Merge branch 'branch-25.02' into fix_github_link

cpp/CMakeLists.txt

@@ -1,5 +1,5 @@
 #=============================================================================
-# Copyright (c) 2018-2024, NVIDIA CORPORATION.
+# Copyright (c) 2018-2025, NVIDIA CORPORATION.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -109,6 +109,17 @@ set(RMM_LOGGING_LEVEL "INFO" CACHE STRING "Choose the logging level.")
 set_property(CACHE RMM_LOGGING_LEVEL PROPERTY STRINGS "TRACE" "DEBUG" "INFO" "WARN" "ERROR" "CRITICAL" "OFF")
 message(VERBOSE "CUML_CPP: RMM_LOGGING_LEVEL = '${RMM_LOGGING_LEVEL}'.")
 
+# Set logging level
+set(LIBCUML_LOGGING_LEVEL
+    "DEBUG"
+    CACHE STRING "Choose the logging level."
+)                                                                                                
+set_property(
+  CACHE LIBCUML_LOGGING_LEVEL PROPERTY STRINGS "TRACE" "DEBUG" "INFO" "WARN" "ERROR" "CRITICAL"
+                                       "OFF"
+)
+message(VERBOSE "CUML: LIBCUML_LOGGING_LEVEL = '${LIBCUML_LOGGING_LEVEL}'.")
+
 if(BUILD_CUML_TESTS OR BUILD_PRIMS_TESTS)
   # Needed because GoogleBenchmark changes the state of FindThreads.cmake, causing subsequent runs to
   # have different values for the `Threads::Threads` target. Setting this flag ensures
@@ -220,6 +231,12 @@ endif()
 rapids_cpm_init()
 rapids_cmake_install_lib_dir(lib_dir)
 
+include(${rapids-cmake-dir}/cpm/rapids_logger.cmake)
+rapids_cpm_rapids_logger()
+rapids_make_logger(
+  ML EXPORT_SET cuml-exports LOGGER_HEADER_DIR include/cuml/common/ LOGGER_MACRO_PREFIX CUML LOGGER_TARGET cuml_logger
+)
+
 if(BUILD_CUML_TESTS OR BUILD_PRIMS_TESTS)
   find_package(Threads)
 endif()
@@ -291,8 +308,7 @@ if(BUILD_CUML_CPP_LIBRARY)
 
   # single GPU components
   # common components
-  add_library(${CUML_CPP_TARGET}
-              src/common/logger.cpp)
+  add_library(${CUML_CPP_TARGET})
   if (CUML_ENABLE_GPU)
     target_compile_definitions(${CUML_CPP_TARGET} PUBLIC CUML_ENABLE_GPU)
   endif()
@@ -564,6 +580,7 @@ if(BUILD_CUML_CPP_LIBRARY)
         PRIVATE "$<$<COMPILE_LANGUAGE:CXX>:${CUML_CXX_FLAGS}>"
                 "$<$<COMPILE_LANGUAGE:CUDA>:${CUML_CUDA_FLAGS}>"
   )
+  target_compile_definitions(${CUML_CPP_TARGET} PUBLIC "CUML_LOG_ACTIVE_LEVEL=CUML_LOG_LEVEL_${LIBCUML_LOGGING_LEVEL}")
 
   target_include_directories(${CUML_CPP_TARGET}
     PUBLIC
@@ -604,6 +621,7 @@ if(BUILD_CUML_CPP_LIBRARY)
     raft::raft
     rmm::rmm_logger_impl
     raft::raft_logger_impl
+    cuml_logger_impl
     $<TARGET_NAME_IF_EXISTS:GPUTreeShap::GPUTreeShap>
     $<$<BOOL:${LINK_CUFFT}>:CUDA::cufft${_ctk_fft_static_suffix}>
     ${TREELITE_LIBS}
@@ -630,6 +648,7 @@ if(BUILD_CUML_CPP_LIBRARY)
   target_link_libraries(${CUML_CPP_TARGET}
     PUBLIC  rmm::rmm rmm::rmm_logger ${CUVS_LIB}
             ${_cuml_cpp_public_libs}
+            cuml_logger
     PRIVATE ${_cuml_cpp_private_libs}
   )
 

cpp/bench/sg/svc.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2020-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -100,8 +100,9 @@ std::vector<SvcParams<D>> getInputs()
   p.blobs.seed           = 12345ULL;
 
   // SvmParameter{C, cache_size, max_iter, nochange_steps, tol, verbosity})
-  p.svm_param = ML::SVM::SvmParameter{1, 200, 100, 100, 1e-3, CUML_LEVEL_INFO, 0, ML::SVM::C_SVC};
-  p.model     = ML::SVM::SvmModel<D>{0, 0, 0, nullptr, {}, nullptr, 0, nullptr};
+  p.svm_param =
+    ML::SVM::SvmParameter{1, 200, 100, 100, 1e-3, ML::level_enum::info, 0, ML::SVM::C_SVC};
+  p.model = ML::SVM::SvmModel<D>{0, 0, 0, nullptr, {}, nullptr, 0, nullptr};
 
   std::vector<Triplets> rowcols = {{50000, 2, 2}, {2048, 100000, 2}, {50000, 1000, 2}};
 

cpp/bench/sg/svr.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2020-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -102,7 +102,7 @@ std::vector<SvrParams<D>> getInputs()
   // SvmParameter{C, cache_size, max_iter, nochange_steps, tol, verbosity,
   //              epsilon, svmType})
   p.svm_param =
-    ML::SVM::SvmParameter{1, 200, 200, 100, 1e-3, CUML_LEVEL_INFO, 0.1, ML::SVM::EPSILON_SVR};
+    ML::SVM::SvmParameter{1, 200, 200, 100, 1e-3, ML::level_enum::info, 0.1, ML::SVM::EPSILON_SVR};
   p.model = new ML::SVM::SvmModel<D>{0, 0, 0, 0};
 
   std::vector<Triplets> rowcols = {{50000, 2, 2}, {1024, 10000, 10}, {3000, 200, 200}};

cpp/examples/dbscan/dbscan_example.cpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -209,7 +209,7 @@ int main(int argc, char* argv[])
                   nullptr,
                   max_bytes_per_batch,
                   ML::Dbscan::EpsNnMethod::BRUTE_FORCE,
-                  false);
+                  ML::level_enum::off);
   CUDA_RT_CALL(cudaMemcpyAsync(
     h_labels.data(), d_labels, nRows * sizeof(int), cudaMemcpyDeviceToHost, stream));
   CUDA_RT_CALL(cudaStreamSynchronize(stream));

cpp/include/cuml/cluster/dbscan.hpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2018-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -16,7 +16,7 @@
 
 #pragma once
 
-#include <cuml/common/log_levels.hpp>
+#include <cuml/common/logger.hpp>
 
 #include <cuvs/distance/distance.hpp>
 
@@ -73,7 +73,7 @@ void fit(const raft::handle_t& handle,
          float* sample_weight       = nullptr,
          size_t max_bytes_per_batch = 0,
          EpsNnMethod eps_nn_method  = BRUTE_FORCE,
-         int verbosity              = CUML_LEVEL_INFO,
+         level_enum verbosity       = ML::level_enum::info,
          bool opg                   = false);
 void fit(const raft::handle_t& handle,
          double* input,
@@ -87,7 +87,7 @@ void fit(const raft::handle_t& handle,
          double* sample_weight      = nullptr,
          size_t max_bytes_per_batch = 0,
          EpsNnMethod eps_nn_method  = BRUTE_FORCE,
-         int verbosity              = CUML_LEVEL_INFO,
+         level_enum verbosity       = ML::level_enum::info,
          bool opg                   = false);
 
 void fit(const raft::handle_t& handle,
@@ -102,7 +102,7 @@ void fit(const raft::handle_t& handle,
          float* sample_weight         = nullptr,
          size_t max_bytes_per_batch   = 0,
          EpsNnMethod eps_nn_method    = BRUTE_FORCE,
-         int verbosity                = CUML_LEVEL_INFO,
+         level_enum verbosity         = ML::level_enum::info,
          bool opg                     = false);
 void fit(const raft::handle_t& handle,
          double* input,
@@ -116,7 +116,7 @@ void fit(const raft::handle_t& handle,
          double* sample_weight        = nullptr,
          size_t max_bytes_per_batch   = 0,
          EpsNnMethod eps_nn_method    = BRUTE_FORCE,
-         int verbosity                = CUML_LEVEL_INFO,
+         level_enum verbosity         = ML::level_enum::info,
          bool opg                     = false);
 
 /** @} */

cpp/include/cuml/cluster/kmeans.hpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -16,8 +16,6 @@
 
 #pragma once
 
-#include <cuml/common/log_levels.hpp>
-
 #include <cuvs/cluster/kmeans.hpp>
 
 namespace raft {