Merge branch 'oap-project:master' into random_forest

oap-project · May 9, 2023 · 0554684 · 0554684
2 parents a4f1cd5 + e8ee55f
commit 0554684
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Showing 9 changed files with 33 additions and 17 deletions.
diff --git a/mllib-dal/src/main/native/CorrelationImpl.cpp b/mllib-dal/src/main/native/CorrelationImpl.cpp
@@ -35,7 +35,7 @@ namespace covariance_cpu = daal::algorithms::covariance;
 
 typedef double algorithmFPType; /* Algorithm floating-point type */
 
-static void doCorrelationDaalCompute(JNIEnv *env, jobject obj, int rankId,
+static void doCorrelationDaalCompute(JNIEnv *env, jobject obj, size_t rankId,
                                      ccl::communicator &comm,
                                      const NumericTablePtr &pData,
                                      size_t nBlocks, jobject resultObj) {
@@ -235,6 +235,10 @@ Java_com_intel_oap_mllib_stat_CorrelationDALImpl_cCorrelationTrainDAL(
         break;
     }
 #endif
+    default: {
+        std::cout << "no supported device!" << std::endl;
+        exit(-1);
+    }
     }
     return 0;
 }
diff --git a/mllib-dal/src/main/native/KMeansImpl.cpp b/mllib-dal/src/main/native/KMeansImpl.cpp
@@ -37,7 +37,7 @@ namespace kmeans_cpu = daal::algorithms::kmeans;
 
 typedef double algorithmFPType; /* Algorithm floating-point type */
 
-static NumericTablePtr kmeans_compute(int rankId, ccl::communicator &comm,
+static NumericTablePtr kmeans_compute(size_t rankId, ccl::communicator &comm,
                                       const NumericTablePtr &pData,
                                       const NumericTablePtr &initialCentroids,
                                       size_t nClusters, size_t nBlocks,
@@ -174,7 +174,7 @@ static bool areAllCentersConverged(const NumericTablePtr &oldCenters,
     return true;
 }
 
-static jlong doKMeansDaalCompute(JNIEnv *env, jobject obj, int rankId,
+static jlong doKMeansDaalCompute(JNIEnv *env, jobject obj, size_t rankId,
                                  ccl::communicator &comm,
                                  NumericTablePtr &pData,
                                  NumericTablePtr &centroids, jint cluster_num,
@@ -354,6 +354,10 @@ Java_com_intel_oap_mllib_clustering_KMeansDALImpl_cKMeansOneapiComputeWithInitCe
         break;
     }
 #endif
+    default: {
+        std::cout << "no supported device!" << std::endl;
+        exit(-1);
+    }
     }
     return ret;
 }
diff --git a/mllib-dal/src/main/native/LinearRegressionImpl.cpp b/mllib-dal/src/main/native/LinearRegressionImpl.cpp
@@ -41,7 +41,7 @@ namespace ridge_regression_cpu = daal::algorithms::ridge_regression;
 
 typedef double algorithmFPType; /* Algorithm floating-point type */
 
-static NumericTablePtr linear_regression_compute(int rankId,
+static NumericTablePtr linear_regression_compute(size_t rankId,
                                                  ccl::communicator &comm,
                                                  const NumericTablePtr &pData,
                                                  const NumericTablePtr &pLabel,
@@ -126,7 +126,7 @@ static NumericTablePtr linear_regression_compute(int rankId,
 }
 
 static NumericTablePtr ridge_regression_compute(
-    int rankId, ccl::communicator &comm, const NumericTablePtr &pData,
+    size_t rankId, ccl::communicator &comm, const NumericTablePtr &pData,
     const NumericTablePtr &pLabel, double regParam, size_t nBlocks) {
 
     using daal::byte;
@@ -213,7 +213,7 @@ static NumericTablePtr ridge_regression_compute(
 }
 
 #ifdef CPU_GPU_PROFILE
-static jlong doLROneAPICompute(JNIEnv *env, int rankId,
+static jlong doLROneAPICompute(JNIEnv *env, size_t rankId,
                                ccl::communicator &cclComm, sycl::queue &queue,
                                jlong pData, jlong pLabel, jint executorNum,
                                jobject resultObj) {
@@ -262,7 +262,7 @@ Java_com_intel_oap_mllib_regression_LinearRegressionDALImpl_cLinearRegressionTra
               << std::endl;
 
     ccl::communicator &cclComm = getComm();
-    int rankId = cclComm.rank();
+    size_t rankId = cclComm.rank();
 
     ComputeDevice device = getComputeDeviceByOrdinal(computeDeviceOrdinal);
     bool useGPU = false;

diff --git a/mllib-dal/src/main/native/Makefile b/mllib-dal/src/main/native/Makefile
@@ -29,7 +29,7 @@ $(info )
 $(info === Profile is $(PLATFORM_PROFILE) ===)
 $(info )
 
-CFLAGS_COMMON := -g -Wall -Wno-deprecated-declarations -fPIC -std=c++17 \
+CFLAGS_COMMON := -Wall -Wno-deprecated-declarations -fPIC -std=c++17 \
                  -I $(I_MPI_ROOT)/include \
                  -I $(DAALROOT)/include \
                  -I $(CCL_ROOT)/include/cpu/oneapi/ \

diff --git a/mllib-dal/src/main/native/NaiveBayesDALImpl.cpp b/mllib-dal/src/main/native/NaiveBayesDALImpl.cpp
@@ -26,8 +26,8 @@ trainModel(const ccl::communicator &comm, const NumericTablePtr &featuresTab,
     Profiler profiler("NaiveBayes");
 #endif
 
-    auto rankId = comm.rank();
-    auto nBlocks = comm.size();
+    size_t rankId = comm.rank();
+    size_t nBlocks = comm.size();
 
     /* Create an algorithm object to train the Naive Bayes model based on the
      * local-node data */
@@ -127,7 +127,7 @@ Java_com_intel_oap_mllib_classification_NaiveBayesDALImpl_cNaiveBayesDALCompute(
     jint class_num, jint executor_num, jint executor_cores, jobject resultObj) {
 
     ccl::communicator &comm = getComm();
-    auto rankId = comm.rank();
+    size_t rankId = comm.rank();
 
     NumericTablePtr featuresTab = *((NumericTablePtr *)pFeaturesTab);
     NumericTablePtr labelsTab = *((NumericTablePtr *)pLabelsTab);

diff --git a/mllib-dal/src/main/native/OneCCL.cpp b/mllib-dal/src/main/native/OneCCL.cpp
@@ -31,7 +31,7 @@
 #include "OneCCL.h"
 #include "com_intel_oap_mllib_OneCCL__.h"
 
-extern const int ccl_root = 0;
+extern const size_t ccl_root = 0;
 
 static const int CCL_IP_LEN = 128;
 static std::list<std::string> local_host_ips;

diff --git a/mllib-dal/src/main/native/OneCCL.h b/mllib-dal/src/main/native/OneCCL.h
@@ -44,4 +44,4 @@ event CCL_API gather(const BufferType *sendbuf, int sendcount,
 
 ccl::communicator &getComm();
 ccl::shared_ptr_class<ccl::kvs> &getKvs();
-extern const int ccl_root;
+extern const size_t ccl_root;
diff --git a/mllib-dal/src/main/native/PCAImpl.cpp b/mllib-dal/src/main/native/PCAImpl.cpp
@@ -39,9 +39,9 @@ namespace covariance_cpu = daal::algorithms::covariance;
 
 typedef double algorithmFPType; /* Algorithm floating-point type */
 
-static void doPCADAALCompute(JNIEnv *env, jobject obj, int rankId,
+static void doPCADAALCompute(JNIEnv *env, jobject obj, size_t rankId,
                              ccl::communicator &comm, NumericTablePtr &pData,
-                             int nBlocks, jobject resultObj) {
+                             size_t nBlocks, jobject resultObj) {
     std::cout << "oneDAL (native): CPU compute start" << std::endl;
     using daal::byte;
     auto t1 = std::chrono::high_resolution_clock::now();
@@ -252,7 +252,7 @@ Java_com_intel_oap_mllib_feature_PCADALImpl_cPCATrainDAL(
               << "; device " << ComputeDeviceString[computeDeviceOrdinal]
               << std::endl;
     ccl::communicator &cclComm = getComm();
-    int rankId = cclComm.rank();
+    size_t rankId = cclComm.rank();
     ComputeDevice device = getComputeDeviceByOrdinal(computeDeviceOrdinal);
     switch (device) {
     case ComputeDevice::host:
@@ -292,6 +292,10 @@ Java_com_intel_oap_mllib_feature_PCADALImpl_cPCATrainDAL(
         break;
     }
 #endif
+    default: {
+        std::cout << "no supported device!" << std::endl;
+        exit(-1);
+    }
     }
     return 0;
 }
diff --git a/mllib-dal/src/main/native/SummarizerImpl.cpp b/mllib-dal/src/main/native/SummarizerImpl.cpp
@@ -35,7 +35,7 @@ using namespace daal::services;
 
 typedef double algorithmFPType; /* Algorithm floating-point type */
 
-static void doSummarizerDAALCompute(JNIEnv *env, jobject obj, int rankId,
+static void doSummarizerDAALCompute(JNIEnv *env, jobject obj, size_t rankId,
                                     ccl::communicator &comm,
                                     const NumericTablePtr &pData,
                                     size_t nBlocks, jobject resultObj) {
@@ -304,6 +304,10 @@ Java_com_intel_oap_mllib_stat_SummarizerDALImpl_cSummarizerTrainDAL(
         break;
     }
 #endif
+    default: {
+        std::cout << "no supported device!" << std::endl;
+        exit(-1);
+    }
     }
     return 0;
 }