         capacity_(capacity_)
     {
 		// reserving capacity to prevent memory re-allocations
-		dist_index_.resize(capacity_, DistIndex(std::numeric_limits<DistanceType>::max(),-1));
+		dist_index_.resize(capacity_, DistIndex(std::numeric_limits<DistanceType>::max(),std::numeric_limits<size_t>::max()));
     	clear();
     }
 
@@ -210,7 +210,7 @@ class KNNResultSet : public ResultSet<DistanceType>
     KNNResultSet(int capacity) : capacity_(capacity)
     {
 		// reserving capacity to prevent memory re-allocations
-		dist_index_.resize(capacity_, DistIndex(std::numeric_limits<DistanceType>::max(),-1));
+		dist_index_.resize(capacity_, DistIndex(std::numeric_limits<DistanceType>::max(),std::numeric_limits<size_t>::max()));
     	clear();
     }
 

src/cpp/flann/util/serialization.h

@@ -723,7 +723,7 @@ class LoadArchive : public InputArchive<LoadArchive>
         // If not v1.0 format hack...
         if (buffer_blocks_ != NULL) {
             // Read the last '0' in the file
-            size_t zero = -1;
+            size_t zero = 1;
             if (fread(&zero, sizeof(zero), 1, stream_) != 1) {
                 throw FLANNException("Invalid index file, cannot read from disk (end)");
             }

test/CMakeLists.txt

@@ -10,15 +10,6 @@ add_dependencies(test tests)
 
 set(EXECUTABLE_OUTPUT_PATH ${TEST_OUTPUT_PATH})
 
-if (PYTHON_EXECUTABLE) 
-    flann_download_test_data(sift10K.h5 0964a910946d2dd5fe28337507a8abc3)
-    flann_download_test_data(sift10K_byte.h5 f835e0148df4618a81f67febfda2b4d0)
-    flann_download_test_data(sift100K.h5 ae2b08f93f3d9f89f5d68566b0406102)
-    flann_download_test_data(sift100K_byte.h5 b772255fd2044e9d2a5a0183953e4705)
-    flann_download_test_data(cloud.h5 dfc77bad391a3ae739a9874f4a5dc0d7)
-    flann_download_test_data(brief100K.h5 e1e781c0955917bc2f0a27b6344c2342)
-endif()
-
 if (GTEST_FOUND AND HDF5_FOUND)
     include_directories(${HDF5_INCLUDE_DIR})
 
@@ -56,7 +47,7 @@ if (GTEST_FOUND AND HDF5_FOUND)
 endif()
 
 if (GTEST_FOUND AND HDF5_FOUND AND BUILD_CUDA_LIB)
-    set(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS};-Xcompiler;-fPIC;-arch=sm_13" )
+    set(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS};-Xcompiler;-fPIC;-Xcudafe \"--diag_suppress=partial_override\" ;-gencode=arch=compute_52,code=\"sm_52,compute_52\";-gencode=arch=compute_61,code=\"sm_61,compute_61\"" )
     if (NVCC_COMPILER_BINDIR)
         set(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS};--compiler-bindir=${NVCC_COMPILER_BINDIR}")
     endif()
@@ -75,9 +66,9 @@ if (BUILD_PYTHON_BINDINGS)
 endif()
 
 #---------- ruby spec ----------------
-if (BUILD_C_BINDINGS)
-    add_custom_target(flann_ruby_spec
-                    COMMAND bundle exec rake spec
-                    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/src/ruby)
-    add_dependencies(test flann_ruby_spec)
-endif()
+#if (BUILD_C_BINDINGS)
+#    add_custom_target(flann_ruby_spec
+#                    COMMAND bundle exec rake spec
+#                    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/src/ruby)
+#    add_dependencies(test flann_ruby_spec)
+#endif()

test/flann_autotuned_test.cpp

@@ -27,9 +27,9 @@ class Autotuned_SIFT100K : public FLANNTestFixture {
         indices = flann::Matrix<size_t>(new size_t[1000*5], 1000, 5);
         printf("Reading test data...");
         fflush(stdout);
-        flann::load_from_file(data, "sift100K.h5","dataset");
-        flann::load_from_file(query,"sift100K.h5","query");
-        flann::load_from_file(match,"sift100K.h5","match");
+        flann::load_from_file(data, "../datasets/sift100K.h5","dataset");
+        flann::load_from_file(query,"../datasets/sift100K.h5","query");
+        flann::load_from_file(match,"../datasets/sift100K.h5","match");
         printf("done\n");
     }
 

test/flann_cuda_test.cu

@@ -112,9 +112,9 @@ protected:
     {
         printf("Reading test data...");
         fflush(stdout);
-        flann::load_from_file(data, "cloud.h5","dataset");
-        flann::load_from_file(query,"cloud.h5","query");
-        flann::load_from_file(match,"cloud.h5","indices");
+        flann::load_from_file(data, "../datasets/cloud.h5","dataset");
+        flann::load_from_file(query,"../datasets/cloud.h5","query");
+        flann::load_from_file(match,"../datasets/cloud.h5","match");
 
         dists = flann::Matrix<float>(new float[query.rows*5], query.rows, 5);
         indices = flann::Matrix<int>(new int[query.rows*5], query.rows, 5);

test/flann_hierarchical_test.cpp

@@ -28,8 +28,8 @@ class HierarchicalIndex_Brief100K : public FLANNTestFixture
 		k_nn_ = 3;
 		printf("Reading test data...");
 		fflush(stdout);
-		flann::load_from_file(data, "brief100K.h5", "dataset");
-		flann::load_from_file(query, "brief100K.h5", "query");
+		flann::load_from_file(data, "../datasets/brief100K.h5", "dataset");
+		flann::load_from_file(query, "../datasets/brief100K.h5", "query");
 		printf("done\n");
 
 		flann::Index<Distance> index(data, flann::LinearIndexParams());

test/flann_kdtree_single_test.cpp

@@ -10,7 +10,7 @@ using namespace flann;
 
 class KDTreeSingle :public DatasetTestFixture<float, float> {
 protected:
-	KDTreeSingle() : DatasetTestFixture("cloud.h5") {}
+	KDTreeSingle() : DatasetTestFixture("../datasets/cloud.h5") {}
 };
 
 TEST_F(KDTreeSingle, TestSearch)
@@ -29,7 +29,7 @@ TEST_F(KDTreeSingle, TestSearch2)
 TEST_F(KDTreeSingle, TestSearchPadded)
 {
     flann::Matrix<float> data_padded;
-    flann::load_from_file(data_padded, "cloud.h5", "dataset_padded");
+    flann::load_from_file(data_padded, "../datasets/cloud.h5", "dataset_padded");
     flann::Matrix<float> data2(data_padded.ptr(), data_padded.rows, 3, data_padded.cols*sizeof(float));
 
 	TestSearch<L2_Simple<float> >(data2, flann::KDTreeSingleIndexParams(12, false),

test/flann_kdtree_test.cpp

@@ -13,7 +13,7 @@ using namespace flann;
  */
 class KDTree_SIFT10K : public DatasetTestFixture<float, float> {
 protected:
-	KDTree_SIFT10K() : DatasetTestFixture("sift10K.h5") {}
+	KDTree_SIFT10K() : DatasetTestFixture("../datasets/sift10K.h5") {}
 };
 
 TEST_F(KDTree_SIFT10K, TestSearch)
@@ -72,7 +72,7 @@ TEST_F(KDTree_SIFT10K, TestCopy2)
  */
 class KDTree_SIFT100K : public DatasetTestFixture<float, float> {
 protected:
-	KDTree_SIFT100K() : DatasetTestFixture("sift100K.h5") {}
+	KDTree_SIFT100K() : DatasetTestFixture("../datasets/sift100K.h5") {}
 };
 
 
@@ -110,7 +110,7 @@ TEST_F(KDTree_SIFT100K, TestRemove)
  */
 class KDTree_SIFT10K_byte : public DatasetTestFixture<unsigned char, float> {
 protected:
-	KDTree_SIFT10K_byte() : DatasetTestFixture("sift10K_byte.h5") {}
+	KDTree_SIFT10K_byte() : DatasetTestFixture("../datasets/sift10K_byte.h5") {}
 };
 
 
@@ -123,7 +123,7 @@ TEST_F(KDTree_SIFT10K_byte, TestSearch)
 
 class KDTree_SIFT100K_byte : public DatasetTestFixture<unsigned char, float> {
 protected:
-	KDTree_SIFT100K_byte() : DatasetTestFixture("sift100K_byte.h5") {}
+	KDTree_SIFT100K_byte() : DatasetTestFixture("../datasets/sift100K_byte.h5") {}
 };
 
 

test/flann_kmeans_test.cpp

@@ -13,7 +13,7 @@ using namespace flann;
  */
 class KMeans_SIFT10K : public DatasetTestFixture<float, float> {
 protected:
-	KMeans_SIFT10K() : DatasetTestFixture("sift10K.h5") {}
+	KMeans_SIFT10K() : DatasetTestFixture("../datasets/sift10K.h5") {}
 };
 
 
@@ -77,7 +77,7 @@ TEST_F(KMeans_SIFT10K, TestCopy2)
  */
 class KMeans_SIFT100K : public DatasetTestFixture<float, float> {
 protected:
-	KMeans_SIFT100K() : DatasetTestFixture("sift100K.h5") {}
+	KMeans_SIFT100K() : DatasetTestFixture("../datasets/sift100K.h5") {}
 };
 
 
@@ -120,7 +120,7 @@ TEST_F(KMeans_SIFT100K, TestSave)
  */
 class KMeans_SIFT10K_byte :  public DatasetTestFixture<unsigned char, float> {
 protected:
-	KMeans_SIFT10K_byte() : DatasetTestFixture("sift10K_byte.h5") {}
+	KMeans_SIFT10K_byte() : DatasetTestFixture("../datasets/sift10K_byte.h5") {}
 };
 
 TEST_F(KMeans_SIFT10K_byte, TestSearch)
@@ -133,7 +133,7 @@ TEST_F(KMeans_SIFT10K_byte, TestSearch)
 
 class KMeans_SIFT100K_byte : public DatasetTestFixture<unsigned char, float> {
 protected:
-	KMeans_SIFT100K_byte() : DatasetTestFixture("sift100K_byte.h5") {}
+	KMeans_SIFT100K_byte() : DatasetTestFixture("../datasets/sift100K_byte.h5") {}
 };
 
 TEST_F(KMeans_SIFT100K_byte, TestSearch)

test/flann_linear_test.cpp

@@ -13,7 +13,7 @@ using namespace flann;
  */
 class Linear_SIFT10K : public DatasetTestFixture<float, float> {
 protected:
-	Linear_SIFT10K() : DatasetTestFixture("sift10K.h5") {}
+	Linear_SIFT10K() : DatasetTestFixture("../datasets/sift10K.h5") {}
 };
 
 
@@ -61,7 +61,7 @@ TEST_F(Linear_SIFT10K, TestCopy2)
  */
 class Linear_SIFT100K :  public DatasetTestFixture<float, float> {
 protected:
-	Linear_SIFT100K() : DatasetTestFixture("sift100K.h5") {}
+	Linear_SIFT100K() : DatasetTestFixture("../datasets/sift100K.h5") {}
 };
 
 
@@ -77,7 +77,7 @@ TEST_F(Linear_SIFT100K, TestSearch)
  */
 class Linear_SIFT10K_byte : public DatasetTestFixture<unsigned char, float> {
 protected:
-	Linear_SIFT10K_byte() : DatasetTestFixture("sift10K_byte.h5") {}
+	Linear_SIFT10K_byte() : DatasetTestFixture("../datasets/sift10K_byte.h5") {}
 };
 
 
@@ -93,7 +93,7 @@ TEST_F(Linear_SIFT10K_byte, Linear)
 
 class Linear_SIFT100K_byte : public DatasetTestFixture<unsigned char, float> {
 protected:
-	Linear_SIFT100K_byte() : DatasetTestFixture("sift100K_byte.h5") {}
+	Linear_SIFT100K_byte() : DatasetTestFixture("../datasets/sift100K_byte.h5") {}
 };
 
 

test/flann_lsh_test.cpp

@@ -28,16 +28,16 @@ class LshIndex_Brief100K : public FLANNTestFixture
 		k_nn_ = 3;
 		printf("Reading test data...");
 		fflush(stdout);
-		flann::load_from_file(data, "brief100K.h5", "dataset");
-		flann::load_from_file(query, "brief100K.h5", "query");
+		flann::load_from_file(data, "../datasets/brief100K.h5", "dataset");
+		flann::load_from_file(query, "../datasets/brief100K.h5", "query");
 
 		dists = flann::Matrix<DistanceType>(new DistanceType[query.rows * k_nn_], query.rows, k_nn_);
 		indices = flann::Matrix<size_t>(new size_t[query.rows * k_nn_], query.rows, k_nn_);
 
 		printf("done\n");
 
 		// The matches are bogus so we compute them the hard way
-		//    flann::load_from_file(match,"brief100K.h5","indices");
+		//    flann::load_from_file(match,"../datasets/brief100K.h5","indices");
 
 		flann::Index<Distance> index(data, flann::LinearIndexParams());
 		index.buildIndex();

test/flann_multithreaded_test.cpp

@@ -68,9 +68,9 @@ class FlannTest : public FLANNTestFixture {
 
         printf("Reading test data...");
         fflush(stdout);
-        flann::load_from_file(data_, "cloud.h5","dataset");
-        flann::load_from_file(query_,"cloud.h5","query");
-        flann::load_from_file(match_,"cloud.h5","match");
+        flann::load_from_file(data_, "../datasets/cloud.h5","dataset");
+        flann::load_from_file(query_,"../datasets/cloud.h5","query");
+        flann::load_from_file(match_,"../datasets/cloud.h5","match");
 
         dists_ = flann::Matrix<float>(new float[query_.rows*knn_], query_.rows, knn_);
         indices_ = flann::Matrix<size_t>(new size_t[query_.rows*knn_], query_.rows, knn_);
@@ -155,8 +155,8 @@ class FlannCompareKnnTest : public FLANNTestFixture {
 
         printf("Reading test data...");
         fflush(stdout);
-        flann::load_from_file(data_, "cloud.h5","dataset");
-        flann::load_from_file(query_,"cloud.h5","query");
+        flann::load_from_file(data_, "../datasets/cloud.h5","dataset");
+        flann::load_from_file(query_,"../datasets/cloud.h5","query");
 
         dists_single_ = flann::Matrix<float>(new float[query_.rows*knn_], query_.rows, knn_);
         indices_single_ = flann::Matrix<size_t>(new size_t[query_.rows*knn_], query_.rows, knn_);
@@ -229,8 +229,8 @@ class FlannCompareRadiusTest : public FLANNTestFixture {
 
         printf("Reading test data...");
         fflush(stdout);
-        flann::load_from_file(data_, "cloud.h5","dataset");
-        flann::load_from_file(query_,"cloud.h5","query");
+        flann::load_from_file(data_, "../datasets/cloud.h5","dataset");
+        flann::load_from_file(query_,"../datasets/cloud.h5","query");
 
         int reserve_size = data_.rows / 1000;