From 70fe52684493c9073abf830533efe2ea7338adec Mon Sep 17 00:00:00 2001 From: Ben Frederickson Date: Thu, 3 Oct 2024 20:03:32 -0700 Subject: [PATCH 1/2] Migrate to use cuVS for vector search (#6085) This PR updates to use cuVS instead of RAFT for vector search, pairwise distances and clustering. This is required for us to deprecate the vector search functionality in RAFT, in favour of the code in cuVS. Because some code hasn't been migrated over to cuvs yet, we will continue to use the version in RAFT - but with RAFT in header only mode. In particular this functionality will be used in RAFT header only mode: * Random Ball Cover (see https://github.com/rapidsai/cuvs/pull/218) * Sparse KNN * nn-descent https://github.com/rapidsai/cuvs/issues/364 * [MetricProcessor](https://github.com/rapidsai/cuml/pull/6085/commits/c7d1b0ee57dfc9ee0b525ccdc273538712406a77) * knn_merge_parts * build_dendrogram_host * build_sorted_mst * raft DistanceType Because sparse KNN in RAFT uses the DistanceType in RAFT, we can't fully move over to use the DistanceType code in cuVS with this PR. (Also the DistanceType code in RAFT has a `Precomputed` option that isn't available in cuvs - but is needed by cuml for dbscan.) This means that we have both the raft and cuvs DistanceType enum's in use with this change, with conversions between them. Authors: - Ben Frederickson (https://github.com/benfred) - Bradley Dice (https://github.com/bdice) - Kyle Edwards (https://github.com/KyleFromNVIDIA) - Corey J. Nolet (https://github.com/cjnolet) Approvers: - Corey J. Nolet (https://github.com/cjnolet) - Dante Gama Dessavre (https://github.com/dantegd) - Bradley Dice (https://github.com/bdice) URL: https://github.com/rapidsai/cuml/pull/6085 --- ci/build_wheel.sh | 7 +- ci/release/update-version.sh | 2 + .../all_cuda-118_arch-x86_64.yaml | 3 +- .../all_cuda-125_arch-x86_64.yaml | 3 +- .../clang_tidy_cuda-118_arch-x86_64.yaml | 2 +- .../cpp_all_cuda-118_arch-x86_64.yaml | 2 +- .../cpp_all_cuda-125_arch-x86_64.yaml | 2 +- conda/recipes/libcuml/meta.yaml | 4 +- cpp/CMakeLists.txt | 21 +- cpp/bench/CMakeLists.txt | 1 - cpp/bench/sg/kmeans.cu | 2 +- cpp/cmake/thirdparty/get_cuvs.cmake | 77 ++ cpp/cmake/thirdparty/get_raft.cmake | 12 +- cpp/examples/kmeans/kmeans_example.cpp | 2 +- cpp/include/cuml/cluster/kmeans.hpp | 4 +- cpp/include/cuml/cluster/kmeans_mg.hpp | 10 +- cpp/include/cuml/neighbors/knn.hpp | 48 +- cpp/src/hdbscan/detail/soft_clustering.cuh | 50 +- cpp/src/hdbscan/runner.h | 25 +- cpp/src/kmeans/kmeans_fit_predict.cu | 16 +- cpp/src/kmeans/kmeans_mg.cu | 85 +- cpp/src/kmeans/kmeans_mg_impl.cuh | 818 ------------------ cpp/src/kmeans/kmeans_predict.cu | 16 +- cpp/src/kmeans/kmeans_transform.cu | 16 +- cpp/src/knn/knn.cu | 216 ++++- cpp/src/knn/knn_opg_common.cuh | 30 +- cpp/src/metrics/pairwise_distance.cu | 133 +-- cpp/src/metrics/pairwise_distance_canberra.cu | 59 -- .../metrics/pairwise_distance_canberra.cuh | 47 - .../metrics/pairwise_distance_chebyshev.cu | 58 -- .../metrics/pairwise_distance_chebyshev.cuh | 46 - .../metrics/pairwise_distance_correlation.cu | 61 -- .../metrics/pairwise_distance_correlation.cuh | 47 - cpp/src/metrics/pairwise_distance_cosine.cu | 60 -- cpp/src/metrics/pairwise_distance_cosine.cuh | 46 - .../metrics/pairwise_distance_euclidean.cu | 102 --- .../metrics/pairwise_distance_euclidean.cuh | 46 - cpp/src/metrics/pairwise_distance_hamming.cu | 61 -- cpp/src/metrics/pairwise_distance_hamming.cuh | 47 - .../metrics/pairwise_distance_hellinger.cu | 60 -- .../metrics/pairwise_distance_hellinger.cuh | 45 - .../pairwise_distance_jensen_shannon.cu | 58 -- .../pairwise_distance_jensen_shannon.cuh | 47 - .../pairwise_distance_kl_divergence.cu | 57 -- .../pairwise_distance_kl_divergence.cuh | 47 - cpp/src/metrics/pairwise_distance_l1.cu | 57 -- cpp/src/metrics/pairwise_distance_l1.cuh | 46 - .../metrics/pairwise_distance_minkowski.cu | 57 -- .../metrics/pairwise_distance_minkowski.cuh | 47 - .../metrics/pairwise_distance_russell_rao.cu | 59 -- .../metrics/pairwise_distance_russell_rao.cuh | 47 - cpp/src/metrics/silhouette_score.cu | 20 +- .../silhouette_score_batched_double.cu | 22 +- .../metrics/silhouette_score_batched_float.cu | 21 +- cpp/src/metrics/trustworthiness.cu | 13 +- cpp/src/tsne/distances.cuh | 41 +- cpp/src/umap/knn_graph/algo.cuh | 34 +- cpp/test/CMakeLists.txt | 1 - cpp/test/prims/knn_classify.cu | 26 +- cpp/test/prims/knn_regression.cu | 27 +- cpp/test/sg/hdbscan_test.cu | 3 +- cpp/test/sg/umap_parametrizable_test.cu | 25 +- dependencies.yaml | 11 +- python/cuml/CMakeLists.txt | 15 +- python/cuml/cuml/cluster/cpp/kmeans.pxd | 22 +- python/cuml/cuml/cluster/kmeans.pyx | 10 +- python/cuml/cuml/cluster/kmeans_mg.pyx | 2 +- python/cuml/cuml/cluster/kmeans_utils.pxd | 34 +- python/cuml/cuml/neighbors/ann.pxd | 15 +- .../cuml/cuml/tests/test_nearest_neighbors.py | 6 +- python/cuml/pyproject.toml | 2 + 71 files changed, 694 insertions(+), 2570 deletions(-) create mode 100644 cpp/cmake/thirdparty/get_cuvs.cmake delete mode 100644 cpp/src/kmeans/kmeans_mg_impl.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_canberra.cu delete mode 100644 cpp/src/metrics/pairwise_distance_canberra.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_chebyshev.cu delete mode 100644 cpp/src/metrics/pairwise_distance_chebyshev.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_correlation.cu delete mode 100644 cpp/src/metrics/pairwise_distance_correlation.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_cosine.cu delete mode 100644 cpp/src/metrics/pairwise_distance_cosine.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_euclidean.cu delete mode 100644 cpp/src/metrics/pairwise_distance_euclidean.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_hamming.cu delete mode 100644 cpp/src/metrics/pairwise_distance_hamming.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_hellinger.cu delete mode 100644 cpp/src/metrics/pairwise_distance_hellinger.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_jensen_shannon.cu delete mode 100644 cpp/src/metrics/pairwise_distance_jensen_shannon.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_kl_divergence.cu delete mode 100644 cpp/src/metrics/pairwise_distance_kl_divergence.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_l1.cu delete mode 100644 cpp/src/metrics/pairwise_distance_l1.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_minkowski.cu delete mode 100644 cpp/src/metrics/pairwise_distance_minkowski.cuh delete mode 100644 cpp/src/metrics/pairwise_distance_russell_rao.cu delete mode 100644 cpp/src/metrics/pairwise_distance_russell_rao.cuh diff --git a/ci/build_wheel.sh b/ci/build_wheel.sh index af3a4c124b..976d7003dd 100755 --- a/ci/build_wheel.sh +++ b/ci/build_wheel.sh @@ -21,6 +21,7 @@ cd ${package_dir} case "${RAPIDS_CUDA_VERSION}" in 12.*) EXCLUDE_ARGS=( + --exclude "libcuvs.so" --exclude "libcublas.so.12" --exclude "libcublasLt.so.12" --exclude "libcufft.so.11" @@ -32,12 +33,14 @@ case "${RAPIDS_CUDA_VERSION}" in EXTRA_CMAKE_ARGS=";-DUSE_CUDA_MATH_WHEELS=ON" ;; 11.*) - EXCLUDE_ARGS=() + EXCLUDE_ARGS=( + --exclude "libcuvs.so" + ) EXTRA_CMAKE_ARGS=";-DUSE_CUDA_MATH_WHEELS=OFF" ;; esac -SKBUILD_CMAKE_ARGS="-DDETECT_CONDA_ENV=OFF;-DDISABLE_DEPRECATION_WARNINGS=ON;-DCPM_cumlprims_mg_SOURCE=${GITHUB_WORKSPACE}/cumlprims_mg/${EXTRA_CMAKE_ARGS}" \ +SKBUILD_CMAKE_ARGS="-DDETECT_CONDA_ENV=OFF;-DDISABLE_DEPRECATION_WARNINGS=ON;-DCPM_cumlprims_mg_SOURCE=${GITHUB_WORKSPACE}/cumlprims_mg/;-DUSE_CUVS_WHEEL=ON${EXTRA_CMAKE_ARGS}" \ python -m pip wheel . \ -w dist \ -vvv \ diff --git a/ci/release/update-version.sh b/ci/release/update-version.sh index e234e1401f..c37ba94238 100755 --- a/ci/release/update-version.sh +++ b/ci/release/update-version.sh @@ -40,11 +40,13 @@ echo "${NEXT_FULL_TAG}" > VERSION DEPENDENCIES=( cudf cuml + cuvs dask-cuda dask-cudf libcuml libcuml-tests libcumlprims + libcuvs libraft-headers libraft librmm diff --git a/conda/environments/all_cuda-118_arch-x86_64.yaml b/conda/environments/all_cuda-118_arch-x86_64.yaml index 406789fffc..7bef5fcb11 100644 --- a/conda/environments/all_cuda-118_arch-x86_64.yaml +++ b/conda/environments/all_cuda-118_arch-x86_64.yaml @@ -14,6 +14,7 @@ dependencies: - cudatoolkit - cudf==24.10.*,>=0.0.0a0 - cupy>=12.0.0 +- cuvs==24.10.*,>=0.0.0a0 - cxx-compiler - cython>=3.0.0 - dask-cuda==24.10.*,>=0.0.0a0 @@ -39,8 +40,8 @@ dependencies: - libcusolver=11.4.1.48 - libcusparse-dev=11.7.5.86 - libcusparse=11.7.5.86 +- libcuvs==24.10.*,>=0.0.0a0 - libraft-headers==24.10.*,>=0.0.0a0 -- libraft==24.10.*,>=0.0.0a0 - librmm==24.10.*,>=0.0.0a0 - nbsphinx - ninja diff --git a/conda/environments/all_cuda-125_arch-x86_64.yaml b/conda/environments/all_cuda-125_arch-x86_64.yaml index 28c9197192..a016e3ccef 100644 --- a/conda/environments/all_cuda-125_arch-x86_64.yaml +++ b/conda/environments/all_cuda-125_arch-x86_64.yaml @@ -16,6 +16,7 @@ dependencies: - cuda-version=12.5 - cudf==24.10.*,>=0.0.0a0 - cupy>=12.0.0 +- cuvs==24.10.*,>=0.0.0a0 - cxx-compiler - cython>=3.0.0 - dask-cuda==24.10.*,>=0.0.0a0 @@ -36,8 +37,8 @@ dependencies: - libcurand-dev - libcusolver-dev - libcusparse-dev +- libcuvs==24.10.*,>=0.0.0a0 - libraft-headers==24.10.*,>=0.0.0a0 -- libraft==24.10.*,>=0.0.0a0 - librmm==24.10.*,>=0.0.0a0 - nbsphinx - ninja diff --git a/conda/environments/clang_tidy_cuda-118_arch-x86_64.yaml b/conda/environments/clang_tidy_cuda-118_arch-x86_64.yaml index f332c206d9..bec05e19f3 100644 --- a/conda/environments/clang_tidy_cuda-118_arch-x86_64.yaml +++ b/conda/environments/clang_tidy_cuda-118_arch-x86_64.yaml @@ -27,8 +27,8 @@ dependencies: - libcusolver=11.4.1.48 - libcusparse-dev=11.7.5.86 - libcusparse=11.7.5.86 +- libcuvs==24.10.*,>=0.0.0a0 - libraft-headers==24.10.*,>=0.0.0a0 -- libraft==24.10.*,>=0.0.0a0 - librmm==24.10.*,>=0.0.0a0 - ninja - nvcc_linux-64=11.8 diff --git a/conda/environments/cpp_all_cuda-118_arch-x86_64.yaml b/conda/environments/cpp_all_cuda-118_arch-x86_64.yaml index 66291a21ec..f70c53c16c 100644 --- a/conda/environments/cpp_all_cuda-118_arch-x86_64.yaml +++ b/conda/environments/cpp_all_cuda-118_arch-x86_64.yaml @@ -25,8 +25,8 @@ dependencies: - libcusolver=11.4.1.48 - libcusparse-dev=11.7.5.86 - libcusparse=11.7.5.86 +- libcuvs==24.10.*,>=0.0.0a0 - libraft-headers==24.10.*,>=0.0.0a0 -- libraft==24.10.*,>=0.0.0a0 - librmm==24.10.*,>=0.0.0a0 - ninja - nvcc_linux-64=11.8 diff --git a/conda/environments/cpp_all_cuda-125_arch-x86_64.yaml b/conda/environments/cpp_all_cuda-125_arch-x86_64.yaml index 90bdefa75e..2210fe6e8b 100644 --- a/conda/environments/cpp_all_cuda-125_arch-x86_64.yaml +++ b/conda/environments/cpp_all_cuda-125_arch-x86_64.yaml @@ -22,8 +22,8 @@ dependencies: - libcurand-dev - libcusolver-dev - libcusparse-dev +- libcuvs==24.10.*,>=0.0.0a0 - libraft-headers==24.10.*,>=0.0.0a0 -- libraft==24.10.*,>=0.0.0a0 - librmm==24.10.*,>=0.0.0a0 - ninja - spdlog>=1.14.1,<1.15 diff --git a/conda/recipes/libcuml/meta.yaml b/conda/recipes/libcuml/meta.yaml index ea1b935f01..f4a65c50f7 100644 --- a/conda/recipes/libcuml/meta.yaml +++ b/conda/recipes/libcuml/meta.yaml @@ -70,7 +70,7 @@ requirements: {% endif %} - fmt {{ fmt_version }} - libcumlprims ={{ minor_version }} - - libraft ={{ minor_version }} + - libcuvs ={{ minor_version }} - libraft-headers ={{ minor_version }} - librmm ={{ minor_version }} - spdlog {{ spdlog_version }} @@ -116,7 +116,7 @@ outputs: - libcusparse {% endif %} - libcumlprims ={{ minor_version }} - - libraft ={{ minor_version }} + - libcuvs ={{ minor_version }} - librmm ={{ minor_version }} - treelite {{ treelite_version }} about: diff --git a/cpp/CMakeLists.txt b/cpp/CMakeLists.txt index 7451bde50b..f400b244c8 100644 --- a/cpp/CMakeLists.txt +++ b/cpp/CMakeLists.txt @@ -64,8 +64,7 @@ option(SINGLEGPU "Disable all mnmg components and comms libraries" OFF) option(USE_CCACHE "Cache build artifacts with ccache" OFF) option(CUDA_STATIC_RUNTIME "Statically link the CUDA runtime" OFF) option(CUDA_STATIC_MATH_LIBRARIES "Statically link the CUDA math libraries" OFF) -option(CUML_USE_RAFT_STATIC "Build and statically link the RAFT libraries" OFF) -option(CUML_RAFT_COMPILED "Use libraft shared library" ON) +option(CUML_USE_CUVS_STATIC "Build and statically link the CUVS library" OFF) option(CUML_USE_TREELITE_STATIC "Build and statically link the treelite library" OFF) option(CUML_EXPORT_TREELITE_LINKAGE "Whether to publicly or privately link treelite to libcuml++" OFF) option(CUML_USE_CUMLPRIMS_MG_STATIC "Build and statically link the cumlprims_mg library" OFF) @@ -78,6 +77,7 @@ option(CUML_EXCLUDE_RAFT_FROM_ALL "Exclude RAFT targets from cuML's 'all' target option(CUML_EXCLUDE_TREELITE_FROM_ALL "Exclude Treelite targets from cuML's 'all' target" OFF) option(CUML_EXCLUDE_CUMLPRIMS_MG_FROM_ALL "Exclude cumlprims_mg targets from cuML's 'all' target" OFF) option(CUML_RAFT_CLONE_ON_PIN "Explicitly clone RAFT branch when pinned to non-feature branch" ON) +option(CUML_CUVS_CLONE_ON_PIN "Explicitly clone CUVS branch when pinned to non-feature branch" ON) message(VERBOSE "CUML_CPP: Building libcuml_c shared library. Contains the cuML C API: ${BUILD_CUML_C_LIBRARY}") message(VERBOSE "CUML_CPP: Building libcuml shared library: ${BUILD_CUML_CPP_LIBRARY}") @@ -98,7 +98,7 @@ message(VERBOSE "CUML_CPP: Disabling all mnmg components and comms libraries: ${ message(VERBOSE "CUML_CPP: Cache build artifacts with ccache: ${USE_CCACHE}") message(VERBOSE "CUML_CPP: Statically link the CUDA runtime: ${CUDA_STATIC_RUNTIME}") message(VERBOSE "CUML_CPP: Statically link the CUDA math libraries: ${CUDA_STATIC_MATH_LIBRARIES}") -message(VERBOSE "CUML_CPP: Build and statically link RAFT libraries: ${CUML_USE_RAFT_STATIC}") +message(VERBOSE "CUML_CPP: Build and statically link CUVS libraries: ${CUML_USE_CUVS_STATIC}") message(VERBOSE "CUML_CPP: Build and statically link Treelite library: ${CUML_USE_TREELITE_STATIC}") set(CUML_ALGORITHMS "ALL" CACHE STRING "Experimental: Choose which algorithms are built into libcuml++.so. Can specify individual algorithms or groups in a semicolon-separated list.") @@ -228,6 +228,7 @@ endif() include(cmake/thirdparty/get_cccl.cmake) include(cmake/thirdparty/get_rmm.cmake) include(cmake/thirdparty/get_raft.cmake) +include(cmake/thirdparty/get_cuvs.cmake) if(LINK_TREELITE) include(cmake/thirdparty/get_treelite.cmake) @@ -442,18 +443,6 @@ if(BUILD_CUML_CPP_LIBRARY) src/metrics/kl_divergence.cu src/metrics/mutual_info_score.cu src/metrics/pairwise_distance.cu - src/metrics/pairwise_distance_canberra.cu - src/metrics/pairwise_distance_chebyshev.cu - src/metrics/pairwise_distance_correlation.cu - src/metrics/pairwise_distance_cosine.cu - src/metrics/pairwise_distance_euclidean.cu - src/metrics/pairwise_distance_hamming.cu - src/metrics/pairwise_distance_hellinger.cu - src/metrics/pairwise_distance_jensen_shannon.cu - src/metrics/pairwise_distance_kl_divergence.cu - src/metrics/pairwise_distance_l1.cu - src/metrics/pairwise_distance_minkowski.cu - src/metrics/pairwise_distance_russell_rao.cu src/metrics/r2_score.cu src/metrics/rand_index.cu src/metrics/silhouette_score.cu @@ -635,7 +624,7 @@ if(BUILD_CUML_CPP_LIBRARY) ) target_link_libraries(${CUML_CPP_TARGET} - PUBLIC rmm::rmm + PUBLIC rmm::rmm ${CUVS_LIB} ${_cuml_cpp_public_libs} PRIVATE ${_cuml_cpp_private_libs} ) diff --git a/cpp/bench/CMakeLists.txt b/cpp/bench/CMakeLists.txt index 4f8c312717..237d8e0c6e 100644 --- a/cpp/bench/CMakeLists.txt +++ b/cpp/bench/CMakeLists.txt @@ -50,7 +50,6 @@ if(BUILD_CUML_BENCH) benchmark::benchmark ${TREELITE_LIBS} raft::raft - raft::compiled ) target_include_directories(${CUML_CPP_BENCH_TARGET} diff --git a/cpp/bench/sg/kmeans.cu b/cpp/bench/sg/kmeans.cu index 37eeed6346..7fb44a20fb 100644 --- a/cpp/bench/sg/kmeans.cu +++ b/cpp/bench/sg/kmeans.cu @@ -92,7 +92,7 @@ std::vector getInputs() p.kmeans.max_iter = 300; p.kmeans.tol = 1e-4; p.kmeans.verbosity = RAFT_LEVEL_INFO; - p.kmeans.metric = raft::distance::DistanceType::L2Expanded; + p.kmeans.metric = cuvs::distance::DistanceType::L2Expanded; p.kmeans.rng_state = raft::random::RngState(p.blobs.seed); p.kmeans.inertia_check = true; std::vector> rowcols = { diff --git a/cpp/cmake/thirdparty/get_cuvs.cmake b/cpp/cmake/thirdparty/get_cuvs.cmake new file mode 100644 index 0000000000..1d319206ba --- /dev/null +++ b/cpp/cmake/thirdparty/get_cuvs.cmake @@ -0,0 +1,77 @@ +#============================================================================= +# Copyright (c) 2024, NVIDIA CORPORATION. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#============================================================================= + +set(CUML_MIN_VERSION_cuvs "${CUML_VERSION_MAJOR}.${CUML_VERSION_MINOR}.00") +set(CUML_BRANCH_VERSION_cuvs "${CUML_VERSION_MAJOR}.${CUML_VERSION_MINOR}") + +function(find_and_configure_cuvs) + set(oneValueArgs VERSION FORK PINNED_TAG EXCLUDE_FROM_ALL USE_CUVS_STATIC COMPILE_LIBRARY CLONE_ON_PIN) + cmake_parse_arguments(PKG "${options}" "${oneValueArgs}" + "${multiValueArgs}" ${ARGN} ) + + if(PKG_CLONE_ON_PIN AND NOT PKG_PINNED_TAG STREQUAL "branch-${CUML_BRANCH_VERSION_cuvs}") + message(STATUS "CUML: CUVS pinned tag found: ${PKG_PINNED_TAG}. Cloning cuvs locally.") + set(CPM_DOWNLOAD_cuvs ON) + elseif(PKG_USE_CUVS_STATIC AND (NOT CPM_cuvs_SOURCE)) + message(STATUS "CUML: Cloning cuvs locally to build static libraries.") + set(CPM_DOWNLOAD_cuvs ON) + else() + message(STATUS "Not cloning cuvs locally") + endif() + + if(PKG_USE_CUVS_STATIC) + set(CUVS_LIB cuvs::cuvs_static PARENT_SCOPE) + else() + set(CUVS_LIB cuvs::cuvs PARENT_SCOPE) + endif() + + rapids_cpm_find(cuvs ${PKG_VERSION} + GLOBAL_TARGETS cuvs::cuvs + BUILD_EXPORT_SET cuml-exports + INSTALL_EXPORT_SET cuml-exports + CPM_ARGS + GIT_REPOSITORY https://github.com/${PKG_FORK}/cuvs.git + GIT_TAG ${PKG_PINNED_TAG} + SOURCE_SUBDIR cpp + EXCLUDE_FROM_ALL ${PKG_EXCLUDE_FROM_ALL} + OPTIONS + "BUILD_TESTS OFF" + "BUILD_BENCH OFF" + ) + + if(cuvs_ADDED) + message(VERBOSE "CUML: Using CUVS located in ${cuvs_SOURCE_DIR}") + else() + message(VERBOSE "CUML: Using CUVS located in ${cuvs_DIR}") + endif() + + +endfunction() + +# Change pinned tag here to test a commit in CI +# To use a different CUVS locally, set the CMake variable +# CPM_cuvs_SOURCE=/path/to/local/cuvs +find_and_configure_cuvs(VERSION ${CUML_MIN_VERSION_cuvs} + FORK rapidsai + PINNED_TAG branch-${CUML_BRANCH_VERSION_cuvs} + EXCLUDE_FROM_ALL ${CUML_EXCLUDE_CUVS_FROM_ALL} + # When PINNED_TAG above doesn't match cuml, + # force local cuvs clone in build directory + # even if it's already installed. + CLONE_ON_PIN ${CUML_CUVS_CLONE_ON_PIN} + COMPILE_LIBRARY ${CUML_CUVS_COMPILED} + USE_CUVS_STATIC ${CUML_USE_CUVS_STATIC} + ) diff --git a/cpp/cmake/thirdparty/get_raft.cmake b/cpp/cmake/thirdparty/get_raft.cmake index 7bc860eed8..4f260fcb93 100644 --- a/cpp/cmake/thirdparty/get_raft.cmake +++ b/cpp/cmake/thirdparty/get_raft.cmake @@ -36,16 +36,6 @@ function(find_and_configure_raft) string(APPEND RAFT_COMPONENTS " distributed") endif() - if(PKG_COMPILE_LIBRARY) - if(NOT PKG_USE_RAFT_STATIC) - string(APPEND RAFT_COMPONENTS " compiled") - set(RAFT_COMPILED_LIB raft::compiled PARENT_SCOPE) - else() - string(APPEND RAFT_COMPONENTS " compiled_static") - set(RAFT_COMPILED_LIB raft::compiled_static PARENT_SCOPE) - endif() - endif() - # We need to set this each time so that on subsequent calls to cmake # the raft-config.cmake re-evaluates the RAFT_NVTX value set(RAFT_NVTX ${PKG_NVTX}) @@ -66,7 +56,7 @@ function(find_and_configure_raft) "BUILD_TESTS OFF" "BUILD_BENCH OFF" "BUILD_CAGRA_HNSWLIB OFF" - "RAFT_COMPILE_LIBRARY ${PKG_COMPILE_LIBRARY}" + "RAFT_COMPILE_LIBRARY OFF" ) if(raft_ADDED) diff --git a/cpp/examples/kmeans/kmeans_example.cpp b/cpp/examples/kmeans/kmeans_example.cpp index 4e0a39e5bc..18433d8f16 100644 --- a/cpp/examples/kmeans/kmeans_example.cpp +++ b/cpp/examples/kmeans/kmeans_example.cpp @@ -112,7 +112,7 @@ int main(int argc, char* argv[]) params.max_iter = 300; params.tol = 0.05; } - params.metric = raft::distance::DistanceType::L2SqrtExpanded; + params.metric = cuvs::distance::DistanceType::L2SqrtExpanded; params.init = ML::kmeans::KMeansParams::InitMethod::Random; // Inputs copied from kmeans_test.cu diff --git a/cpp/include/cuml/cluster/kmeans.hpp b/cpp/include/cuml/cluster/kmeans.hpp index b62059945e..f075e49843 100644 --- a/cpp/include/cuml/cluster/kmeans.hpp +++ b/cpp/include/cuml/cluster/kmeans.hpp @@ -18,7 +18,7 @@ #include -#include +#include namespace raft { class handle_t; @@ -28,7 +28,7 @@ namespace ML { namespace kmeans { -using KMeansParams = raft::cluster::KMeansParams; +using KMeansParams = cuvs::cluster::kmeans::params; /** * @brief Compute k-means clustering and predicts cluster index for each sample diff --git a/cpp/include/cuml/cluster/kmeans_mg.hpp b/cpp/include/cuml/cluster/kmeans_mg.hpp index 722534e248..368d3c828c 100644 --- a/cpp/include/cuml/cluster/kmeans_mg.hpp +++ b/cpp/include/cuml/cluster/kmeans_mg.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2022, NVIDIA CORPORATION. + * Copyright (c) 2019-2024, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -48,7 +48,7 @@ namespace opg { * @param[out] n_iter Number of iterations run. */ -void fit(const raft::handle_t& handle, +void fit(const raft::resources& handle, const KMeansParams& params, const float* X, int n_samples, @@ -58,7 +58,7 @@ void fit(const raft::handle_t& handle, float& inertia, int& n_iter); -void fit(const raft::handle_t& handle, +void fit(const raft::resources& handle, const KMeansParams& params, const double* X, int n_samples, @@ -68,7 +68,7 @@ void fit(const raft::handle_t& handle, double& inertia, int& n_iter); -void fit(const raft::handle_t& handle, +void fit(const raft::resources& handle, const KMeansParams& params, const float* X, int64_t n_samples, @@ -78,7 +78,7 @@ void fit(const raft::handle_t& handle, float& inertia, int64_t& n_iter); -void fit(const raft::handle_t& handle, +void fit(const raft::resources& handle, const KMeansParams& params, const double* X, int64_t n_samples, diff --git a/cpp/include/cuml/neighbors/knn.hpp b/cpp/include/cuml/neighbors/knn.hpp index 7927ec63a6..43150cf976 100644 --- a/cpp/include/cuml/neighbors/knn.hpp +++ b/cpp/include/cuml/neighbors/knn.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2023, NVIDIA CORPORATION. + * Copyright (c) 2019-2024, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -17,8 +17,11 @@ #pragma once #include -#include #include +#include // MetricProcessor + +#include +#include namespace raft { class handle_t; @@ -46,6 +49,8 @@ namespace ML { * default * @param[in] metric_arg the value of `p` for Minkowski (l-p) distances. This * is ignored if the metric_type is not Minkowski. + * @param[in] translations translation ids for indices when index rows represent + * non-contiguous partitions */ void brute_force_knn(const raft::handle_t& handle, std::vector& input, @@ -59,7 +64,8 @@ void brute_force_knn(const raft::handle_t& handle, bool rowMajorIndex = false, bool rowMajorQuery = false, raft::distance::DistanceType metric = raft::distance::DistanceType::L2Expanded, - float metric_arg = 2.0f); + float metric_arg = 2.0f, + std::vector* translations = nullptr); void rbc_build_index(const raft::handle_t& handle, raft::spatial::knn::BallCoverIndex& index); @@ -71,6 +77,36 @@ void rbc_knn_query(const raft::handle_t& handle, uint32_t n_search_items, int64_t* out_inds, float* out_dists); + +struct knnIndex { + raft::distance::DistanceType metric; + float metricArg; + int nprobe; + std::unique_ptr> metric_processor; + + std::unique_ptr> ivf_flat; + std::unique_ptr> ivf_pq; + + int device; +}; + +struct knnIndexParam { + virtual ~knnIndexParam() {} +}; + +struct IVFParam : knnIndexParam { + int nlist; + int nprobe; +}; + +struct IVFFlatParam : IVFParam {}; + +struct IVFPQParam : IVFParam { + int M; + int n_bits; + bool usePrecomputedTables; +}; + /** * @brief Flat C++ API function to build an approximate nearest neighbors index * from an index array and a set of parameters. @@ -85,8 +121,8 @@ void rbc_knn_query(const raft::handle_t& handle, * @param[in] D the dimensionality of the index array */ void approx_knn_build_index(raft::handle_t& handle, - raft::spatial::knn::knnIndex* index, - raft::spatial::knn::knnIndexParam* params, + knnIndex* index, + knnIndexParam* params, raft::distance::DistanceType metric, float metricArg, float* index_array, @@ -109,7 +145,7 @@ void approx_knn_build_index(raft::handle_t& handle, void approx_knn_search(raft::handle_t& handle, float* distances, int64_t* indices, - raft::spatial::knn::knnIndex* index, + knnIndex* index, int k, float* query_array, int n); diff --git a/cpp/src/hdbscan/detail/soft_clustering.cuh b/cpp/src/hdbscan/detail/soft_clustering.cuh index 19f6e40754..5370ad2dfb 100644 --- a/cpp/src/hdbscan/detail/soft_clustering.cuh +++ b/cpp/src/hdbscan/detail/soft_clustering.cuh @@ -24,7 +24,6 @@ #include #include -#include #include #include #include @@ -43,6 +42,8 @@ #include #include +#include + #include #include #include @@ -88,45 +89,14 @@ void dist_membership_vector(const raft::handle_t& handle, value_idx samples_per_batch = min((value_idx)batch_size, (value_idx)n_queries - batch_offset); rmm::device_uvector dist(samples_per_batch * n_exemplars, stream); - // compute the distances using raft API - switch (metric) { - case raft::distance::DistanceType::L2SqrtExpanded: - raft::distance:: - distance( - handle, - query + batch_offset * n, - exemplars_dense.data(), - dist.data(), - samples_per_batch, - n_exemplars, - n, - true); - break; - case raft::distance::DistanceType::L1: - raft::distance::distance( - handle, - query + batch_offset * n, - exemplars_dense.data(), - dist.data(), - samples_per_batch, - n_exemplars, - n, - true); - break; - case raft::distance::DistanceType::CosineExpanded: - raft::distance:: - distance( - handle, - query + batch_offset * n, - exemplars_dense.data(), - dist.data(), - samples_per_batch, - n_exemplars, - n, - true); - break; - default: RAFT_EXPECTS(false, "Incorrect metric passed!"); - } + // compute the distances using the CUVS API + cuvs::distance::pairwise_distance( + handle, + raft::make_device_matrix_view( + query + batch_offset * n, samples_per_batch, n), + raft::make_device_matrix_view(exemplars_dense.data(), n_exemplars, n), + raft::make_device_matrix_view(dist.data(), samples_per_batch, n_exemplars), + static_cast(metric)); // compute the minimum distances to exemplars of each cluster value_idx n_elements = samples_per_batch * n_selected_clusters; diff --git a/cpp/src/hdbscan/runner.h b/cpp/src/hdbscan/runner.h index c79148eed2..2f3e554a20 100644 --- a/cpp/src/hdbscan/runner.h +++ b/cpp/src/hdbscan/runner.h @@ -24,8 +24,8 @@ #include #include -#include -#include +#include // build_dendrogram_host +#include // build_sorted_mst #include #include #include @@ -40,6 +40,8 @@ #include #include +#include + namespace ML { namespace HDBSCAN { @@ -174,16 +176,15 @@ void build_linkage(const raft::handle_t& handle, raft::sparse::COO mutual_reachability_coo(stream, (params.min_samples + 1) * m * 2); - detail::Reachability::mutual_reachability_graph(handle, - X, - (size_t)m, - (size_t)n, - metric, - params.min_samples + 1, - params.alpha, - mutual_reachability_indptr.data(), - core_dists, - mutual_reachability_coo); + cuvs::neighbors::reachability::mutual_reachability_graph( + handle, + raft::make_device_matrix_view(X, m, n), + params.min_samples + 1, + raft::make_device_vector_view(mutual_reachability_indptr.data(), m + 1), + raft::make_device_vector_view(core_dists, m), + mutual_reachability_coo, + static_cast(metric), + params.alpha); /** * Construct MST sorted by weights diff --git a/cpp/src/kmeans/kmeans_fit_predict.cu b/cpp/src/kmeans/kmeans_fit_predict.cu index f982e6b26a..8e37ea4534 100644 --- a/cpp/src/kmeans/kmeans_fit_predict.cu +++ b/cpp/src/kmeans/kmeans_fit_predict.cu @@ -14,17 +14,17 @@ * limitations under the License. */ -#include -#include #include +#include + namespace ML { namespace kmeans { // -------------------------- fit_predict --------------------------------// template void fit_predict_impl(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const value_t* X, idx_t n_samples, idx_t n_features, @@ -45,12 +45,12 @@ void fit_predict_impl(const raft::handle_t& handle, auto inertia_view = raft::make_host_scalar_view(&inertia); auto n_iter_view = raft::make_host_scalar_view(&n_iter); - raft::cluster::kmeans_fit_predict( + cuvs::cluster::kmeans::fit_predict( handle, params, X_view, sw, centroids_opt, rLabels, inertia_view, n_iter_view); } void fit_predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const float* X, int n_samples, int n_features, @@ -65,7 +65,7 @@ void fit_predict(const raft::handle_t& handle, } void fit_predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const double* X, int n_samples, int n_features, @@ -80,7 +80,7 @@ void fit_predict(const raft::handle_t& handle, } void fit_predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const float* X, int64_t n_samples, int64_t n_features, @@ -95,7 +95,7 @@ void fit_predict(const raft::handle_t& handle, } void fit_predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const double* X, int64_t n_samples, int64_t n_features, diff --git a/cpp/src/kmeans/kmeans_mg.cu b/cpp/src/kmeans/kmeans_mg.cu index 0d135ebf99..c6804cbcaa 100644 --- a/cpp/src/kmeans/kmeans_mg.cu +++ b/cpp/src/kmeans/kmeans_mg.cu @@ -14,20 +14,16 @@ * limitations under the License. */ -#include "kmeans_mg_impl.cuh" - #include -#include - namespace ML { namespace kmeans { namespace opg { // ----------------------------- fit ---------------------------------// -void fit(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, +void fit(const raft::resources& handle, + const cuvs::cluster::kmeans::params& params, const float* X, int n_samples, int n_features, @@ -36,14 +32,23 @@ void fit(const raft::handle_t& handle, float& inertia, int& n_iter) { - const raft::handle_t& h = handle; + std::optional> sample_weight_view; + if (sample_weight != NULL) { + sample_weight_view = raft::make_device_vector_view(sample_weight, n_samples); + } - raft::stream_syncer _(h); - impl::fit(h, params, X, n_samples, n_features, sample_weight, centroids, inertia, n_iter); + cuvs::cluster::kmeans::fit( + handle, + params, + raft::make_device_matrix_view(X, n_samples, n_features), + sample_weight_view, + raft::make_device_matrix_view(centroids, params.n_clusters, n_features), + raft::make_host_scalar_view(&inertia), + raft::make_host_scalar_view(&n_iter)); } -void fit(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, +void fit(const raft::resources& handle, + const cuvs::cluster::kmeans::params& params, const double* X, int n_samples, int n_features, @@ -52,13 +57,23 @@ void fit(const raft::handle_t& handle, double& inertia, int& n_iter) { - const raft::handle_t& h = handle; - raft::stream_syncer _(h); - impl::fit(h, params, X, n_samples, n_features, sample_weight, centroids, inertia, n_iter); + std::optional> sample_weight_view; + if (sample_weight != NULL) { + sample_weight_view = raft::make_device_vector_view(sample_weight, n_samples); + } + + cuvs::cluster::kmeans::fit( + handle, + params, + raft::make_device_matrix_view(X, n_samples, n_features), + sample_weight_view, + raft::make_device_matrix_view(centroids, params.n_clusters, n_features), + raft::make_host_scalar_view(&inertia), + raft::make_host_scalar_view(&n_iter)); } -void fit(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, +void fit(const raft::resources& handle, + const cuvs::cluster::kmeans::params& params, const float* X, int64_t n_samples, int64_t n_features, @@ -67,14 +82,24 @@ void fit(const raft::handle_t& handle, float& inertia, int64_t& n_iter) { - const raft::handle_t& h = handle; + std::optional> sample_weight_view; + if (sample_weight != NULL) { + sample_weight_view = + raft::make_device_vector_view(sample_weight, n_samples); + } - raft::stream_syncer _(h); - impl::fit(h, params, X, n_samples, n_features, sample_weight, centroids, inertia, n_iter); + cuvs::cluster::kmeans::fit( + handle, + params, + raft::make_device_matrix_view(X, n_samples, n_features), + sample_weight_view, + raft::make_device_matrix_view(centroids, params.n_clusters, n_features), + raft::make_host_scalar_view(&inertia), + raft::make_host_scalar_view(&n_iter)); } -void fit(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, +void fit(const raft::resources& handle, + const cuvs::cluster::kmeans::params& params, const double* X, int64_t n_samples, int64_t n_features, @@ -83,11 +108,21 @@ void fit(const raft::handle_t& handle, double& inertia, int64_t& n_iter) { - const raft::handle_t& h = handle; - raft::stream_syncer _(h); - impl::fit(h, params, X, n_samples, n_features, sample_weight, centroids, inertia, n_iter); -} + std::optional> sample_weight_view; + if (sample_weight != NULL) { + sample_weight_view = + raft::make_device_vector_view(sample_weight, n_samples); + } + cuvs::cluster::kmeans::fit( + handle, + params, + raft::make_device_matrix_view(X, n_samples, n_features), + sample_weight_view, + raft::make_device_matrix_view(centroids, params.n_clusters, n_features), + raft::make_host_scalar_view(&inertia), + raft::make_host_scalar_view(&n_iter)); +} }; // end namespace opg }; // end namespace kmeans }; // end namespace ML diff --git a/cpp/src/kmeans/kmeans_mg_impl.cuh b/cpp/src/kmeans/kmeans_mg_impl.cuh deleted file mode 100644 index 6f08130632..0000000000 --- a/cpp/src/kmeans/kmeans_mg_impl.cuh +++ /dev/null @@ -1,818 +0,0 @@ -/* - * Copyright (c) 2020-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once -#include - -#include -#include -#include -#include -#include -#include -#include - -#include -#include - -#include -#include -#include -#include -#include -#include - -#include - -#include - -namespace ML { - -#define CUML_LOG_KMEANS(handle, fmt, ...) \ - do { \ - bool isRoot = true; \ - if (handle.comms_initialized()) { \ - const auto& comm = handle.get_comms(); \ - const int my_rank = comm.get_rank(); \ - isRoot = my_rank == 0; \ - } \ - if (isRoot) { CUML_LOG_DEBUG(fmt, ##__VA_ARGS__); } \ - } while (0) - -namespace kmeans { -namespace opg { -namespace impl { - -#define KMEANS_COMM_ROOT 0 - -static raft::cluster::kmeans::KMeansParams default_params; - -// Selects 'n_clusters' samples randomly from X -template -void initRandom(const raft::handle_t& handle, - const raft::cluster::kmeans::KMeansParams& params, - raft::device_matrix_view X, - raft::device_matrix_view centroids) -{ - const auto& comm = handle.get_comms(); - cudaStream_t stream = handle.get_stream(); - auto n_local_samples = X.extent(0); - auto n_features = X.extent(1); - auto n_clusters = params.n_clusters; - - const int my_rank = comm.get_rank(); - const int n_ranks = comm.get_size(); - - std::vector nCentroidsSampledByRank(n_ranks, 0); - std::vector nCentroidsElementsToReceiveFromRank(n_ranks, 0); - - const int nranks_reqd = std::min(n_ranks, n_clusters); - ASSERT(KMEANS_COMM_ROOT < nranks_reqd, "KMEANS_COMM_ROOT must be in [0, %d)\n", nranks_reqd); - - for (int rank = 0; rank < nranks_reqd; ++rank) { - int nCentroidsSampledInRank = n_clusters / nranks_reqd; - if (rank == KMEANS_COMM_ROOT) { - nCentroidsSampledInRank += n_clusters - nCentroidsSampledInRank * nranks_reqd; - } - nCentroidsSampledByRank[rank] = nCentroidsSampledInRank; - nCentroidsElementsToReceiveFromRank[rank] = nCentroidsSampledInRank * n_features; - } - - auto nCentroidsSampledInRank = nCentroidsSampledByRank[my_rank]; - ASSERT((IndexT)nCentroidsSampledInRank <= (IndexT)n_local_samples, - "# random samples requested from rank-%d is larger than the available " - "samples at the rank (requested is %lu, available is %lu)", - my_rank, - (size_t)nCentroidsSampledInRank, - (size_t)n_local_samples); - - auto centroidsSampledInRank = - raft::make_device_matrix(handle, nCentroidsSampledInRank, n_features); - - raft::cluster::kmeans::shuffle_and_gather( - handle, X, centroidsSampledInRank.view(), nCentroidsSampledInRank, params.rng_state.seed); - - std::vector displs(n_ranks); - thrust::exclusive_scan(thrust::host, - nCentroidsElementsToReceiveFromRank.begin(), - nCentroidsElementsToReceiveFromRank.end(), - displs.begin()); - - // gather centroids from all ranks - comm.allgatherv(centroidsSampledInRank.data_handle(), // sendbuff - centroids.data_handle(), // recvbuff - nCentroidsElementsToReceiveFromRank.data(), // recvcount - displs.data(), - stream); -} - -/* - * @brief Selects 'n_clusters' samples from X using scalable kmeans++ algorithm - * Scalable kmeans++ pseudocode - * 1: C = sample a point uniformly at random from X - * 2: psi = phi_X (C) - * 3: for O( log(psi) ) times do - * 4: C' = sample each point x in X independently with probability - * p_x = l * ( d^2(x, C) / phi_X (C) ) - * 5: C = C U C' - * 6: end for - * 7: For x in C, set w_x to be the number of points in X closer to x than any - * other point in C - * 8: Recluster the weighted points in C into k clusters - */ -template -void initKMeansPlusPlus(const raft::handle_t& handle, - const raft::cluster::kmeans::KMeansParams& params, - raft::device_matrix_view X, - raft::device_matrix_view centroidsRawData, - rmm::device_uvector& workspace) -{ - const auto& comm = handle.get_comms(); - cudaStream_t stream = handle.get_stream(); - const int my_rank = comm.get_rank(); - const int n_rank = comm.get_size(); - - auto n_samples = X.extent(0); - auto n_features = X.extent(1); - auto n_clusters = params.n_clusters; - auto metric = params.metric; - - raft::random::RngState rng(params.rng_state.seed, raft::random::GeneratorType::GenPhilox); - - // <<<< Step-1 >>> : C <- sample a point uniformly at random from X - // 1.1 - Select a rank r' at random from the available n_rank ranks with a - // probability of 1/n_rank [Note - with same seed all rank selects - // the same r' which avoids a call to comm] - // 1.2 - Rank r' samples a point uniformly at random from the local dataset - // X which will be used as the initial centroid for kmeans++ - // 1.3 - Communicate the initial centroid chosen by rank-r' to all other - // ranks - std::mt19937 gen(params.rng_state.seed); - std::uniform_int_distribution<> dis(0, n_rank - 1); - int rp = dis(gen); - - // buffer to flag the sample that is chosen as initial centroids - std::vector h_isSampleCentroid(n_samples); - std::fill(h_isSampleCentroid.begin(), h_isSampleCentroid.end(), 0); - - auto initialCentroid = raft::make_device_matrix(handle, 1, n_features); - CUML_LOG_KMEANS( - handle, "@Rank-%d : KMeans|| : initial centroid is sampled at rank-%d\n", my_rank, rp); - - // 1.2 - Rank r' samples a point uniformly at random from the local dataset - // X which will be used as the initial centroid for kmeans++ - if (my_rank == rp) { - std::mt19937 gen(params.rng_state.seed); - std::uniform_int_distribution<> dis(0, n_samples - 1); - - int cIdx = dis(gen); - auto centroidsView = raft::make_device_matrix_view( - X.data_handle() + cIdx * n_features, 1, n_features); - - raft::copy( - initialCentroid.data_handle(), centroidsView.data_handle(), centroidsView.size(), stream); - - h_isSampleCentroid[cIdx] = 1; - } - - // 1.3 - Communicate the initial centroid chosen by rank-r' to all other ranks - comm.bcast(initialCentroid.data_handle(), initialCentroid.size(), rp, stream); - - // device buffer to flag the sample that is chosen as initial centroid - auto isSampleCentroid = raft::make_device_vector(handle, n_samples); - - raft::copy( - isSampleCentroid.data_handle(), h_isSampleCentroid.data(), isSampleCentroid.size(), stream); - - rmm::device_uvector centroidsBuf(0, stream); - - // reset buffer to store the chosen centroid - centroidsBuf.resize(initialCentroid.size(), stream); - raft::copy(centroidsBuf.begin(), initialCentroid.data_handle(), initialCentroid.size(), stream); - - auto potentialCentroids = raft::make_device_matrix_view( - centroidsBuf.data(), initialCentroid.extent(0), initialCentroid.extent(1)); - // <<< End of Step-1 >>> - - rmm::device_uvector L2NormBuf_OR_DistBuf(0, stream); - - // L2 norm of X: ||x||^2 - auto L2NormX = raft::make_device_vector(handle, n_samples); - if (metric == raft::distance::DistanceType::L2Expanded || - metric == raft::distance::DistanceType::L2SqrtExpanded) { - raft::linalg::rowNorm(L2NormX.data_handle(), - X.data_handle(), - X.extent(1), - X.extent(0), - raft::linalg::L2Norm, - true, - stream); - } - - auto minClusterDistance = raft::make_device_vector(handle, n_samples); - auto uniformRands = raft::make_device_vector(handle, n_samples); - - // <<< Step-2 >>>: psi <- phi_X (C) - auto clusterCost = raft::make_device_scalar(handle, 0); - - raft::cluster::kmeans::min_cluster_distance(handle, - X, - potentialCentroids, - minClusterDistance.view(), - L2NormX.view(), - L2NormBuf_OR_DistBuf, - params.metric, - params.batch_samples, - params.batch_centroids, - workspace); - - // compute partial cluster cost from the samples in rank - raft::cluster::kmeans::cluster_cost( - handle, - minClusterDistance.view(), - workspace, - clusterCost.view(), - cuda::proclaim_return_type( - [] __device__(const DataT& a, const DataT& b) { return a + b; })); - - // compute total cluster cost by accumulating the partial cost from all the - // ranks - comm.allreduce( - clusterCost.data_handle(), clusterCost.data_handle(), 1, raft::comms::op_t::SUM, stream); - - DataT psi = 0; - raft::copy(&psi, clusterCost.data_handle(), 1, stream); - - // <<< End of Step-2 >>> - - ASSERT(comm.sync_stream(stream) == raft::comms::status_t::SUCCESS, - "An error occurred in the distributed operation. This can result from " - "a failed rank"); - - // Scalable kmeans++ paper claims 8 rounds is sufficient - int niter = std::min(8, (int)ceil(log(psi))); - CUML_LOG_KMEANS(handle, - "@Rank-%d:KMeans|| :phi - %f, max # of iterations for kmeans++ loop - " - "%d\n", - my_rank, - psi, - niter); - - // <<<< Step-3 >>> : for O( log(psi) ) times do - for (int iter = 0; iter < niter; ++iter) { - CUML_LOG_KMEANS(handle, - "@Rank-%d:KMeans|| - Iteration %d: # potential centroids sampled - " - "%d\n", - my_rank, - iter, - potentialCentroids.extent(0)); - - raft::cluster::kmeans::min_cluster_distance(handle, - X, - potentialCentroids, - minClusterDistance.view(), - L2NormX.view(), - L2NormBuf_OR_DistBuf, - params.metric, - params.batch_samples, - params.batch_centroids, - workspace); - - raft::cluster::kmeans::cluster_cost( - handle, - minClusterDistance.view(), - workspace, - clusterCost.view(), - cuda::proclaim_return_type( - [] __device__(const DataT& a, const DataT& b) { return a + b; })); - comm.allreduce( - clusterCost.data_handle(), clusterCost.data_handle(), 1, raft::comms::op_t::SUM, stream); - raft::copy(&psi, clusterCost.data_handle(), 1, stream); - ASSERT(comm.sync_stream(stream) == raft::comms::status_t::SUCCESS, - "An error occurred in the distributed operation. This can result " - "from a failed rank"); - - // <<<< Step-4 >>> : Sample each point x in X independently and identify new - // potentialCentroids - raft::random::uniform( - handle, rng, uniformRands.data_handle(), uniformRands.extent(0), (DataT)0, (DataT)1); - raft::cluster::kmeans::SamplingOp select_op(psi, - params.oversampling_factor, - n_clusters, - uniformRands.data_handle(), - isSampleCentroid.data_handle()); - - rmm::device_uvector inRankCp(0, stream); - raft::cluster::kmeans::sample_centroids(handle, - X, - minClusterDistance.view(), - isSampleCentroid.view(), - select_op, - inRankCp, - workspace); - /// <<<< End of Step-4 >>>> - - int* nPtsSampledByRank; - RAFT_CUDA_TRY(cudaMallocHost(&nPtsSampledByRank, n_rank * sizeof(int))); - - /// <<<< Step-5 >>> : C = C U C' - // append the data in Cp from all ranks to the buffer holding the - // potentialCentroids - // RAFT_CUDA_TRY(cudaMemsetAsync(nPtsSampledByRank, 0, n_rank * sizeof(int), stream)); - std::fill(nPtsSampledByRank, nPtsSampledByRank + n_rank, 0); - nPtsSampledByRank[my_rank] = inRankCp.size() / n_features; - comm.allgather(&(nPtsSampledByRank[my_rank]), nPtsSampledByRank, 1, stream); - ASSERT(comm.sync_stream(stream) == raft::comms::status_t::SUCCESS, - "An error occurred in the distributed operation. This can result " - "from a failed rank"); - - auto nPtsSampled = - thrust::reduce(thrust::host, nPtsSampledByRank, nPtsSampledByRank + n_rank, 0); - - // gather centroids from all ranks - std::vector sizes(n_rank); - thrust::transform( - thrust::host, nPtsSampledByRank, nPtsSampledByRank + n_rank, sizes.begin(), [&](int val) { - return val * n_features; - }); - - RAFT_CUDA_TRY_NO_THROW(cudaFreeHost(nPtsSampledByRank)); - - std::vector displs(n_rank); - thrust::exclusive_scan(thrust::host, sizes.begin(), sizes.end(), displs.begin()); - - centroidsBuf.resize(centroidsBuf.size() + nPtsSampled * n_features, stream); - comm.allgatherv(inRankCp.data(), - centroidsBuf.end() - nPtsSampled * n_features, - sizes.data(), - displs.data(), - stream); - - auto tot_centroids = potentialCentroids.extent(0) + nPtsSampled; - potentialCentroids = - raft::make_device_matrix_view(centroidsBuf.data(), tot_centroids, n_features); - /// <<<< End of Step-5 >>> - } /// <<<< Step-6 >>> - - CUML_LOG_KMEANS(handle, - "@Rank-%d:KMeans||: # potential centroids sampled - %d\n", - my_rank, - potentialCentroids.extent(0)); - - if ((IndexT)potentialCentroids.extent(0) > (IndexT)n_clusters) { - // <<< Step-7 >>>: For x in C, set w_x to be the number of pts closest to X - // temporary buffer to store the sample count per cluster, destructor - // releases the resource - - auto weight = raft::make_device_vector(handle, potentialCentroids.extent(0)); - - raft::cluster::kmeans::count_samples_in_cluster( - handle, params, X, L2NormX.view(), potentialCentroids, workspace, weight.view()); - - // merge the local histogram from all ranks - comm.allreduce(weight.data_handle(), // sendbuff - weight.data_handle(), // recvbuff - weight.size(), // count - raft::comms::op_t::SUM, - stream); - - // <<< end of Step-7 >>> - - // Step-8: Recluster the weighted points in C into k clusters - // Note - reclustering step is duplicated across all ranks and with the same - // seed they should generate the same potentialCentroids - auto const_centroids = raft::make_device_matrix_view( - potentialCentroids.data_handle(), potentialCentroids.extent(0), potentialCentroids.extent(1)); - raft::cluster::kmeans::init_plus_plus( - handle, params, const_centroids, centroidsRawData, workspace); - - auto inertia = raft::make_host_scalar(0); - auto n_iter = raft::make_host_scalar(0); - auto weight_view = - raft::make_device_vector_view(weight.data_handle(), weight.extent(0)); - raft::cluster::kmeans::KMeansParams params_copy = params; - params_copy.rng_state = default_params.rng_state; - - raft::cluster::kmeans::fit_main(handle, - params_copy, - const_centroids, - weight_view, - centroidsRawData, - inertia.view(), - n_iter.view(), - workspace); - - } else if ((IndexT)potentialCentroids.extent(0) < (IndexT)n_clusters) { - // supplement with random - auto n_random_clusters = n_clusters - potentialCentroids.extent(0); - CUML_LOG_KMEANS(handle, - "[Warning!] KMeans||: found fewer than %d centroids during " - "initialization (found %d centroids, remaining %d centroids will be " - "chosen randomly from input samples)\n", - n_clusters, - potentialCentroids.extent(0), - n_random_clusters); - - // generate `n_random_clusters` centroids - raft::cluster::kmeans::KMeansParams rand_params = params; - rand_params.rng_state = default_params.rng_state; - rand_params.init = raft::cluster::kmeans::KMeansParams::InitMethod::Random; - rand_params.n_clusters = n_random_clusters; - initRandom(handle, rand_params, X, centroidsRawData); - - // copy centroids generated during kmeans|| iteration to the buffer - raft::copy(centroidsRawData.data_handle() + n_random_clusters * n_features, - potentialCentroids.data_handle(), - potentialCentroids.size(), - stream); - - } else { - // found the required n_clusters - raft::copy(centroidsRawData.data_handle(), - potentialCentroids.data_handle(), - potentialCentroids.size(), - stream); - } -} - -template -void checkWeights(const raft::handle_t& handle, - rmm::device_uvector& workspace, - raft::device_vector_view weight) -{ - cudaStream_t stream = handle.get_stream(); - rmm::device_scalar wt_aggr(stream); - - const auto& comm = handle.get_comms(); - - auto n_samples = weight.extent(0); - size_t temp_storage_bytes = 0; - RAFT_CUDA_TRY(cub::DeviceReduce::Sum( - nullptr, temp_storage_bytes, weight.data_handle(), wt_aggr.data(), n_samples, stream)); - - workspace.resize(temp_storage_bytes, stream); - - RAFT_CUDA_TRY(cub::DeviceReduce::Sum( - workspace.data(), temp_storage_bytes, weight.data_handle(), wt_aggr.data(), n_samples, stream)); - - comm.allreduce(wt_aggr.data(), // sendbuff - wt_aggr.data(), // recvbuff - 1, // count - raft::comms::op_t::SUM, - stream); - DataT wt_sum = wt_aggr.value(stream); - handle.sync_stream(stream); - - if (wt_sum != n_samples) { - CUML_LOG_KMEANS(handle, - "[Warning!] KMeans: normalizing the user provided sample weights to " - "sum up to %d samples", - n_samples); - - DataT scale = n_samples / wt_sum; - raft::linalg::unaryOp( - weight.data_handle(), - weight.data_handle(), - weight.size(), - cuda::proclaim_return_type([=] __device__(const DataT& wt) { return wt * scale; }), - stream); - } -} - -template -void fit(const raft::handle_t& handle, - const raft::cluster::kmeans::KMeansParams& params, - raft::device_matrix_view X, - raft::device_vector_view weight, - raft::device_matrix_view centroids, - raft::host_scalar_view inertia, - raft::host_scalar_view n_iter, - rmm::device_uvector& workspace) -{ - const auto& comm = handle.get_comms(); - cudaStream_t stream = handle.get_stream(); - auto n_samples = X.extent(0); - auto n_features = X.extent(1); - auto n_clusters = params.n_clusters; - auto metric = params.metric; - - // stores (key, value) pair corresponding to each sample where - // - key is the index of nearest cluster - // - value is the distance to the nearest cluster - auto minClusterAndDistance = - raft::make_device_vector, IndexT>(handle, n_samples); - - // temporary buffer to store L2 norm of centroids or distance matrix, - // destructor releases the resource - rmm::device_uvector L2NormBuf_OR_DistBuf(0, stream); - - // temporary buffer to store intermediate centroids, destructor releases the - // resource - auto newCentroids = raft::make_device_matrix(handle, n_clusters, n_features); - - // temporary buffer to store the weights per cluster, destructor releases - // the resource - auto wtInCluster = raft::make_device_vector(handle, n_clusters); - - // L2 norm of X: ||x||^2 - auto L2NormX = raft::make_device_vector(handle, n_samples); - if (metric == raft::distance::DistanceType::L2Expanded || - metric == raft::distance::DistanceType::L2SqrtExpanded) { - raft::linalg::rowNorm(L2NormX.data_handle(), - X.data_handle(), - X.extent(1), - X.extent(0), - raft::linalg::L2Norm, - true, - stream); - } - - DataT priorClusteringCost = 0; - for (n_iter[0] = 1; n_iter[0] <= params.max_iter; ++n_iter[0]) { - CUML_LOG_KMEANS(handle, - "KMeans.fit: Iteration-%d: fitting the model using the initialize " - "cluster centers\n", - n_iter[0]); - - auto const_centroids = raft::make_device_matrix_view( - centroids.data_handle(), centroids.extent(0), centroids.extent(1)); - // computes minClusterAndDistance[0:n_samples) where - // minClusterAndDistance[i] is a pair where - // 'key' is index to an sample in 'centroids' (index of the nearest - // centroid) and 'value' is the distance between the sample 'X[i]' and the - // 'centroid[key]' - raft::cluster::kmeans::min_cluster_and_distance(handle, - X, - const_centroids, - minClusterAndDistance.view(), - L2NormX.view(), - L2NormBuf_OR_DistBuf, - params.metric, - params.batch_samples, - params.batch_centroids, - workspace); - - // Using TransformInputIteratorT to dereference an array of - // cub::KeyValuePair and converting them to just return the Key to be used - // in reduce_rows_by_key prims - raft::cluster::kmeans::KeyValueIndexOp conversion_op; - cub::TransformInputIterator, - raft::KeyValuePair*> - itr(minClusterAndDistance.data_handle(), conversion_op); - - workspace.resize(n_samples, stream); - - // Calculates weighted sum of all the samples assigned to cluster-i and - // store the result in newCentroids[i] - raft::linalg::reduce_rows_by_key((DataT*)X.data_handle(), - X.extent(1), - itr, - weight.data_handle(), - workspace.data(), - X.extent(0), - X.extent(1), - static_cast(n_clusters), - newCentroids.data_handle(), - stream); - - // Reduce weights by key to compute weight in each cluster - raft::linalg::reduce_cols_by_key(weight.data_handle(), - itr, - wtInCluster.data_handle(), - (IndexT)1, - (IndexT)weight.extent(0), - (IndexT)n_clusters, - stream); - - // merge the local histogram from all ranks - comm.allreduce(wtInCluster.data_handle(), // sendbuff - wtInCluster.data_handle(), // recvbuff - wtInCluster.size(), // count - raft::comms::op_t::SUM, - stream); - - // reduces newCentroids from all ranks - comm.allreduce(newCentroids.data_handle(), // sendbuff - newCentroids.data_handle(), // recvbuff - newCentroids.size(), // count - raft::comms::op_t::SUM, - stream); - - // Computes newCentroids[i] = newCentroids[i]/wtInCluster[i] where - // newCentroids[n_clusters x n_features] - 2D array, newCentroids[i] has - // sum of all the samples assigned to cluster-i - // wtInCluster[n_clusters] - 1D array, wtInCluster[i] contains # of - // samples in cluster-i. - // Note - when wtInCluster[i] is 0, newCentroid[i] is reset to 0 - - raft::linalg::matrixVectorOp( - newCentroids.data_handle(), - newCentroids.data_handle(), - wtInCluster.data_handle(), - newCentroids.extent(1), - newCentroids.extent(0), - true, - false, - cuda::proclaim_return_type([=] __device__(DataT mat, DataT vec) { - if (vec == 0) - return DataT(0); - else - return mat / vec; - }), - stream); - - // copy the centroids[i] to newCentroids[i] when wtInCluster[i] is 0 - cub::ArgIndexInputIterator itr_wt(wtInCluster.data_handle()); - raft::matrix::gather_if( - centroids.data_handle(), - centroids.extent(1), - centroids.extent(0), - itr_wt, - itr_wt, - wtInCluster.extent(0), - newCentroids.data_handle(), - cuda::proclaim_return_type( - [=] __device__(raft::KeyValuePair map) { // predicate - // copy when the # of samples in the cluster is 0 - if (map.value == 0) - return true; - else - return false; - }), - cuda::proclaim_return_type( - [=] __device__(raft::KeyValuePair map) { // map - return map.key; - }), - stream); - - // compute the squared norm between the newCentroids and the original - // centroids, destructor releases the resource - auto sqrdNorm = raft::make_device_scalar(handle, 1); - raft::linalg::mapThenSumReduce( - sqrdNorm.data_handle(), - newCentroids.size(), - cuda::proclaim_return_type([=] __device__(const DataT a, const DataT b) { - DataT diff = a - b; - return diff * diff; - }), - stream, - centroids.data_handle(), - newCentroids.data_handle()); - - DataT sqrdNormError = 0; - raft::copy(&sqrdNormError, sqrdNorm.data_handle(), sqrdNorm.size(), stream); - - raft::copy(centroids.data_handle(), newCentroids.data_handle(), newCentroids.size(), stream); - - bool done = false; - if (params.inertia_check) { - rmm::device_scalar> clusterCostD(stream); - - // calculate cluster cost phi_x(C) - raft::cluster::kmeans::cluster_cost( - handle, - minClusterAndDistance.view(), - workspace, - raft::make_device_scalar_view(clusterCostD.data()), - cuda::proclaim_return_type>( - [] __device__(const raft::KeyValuePair& a, - const raft::KeyValuePair& b) { - raft::KeyValuePair res; - res.key = 0; - res.value = a.value + b.value; - return res; - })); - - // Cluster cost phi_x(C) from all ranks - comm.allreduce(&(clusterCostD.data()->value), - &(clusterCostD.data()->value), - 1, - raft::comms::op_t::SUM, - stream); - - DataT curClusteringCost = 0; - raft::copy(&curClusteringCost, &(clusterCostD.data()->value), 1, stream); - - ASSERT(comm.sync_stream(stream) == raft::comms::status_t::SUCCESS, - "An error occurred in the distributed operation. This can result " - "from a failed rank"); - ASSERT(curClusteringCost != (DataT)0.0, - "Too few points and centroids being found is getting 0 cost from " - "centers\n"); - - if (n_iter[0] > 0) { - DataT delta = curClusteringCost / priorClusteringCost; - if (delta > 1 - params.tol) done = true; - } - priorClusteringCost = curClusteringCost; - } - - handle.sync_stream(stream); - if (sqrdNormError < params.tol) done = true; - - if (done) { - CUML_LOG_KMEANS( - handle, "Threshold triggered after %d iterations. Terminating early.\n", n_iter[0]); - break; - } - } -} - -template -void fit(const raft::handle_t& handle, - const raft::cluster::kmeans::KMeansParams& params, - const DataT* X, - const IndexT n_local_samples, - const IndexT n_features, - const DataT* sample_weight, - DataT* centroids, - DataT& inertia, - IndexT& n_iter) -{ - cudaStream_t stream = handle.get_stream(); - - ASSERT(n_local_samples > 0, "# of samples must be > 0"); - ASSERT(params.oversampling_factor > 0, - "oversampling factor must be > 0 (requested %d)", - (int)params.oversampling_factor); - ASSERT(is_device_or_managed_type(X), "input data must be device accessible"); - - auto n_clusters = params.n_clusters; - auto data = raft::make_device_matrix_view(X, n_local_samples, n_features); - auto weight = raft::make_device_vector(handle, n_local_samples); - if (sample_weight != nullptr) { - raft::copy(weight.data_handle(), sample_weight, n_local_samples, stream); - } else { - thrust::fill( - handle.get_thrust_policy(), weight.data_handle(), weight.data_handle() + weight.size(), 1); - } - - // underlying expandable storage that holds centroids data - auto centroidsRawData = raft::make_device_matrix(handle, n_clusters, n_features); - - // Device-accessible allocation of expandable storage used as temporary buffers - rmm::device_uvector workspace(0, stream); - - // check if weights sum up to n_samples - checkWeights(handle, workspace, weight.view()); - - if (params.init == raft::cluster::kmeans::KMeansParams::InitMethod::Random) { - // initializing with random samples from input dataset - CUML_LOG_KMEANS(handle, - "KMeans.fit: initialize cluster centers by randomly choosing from the " - "input data.\n"); - initRandom(handle, params, data, centroidsRawData.view()); - } else if (params.init == raft::cluster::kmeans::KMeansParams::InitMethod::KMeansPlusPlus) { - // default method to initialize is kmeans++ - CUML_LOG_KMEANS(handle, "KMeans.fit: initialize cluster centers using k-means++ algorithm.\n"); - initKMeansPlusPlus(handle, params, data, centroidsRawData.view(), workspace); - } else if (params.init == raft::cluster::kmeans::KMeansParams::InitMethod::Array) { - CUML_LOG_KMEANS(handle, - "KMeans.fit: initialize cluster centers from the ndarray array input " - "passed to init argument.\n"); - - ASSERT(centroids != nullptr, - "centroids array is null (require a valid array of centroids for " - "the requested initialization method)"); - - raft::copy(centroidsRawData.data_handle(), centroids, params.n_clusters * n_features, stream); - } else { - THROW("unknown initialization method to select initial centers"); - } - auto inertiaView = raft::make_host_scalar_view(&inertia); - auto n_iterView = raft::make_host_scalar_view(&n_iter); - - fit(handle, - params, - data, - weight.view(), - centroidsRawData.view(), - inertiaView, - n_iterView, - workspace); - - raft::copy(centroids, centroidsRawData.data_handle(), params.n_clusters * n_features, stream); - - CUML_LOG_KMEANS(handle, - "KMeans.fit: async call returned (fit could still be running on the " - "device)\n"); -} - -}; // end namespace impl -}; // end namespace opg -}; // end namespace kmeans -}; // end namespace ML diff --git a/cpp/src/kmeans/kmeans_predict.cu b/cpp/src/kmeans/kmeans_predict.cu index c0e79757f5..b65af8c21a 100644 --- a/cpp/src/kmeans/kmeans_predict.cu +++ b/cpp/src/kmeans/kmeans_predict.cu @@ -14,10 +14,10 @@ * limitations under the License. */ -#include -#include #include +#include + namespace ML { namespace kmeans { @@ -25,7 +25,7 @@ namespace kmeans { template void predict_impl(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const value_t* centroids, const value_t* X, idx_t n_samples, @@ -45,12 +45,12 @@ void predict_impl(const raft::handle_t& handle, auto rLabels = raft::make_device_vector_view(labels, n_samples); auto inertia_view = raft::make_host_scalar_view(&inertia); - raft::cluster::kmeans_predict( + cuvs::cluster::kmeans::predict( handle, params, X_view, sw, centroids_view, rLabels, normalize_weights, inertia_view); } void predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const float* centroids, const float* X, int n_samples, @@ -73,7 +73,7 @@ void predict(const raft::handle_t& handle, } void predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const double* centroids, const double* X, int n_samples, @@ -96,7 +96,7 @@ void predict(const raft::handle_t& handle, } void predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const float* centroids, const float* X, int64_t n_samples, @@ -119,7 +119,7 @@ void predict(const raft::handle_t& handle, } void predict(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const double* centroids, const double* X, int64_t n_samples, diff --git a/cpp/src/kmeans/kmeans_transform.cu b/cpp/src/kmeans/kmeans_transform.cu index 2cef14f787..93a9851cf9 100644 --- a/cpp/src/kmeans/kmeans_transform.cu +++ b/cpp/src/kmeans/kmeans_transform.cu @@ -14,17 +14,17 @@ * limitations under the License. */ -#include -#include #include +#include + namespace ML { namespace kmeans { // ----------------------------- transform ---------------------------------// template void transform_impl(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const value_t* centroids, const value_t* X, idx_t n_samples, @@ -36,11 +36,11 @@ void transform_impl(const raft::handle_t& handle, raft::make_device_matrix_view(centroids, params.n_clusters, n_features); auto rX_new = raft::make_device_matrix_view(X_new, n_samples, n_features); - raft::cluster::kmeans::transform(handle, params, X_view, centroids_view, rX_new); + cuvs::cluster::kmeans::transform(handle, params, X_view, centroids_view, rX_new); } void transform(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const float* centroids, const float* X, int n_samples, @@ -51,7 +51,7 @@ void transform(const raft::handle_t& handle, } void transform(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const double* centroids, const double* X, int n_samples, @@ -62,7 +62,7 @@ void transform(const raft::handle_t& handle, } void transform(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const float* centroids, const float* X, int64_t n_samples, @@ -73,7 +73,7 @@ void transform(const raft::handle_t& handle, } void transform(const raft::handle_t& handle, - const raft::cluster::KMeansParams& params, + const cuvs::cluster::kmeans::params& params, const double* centroids, const double* X, int64_t n_samples, diff --git a/cpp/src/knn/knn.cu b/cpp/src/knn/knn.cu index 3d5329abc6..c08cd47de2 100644 --- a/cpp/src/knn/knn.cu +++ b/cpp/src/knn/knn.cu @@ -17,6 +17,7 @@ #include #include +#include #include #include #include @@ -28,6 +29,7 @@ #include +#include #include #include @@ -36,7 +38,6 @@ #include namespace ML { - void brute_force_knn(const raft::handle_t& handle, std::vector& input, std::vector& sizes, @@ -49,24 +50,108 @@ void brute_force_knn(const raft::handle_t& handle, bool rowMajorIndex, bool rowMajorQuery, raft::distance::DistanceType metric, - float metric_arg) + float metric_arg, + std::vector* translations) { ASSERT(input.size() == sizes.size(), "input and sizes vectors must be the same size"); - raft::spatial::knn::brute_force_knn(handle, - input, - sizes, - D, - search_items, - n, - res_I, - res_D, - k, - rowMajorIndex, - rowMajorQuery, - nullptr, - metric, - metric_arg); + // The cuvs api doesn't support having multiple input values to search against. + auto userStream = raft::resource::get_cuda_stream(handle); + + ASSERT(input.size() == sizes.size(), "input and sizes vectors should be the same size"); + + std::vector* id_ranges; + if (translations == nullptr) { + // If we don't have explicit translations + // for offsets of the indices, build them + // from the local partitions + id_ranges = new std::vector(); + int64_t total_n = 0; + for (size_t i = 0; i < input.size(); i++) { + id_ranges->push_back(total_n); + total_n += sizes[i]; + } + } else { + // otherwise, use the given translations + id_ranges = translations; + } + + rmm::device_uvector trans(id_ranges->size(), userStream); + raft::update_device(trans.data(), id_ranges->data(), id_ranges->size(), userStream); + + rmm::device_uvector all_D(0, userStream); + rmm::device_uvector all_I(0, userStream); + + float* out_D = res_D; + int64_t* out_I = res_I; + + if (input.size() > 1) { + all_D.resize(input.size() * k * n, userStream); + all_I.resize(input.size() * k * n, userStream); + + out_D = all_D.data(); + out_I = all_I.data(); + } + + // Make other streams from pool wait on main stream + raft::resource::wait_stream_pool_on_stream(handle); + + for (size_t i = 0; i < input.size(); i++) { + float* out_d_ptr = out_D + (i * k * n); + int64_t* out_i_ptr = out_I + (i * k * n); + + auto stream = raft::resource::get_next_usable_stream(handle, i); + auto current_handle = raft::device_resources(stream); + + // build the brute_force index (precalculates norms etc) + std::optional> idx; + if (rowMajorIndex) { + idx = cuvs::neighbors::brute_force::build( + current_handle, + raft::make_device_matrix_view(input[i], sizes[i], D), + static_cast(metric), + metric_arg); + + } else { + idx = cuvs::neighbors::brute_force::build( + current_handle, + raft::make_device_matrix_view(input[i], sizes[i], D), + static_cast(metric), + metric_arg); + } + + // query the index + if (rowMajorQuery) { + cuvs::neighbors::brute_force::search( + current_handle, + *idx, + raft::make_device_matrix_view(search_items, n, D), + raft::make_device_matrix_view(out_i_ptr, n, k), + raft::make_device_matrix_view(out_d_ptr, n, k)); + } else { + cuvs::neighbors::brute_force::search( + current_handle, + *idx, + raft::make_device_matrix_view(search_items, n, D), + raft::make_device_matrix_view(out_i_ptr, n, k), + raft::make_device_matrix_view(out_d_ptr, n, k)); + } + } + + // Sync internal streams if used. We don't need to + // sync the user stream because we'll already have + // fully serial execution. + raft::resource::sync_stream_pool(handle); + + if (input.size() > 1 || translations != nullptr) { + // This is necessary for proper index translations. If there are + // no translations or partitions to combine, it can be skipped. + // TODO: sort out where this knn_merge_parts should live + raft::spatial::knn::knn_merge_parts( + out_D, out_I, res_D, res_I, n, input.size(), k, userStream, trans.data()); + } + + if (translations == nullptr) delete id_ranges; } void rbc_build_index(const raft::handle_t& handle, @@ -83,32 +168,119 @@ void rbc_knn_query(const raft::handle_t& handle, int64_t* out_inds, float* out_dists) { + // TODO: we're using this from raft in header only mode, decide if we should split out to a + // separate instantiation here raft::spatial::knn::rbc_knn_query( handle, index, k, search_items, n_search_items, out_inds, out_dists); } void approx_knn_build_index(raft::handle_t& handle, - raft::spatial::knn::knnIndex* index, - raft::spatial::knn::knnIndexParam* params, + knnIndex* index, + knnIndexParam* params, raft::distance::DistanceType metric, float metricArg, float* index_array, int n, int D) { - raft::spatial::knn::approx_knn_build_index( - handle, index, params, metric, metricArg, index_array, n, D); + index->metric = metric; + index->metricArg = metricArg; + + auto ivf_ft_pams = dynamic_cast(params); + auto ivf_pq_pams = dynamic_cast(params); + + index->metric_processor = raft::spatial::knn::create_processor( + metric, n, D, 0, false, raft::resource::get_cuda_stream(handle)); + // For cosine/correlation distance, the metric processor translates distance + // to inner product via pre/post processing - pass the translated metric to + // ANN index + if (metric == raft::distance::DistanceType::CosineExpanded || + metric == raft::distance::DistanceType::CorrelationExpanded) { + metric = index->metric = raft::distance::DistanceType::InnerProduct; + } + index->metric_processor->preprocess(index_array); + auto index_view = raft::make_device_matrix_view(index_array, n, D); + + if (ivf_ft_pams) { + index->nprobe = ivf_ft_pams->nprobe; + cuvs::neighbors::ivf_flat::index_params params; + params.metric = static_cast(metric); + params.metric_arg = metricArg; + params.n_lists = ivf_ft_pams->nlist; + + index->ivf_flat = std::make_unique>( + cuvs::neighbors::ivf_flat::build(handle, params, index_view)); + } else if (ivf_pq_pams) { + index->nprobe = ivf_pq_pams->nprobe; + cuvs::neighbors::ivf_pq::index_params params; + params.metric = static_cast(metric); + params.metric_arg = metricArg; + params.n_lists = ivf_pq_pams->nlist; + params.pq_bits = ivf_pq_pams->n_bits; + params.pq_dim = ivf_pq_pams->M; + // TODO: handle ivf_pq_pams.usePrecomputedTables ? + + index->ivf_pq = std::make_unique>( + cuvs::neighbors::ivf_pq::build(handle, params, index_view)); + } else { + RAFT_FAIL("Unrecognized index type."); + } + + index->metric_processor->revert(index_array); } void approx_knn_search(raft::handle_t& handle, float* distances, int64_t* indices, - raft::spatial::knn::knnIndex* index, + knnIndex* index, int k, float* query_array, int n) { - raft::spatial::knn::approx_knn_search(handle, distances, indices, index, k, query_array, n); + index->metric_processor->preprocess(query_array); + index->metric_processor->set_num_queries(k); + + auto indices_view = raft::make_device_matrix_view(indices, n, k); + auto distances_view = raft::make_device_matrix_view(distances, n, k); + + if (index->ivf_flat) { + auto query_view = + raft::make_device_matrix_view(query_array, n, index->ivf_flat->dim()); + cuvs::neighbors::ivf_flat::search_params params; + params.n_probes = index->nprobe; + + cuvs::neighbors::ivf_flat::search( + handle, params, *index->ivf_flat, query_view, indices_view, distances_view); + } else if (index->ivf_pq) { + auto query_view = + raft::make_device_matrix_view(query_array, n, index->ivf_pq->dim()); + cuvs::neighbors::ivf_pq::search_params params; + params.n_probes = index->nprobe; + + cuvs::neighbors::ivf_pq::search( + handle, params, *index->ivf_pq, query_view, indices_view, distances_view); + } else { + RAFT_FAIL("The model is not trained"); + } + + index->metric_processor->revert(query_array); + + // perform post-processing to show the real distances + if (index->metric == raft::distance::DistanceType::L2SqrtExpanded || + index->metric == raft::distance::DistanceType::L2SqrtUnexpanded || + index->metric == raft::distance::DistanceType::LpUnexpanded) { + /** + * post-processing + */ + float p = 0.5; // standard l2 + if (index->metric == raft::distance::DistanceType::LpUnexpanded) p = 1.0 / index->metricArg; + raft::linalg::unaryOp(distances, + distances, + n * k, + raft::pow_const_op(p), + raft::resource::get_cuda_stream(handle)); + } + index->metric_processor->postprocess(distances); } void knn_classify(raft::handle_t& handle, diff --git a/cpp/src/knn/knn_opg_common.cuh b/cpp/src/knn/knn_opg_common.cuh index 188244d643..bcf3fe81ae 100644 --- a/cpp/src/knn/knn_opg_common.cuh +++ b/cpp/src/knn/knn_opg_common.cuh @@ -426,7 +426,7 @@ void perform_local_knn(opg_knn_param& params, size_t query_size) { std::vector ptrs(params.idx_data->size()); - std::vector sizes(params.idx_data->size()); + std::vector sizes(params.idx_data->size()); for (std::size_t cur_idx = 0; cur_idx < params.idx_data->size(); cur_idx++) { ptrs[cur_idx] = params.idx_data->at(cur_idx)->ptr; @@ -443,20 +443,20 @@ void perform_local_knn(opg_knn_param& params, // ID ranges need to be offset by each local partition's // starting indices. - raft::spatial::knn::brute_force_knn( - handle, - ptrs, - sizes, - params.idx_desc->N, - query, - query_size, - work.res_I.data(), - work.res_D.data(), - params.k, - params.rowMajorIndex, - params.rowMajorQuery, - &start_indices_long, - raft::distance::DistanceType::L2SqrtExpanded); + brute_force_knn(handle, + ptrs, + sizes, + params.idx_desc->N, + query, + query_size, + work.res_I.data(), + work.res_D.data(), + params.k, + params.rowMajorIndex, + params.rowMajorQuery, + raft::distance::DistanceType::L2SqrtExpanded, + 2.0f, + &start_indices_long); handle.sync_stream(handle.get_stream()); RAFT_CUDA_TRY(cudaPeekAtLastError()); } diff --git a/cpp/src/metrics/pairwise_distance.cu b/cpp/src/metrics/pairwise_distance.cu index 4cb9fb60d1..1f56ae8bf9 100644 --- a/cpp/src/metrics/pairwise_distance.cu +++ b/cpp/src/metrics/pairwise_distance.cu @@ -15,25 +15,14 @@ * limitations under the License. */ -#include "pairwise_distance_canberra.cuh" -#include "pairwise_distance_chebyshev.cuh" -#include "pairwise_distance_correlation.cuh" -#include "pairwise_distance_cosine.cuh" -#include "pairwise_distance_euclidean.cuh" -#include "pairwise_distance_hamming.cuh" -#include "pairwise_distance_hellinger.cuh" -#include "pairwise_distance_jensen_shannon.cuh" -#include "pairwise_distance_kl_divergence.cuh" -#include "pairwise_distance_l1.cuh" -#include "pairwise_distance_minkowski.cuh" -#include "pairwise_distance_russell_rao.cuh" - #include #include #include #include +#include + namespace ML { namespace Metrics { @@ -48,48 +37,23 @@ void pairwise_distance(const raft::handle_t& handle, bool isRowMajor, double metric_arg) { - switch (metric) { - case raft::distance::DistanceType::L2Expanded: - case raft::distance::DistanceType::L2SqrtExpanded: - case raft::distance::DistanceType::L2Unexpanded: - case raft::distance::DistanceType::L2SqrtUnexpanded: - pairwise_distance_euclidean(handle, x, y, dist, m, n, k, metric, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::CosineExpanded: - pairwise_distance_cosine(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::L1: - pairwise_distance_l1(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::Linf: - pairwise_distance_chebyshev(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::HellingerExpanded: - pairwise_distance_hellinger(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::LpUnexpanded: - pairwise_distance_minkowski(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::Canberra: - pairwise_distance_canberra(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::CorrelationExpanded: - pairwise_distance_correlation(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::HammingUnexpanded: - pairwise_distance_hamming(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::JensenShannon: - pairwise_distance_jensen_shannon(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::KLDivergence: - pairwise_distance_kl_divergence(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::RusselRaoExpanded: - pairwise_distance_russell_rao(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - default: THROW("Unknown or unsupported distance metric '%d'!", (int)metric); - }; + if (isRowMajor) { + cuvs::distance::pairwise_distance( + handle, + raft::make_device_matrix_view(x, m, k), + raft::make_device_matrix_view(y, n, k), + raft::make_device_matrix_view(dist, m, n), + static_cast(metric), + metric_arg); + } else { + cuvs::distance::pairwise_distance( + handle, + raft::make_device_matrix_view(x, m, k), + raft::make_device_matrix_view(y, n, k), + raft::make_device_matrix_view(dist, m, n), + static_cast(metric), + metric_arg); + } } void pairwise_distance(const raft::handle_t& handle, @@ -103,48 +67,23 @@ void pairwise_distance(const raft::handle_t& handle, bool isRowMajor, float metric_arg) { - switch (metric) { - case raft::distance::DistanceType::L2Expanded: - case raft::distance::DistanceType::L2SqrtExpanded: - case raft::distance::DistanceType::L2Unexpanded: - case raft::distance::DistanceType::L2SqrtUnexpanded: - pairwise_distance_euclidean(handle, x, y, dist, m, n, k, metric, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::CosineExpanded: - pairwise_distance_cosine(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::L1: - pairwise_distance_l1(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::Linf: - pairwise_distance_chebyshev(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::HellingerExpanded: - pairwise_distance_hellinger(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::LpUnexpanded: - pairwise_distance_minkowski(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::Canberra: - pairwise_distance_canberra(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::CorrelationExpanded: - pairwise_distance_correlation(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::HammingUnexpanded: - pairwise_distance_hamming(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::JensenShannon: - pairwise_distance_jensen_shannon(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::KLDivergence: - pairwise_distance_kl_divergence(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - case raft::distance::DistanceType::RusselRaoExpanded: - pairwise_distance_russell_rao(handle, x, y, dist, m, n, k, isRowMajor, metric_arg); - break; - default: THROW("Unknown or unsupported distance metric '%d'!", (int)metric); - }; + if (isRowMajor) { + cuvs::distance::pairwise_distance( + handle, + raft::make_device_matrix_view(x, m, k), + raft::make_device_matrix_view(y, n, k), + raft::make_device_matrix_view(dist, m, n), + static_cast(metric), + metric_arg); + } else { + cuvs::distance::pairwise_distance( + handle, + raft::make_device_matrix_view(x, m, k), + raft::make_device_matrix_view(y, n, k), + raft::make_device_matrix_view(dist, m, n), + static_cast(metric), + metric_arg); + } } template diff --git a/cpp/src/metrics/pairwise_distance_canberra.cu b/cpp/src/metrics/pairwise_distance_canberra.cu deleted file mode 100644 index dab8f84d30..0000000000 --- a/cpp/src/metrics/pairwise_distance_canberra.cu +++ /dev/null @@ -1,59 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_canberra.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_canberra(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - // Call the distance function - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_canberra(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - // Call the distance function - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_canberra.cuh b/cpp/src/metrics/pairwise_distance_canberra.cuh deleted file mode 100644 index 76244fae8b..0000000000 --- a/cpp/src/metrics/pairwise_distance_canberra.cuh +++ /dev/null @@ -1,47 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_canberra(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_canberra(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_chebyshev.cu b/cpp/src/metrics/pairwise_distance_chebyshev.cu deleted file mode 100644 index b5e99de16c..0000000000 --- a/cpp/src/metrics/pairwise_distance_chebyshev.cu +++ /dev/null @@ -1,58 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_chebyshev.cuh" - -#include -#include - -#include -namespace ML { - -namespace Metrics { -void pairwise_distance_chebyshev(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - // Call the distance function - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_chebyshev(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - // Call the distance function - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_chebyshev.cuh b/cpp/src/metrics/pairwise_distance_chebyshev.cuh deleted file mode 100644 index d2219a5f84..0000000000 --- a/cpp/src/metrics/pairwise_distance_chebyshev.cuh +++ /dev/null @@ -1,46 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_chebyshev(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_chebyshev(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_correlation.cu b/cpp/src/metrics/pairwise_distance_correlation.cu deleted file mode 100644 index 36fe78ec7e..0000000000 --- a/cpp/src/metrics/pairwise_distance_correlation.cu +++ /dev/null @@ -1,61 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_correlation.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_correlation(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - // Call the distance function - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_correlation(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - // Call the distance function - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_correlation.cuh b/cpp/src/metrics/pairwise_distance_correlation.cuh deleted file mode 100644 index e34c2224e7..0000000000 --- a/cpp/src/metrics/pairwise_distance_correlation.cuh +++ /dev/null @@ -1,47 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_correlation(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_correlation(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_cosine.cu b/cpp/src/metrics/pairwise_distance_cosine.cu deleted file mode 100644 index e207b8ad06..0000000000 --- a/cpp/src/metrics/pairwise_distance_cosine.cu +++ /dev/null @@ -1,60 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_cosine.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_cosine(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - // Call the distance function - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_cosine(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - // Call the distance function - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_cosine.cuh b/cpp/src/metrics/pairwise_distance_cosine.cuh deleted file mode 100644 index 0024ed52ac..0000000000 --- a/cpp/src/metrics/pairwise_distance_cosine.cuh +++ /dev/null @@ -1,46 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_cosine(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_cosine(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_euclidean.cu b/cpp/src/metrics/pairwise_distance_euclidean.cu deleted file mode 100644 index 56cb609067..0000000000 --- a/cpp/src/metrics/pairwise_distance_euclidean.cu +++ /dev/null @@ -1,102 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_euclidean.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_euclidean(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - raft::distance::DistanceType metric, - bool isRowMajor, - double metric_arg) -{ - // Call the distance function - switch (metric) { - case raft::distance::DistanceType::L2Expanded: - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - case raft::distance::DistanceType::L2SqrtExpanded: - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - case raft::distance::DistanceType::L2Unexpanded: - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - case raft::distance::DistanceType::L2SqrtUnexpanded: - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - default: THROW("Unknown or unsupported distance metric '%d'!", (int)metric); - } -} - -void pairwise_distance_euclidean(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - raft::distance::DistanceType metric, - bool isRowMajor, - float metric_arg) -{ - // Call the distance function - switch (metric) { - case raft::distance::DistanceType::L2Expanded: - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - case raft::distance::DistanceType::L2SqrtExpanded: - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - case raft::distance::DistanceType::L2Unexpanded: - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - case raft::distance::DistanceType::L2SqrtUnexpanded: - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); - break; - default: THROW("Unknown or unsupported distance metric '%d'!", (int)metric); - } -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_euclidean.cuh b/cpp/src/metrics/pairwise_distance_euclidean.cuh deleted file mode 100644 index 65a3f41683..0000000000 --- a/cpp/src/metrics/pairwise_distance_euclidean.cuh +++ /dev/null @@ -1,46 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ -#pragma once -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_euclidean(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - raft::distance::DistanceType metric, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_euclidean(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - raft::distance::DistanceType metric, - bool isRowMajor, - float metric_arg); -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_hamming.cu b/cpp/src/metrics/pairwise_distance_hamming.cu deleted file mode 100644 index 080faffe96..0000000000 --- a/cpp/src/metrics/pairwise_distance_hamming.cu +++ /dev/null @@ -1,61 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_hamming.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_hamming(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - // Call the distance function - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_hamming(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - // Call the distance function - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_hamming.cuh b/cpp/src/metrics/pairwise_distance_hamming.cuh deleted file mode 100644 index 7c89b6b58f..0000000000 --- a/cpp/src/metrics/pairwise_distance_hamming.cuh +++ /dev/null @@ -1,47 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_hamming(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_hamming(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_hellinger.cu b/cpp/src/metrics/pairwise_distance_hellinger.cu deleted file mode 100644 index 6cb09e0d93..0000000000 --- a/cpp/src/metrics/pairwise_distance_hellinger.cu +++ /dev/null @@ -1,60 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_hellinger.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_hellinger(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - // Call the distance function - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_hellinger(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_hellinger.cuh b/cpp/src/metrics/pairwise_distance_hellinger.cuh deleted file mode 100644 index 94d0089223..0000000000 --- a/cpp/src/metrics/pairwise_distance_hellinger.cuh +++ /dev/null @@ -1,45 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_hellinger(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_hellinger(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_jensen_shannon.cu b/cpp/src/metrics/pairwise_distance_jensen_shannon.cu deleted file mode 100644 index cf25a8cb5e..0000000000 --- a/cpp/src/metrics/pairwise_distance_jensen_shannon.cu +++ /dev/null @@ -1,58 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_jensen_shannon.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_jensen_shannon(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_jensen_shannon(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_jensen_shannon.cuh b/cpp/src/metrics/pairwise_distance_jensen_shannon.cuh deleted file mode 100644 index c4ba9a218e..0000000000 --- a/cpp/src/metrics/pairwise_distance_jensen_shannon.cuh +++ /dev/null @@ -1,47 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_jensen_shannon(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_jensen_shannon(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_kl_divergence.cu b/cpp/src/metrics/pairwise_distance_kl_divergence.cu deleted file mode 100644 index c47fb7adae..0000000000 --- a/cpp/src/metrics/pairwise_distance_kl_divergence.cu +++ /dev/null @@ -1,57 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_kl_divergence.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_kl_divergence(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_kl_divergence(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_kl_divergence.cuh b/cpp/src/metrics/pairwise_distance_kl_divergence.cuh deleted file mode 100644 index f3866de89d..0000000000 --- a/cpp/src/metrics/pairwise_distance_kl_divergence.cuh +++ /dev/null @@ -1,47 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_kl_divergence(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_kl_divergence(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_l1.cu b/cpp/src/metrics/pairwise_distance_l1.cu deleted file mode 100644 index 3d3ebf625b..0000000000 --- a/cpp/src/metrics/pairwise_distance_l1.cu +++ /dev/null @@ -1,57 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_l1.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_l1(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_l1(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_l1.cuh b/cpp/src/metrics/pairwise_distance_l1.cuh deleted file mode 100644 index 311cc186e7..0000000000 --- a/cpp/src/metrics/pairwise_distance_l1.cuh +++ /dev/null @@ -1,46 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_l1(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_l1(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_minkowski.cu b/cpp/src/metrics/pairwise_distance_minkowski.cu deleted file mode 100644 index 91146955e9..0000000000 --- a/cpp/src/metrics/pairwise_distance_minkowski.cu +++ /dev/null @@ -1,57 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_minkowski.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_minkowski(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor, metric_arg); -} - -void pairwise_distance_minkowski(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - raft::distance::distance( - handle, x, y, dist, m, n, k, isRowMajor, metric_arg); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_minkowski.cuh b/cpp/src/metrics/pairwise_distance_minkowski.cuh deleted file mode 100644 index 0fe15de554..0000000000 --- a/cpp/src/metrics/pairwise_distance_minkowski.cuh +++ /dev/null @@ -1,47 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_minkowski(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_minkowski(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_russell_rao.cu b/cpp/src/metrics/pairwise_distance_russell_rao.cu deleted file mode 100644 index efeb66d13f..0000000000 --- a/cpp/src/metrics/pairwise_distance_russell_rao.cu +++ /dev/null @@ -1,59 +0,0 @@ - -/* - * Copyright (c) 2021-2024, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "pairwise_distance_russell_rao.cuh" - -#include -#include - -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_russell_rao(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg) -{ - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -void pairwise_distance_russell_rao(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg) -{ - raft::distance:: - distance( - handle, x, y, dist, m, n, k, isRowMajor); -} - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/pairwise_distance_russell_rao.cuh b/cpp/src/metrics/pairwise_distance_russell_rao.cuh deleted file mode 100644 index 574a5116df..0000000000 --- a/cpp/src/metrics/pairwise_distance_russell_rao.cuh +++ /dev/null @@ -1,47 +0,0 @@ - -/* - * Copyright (c) 2021-2023, NVIDIA CORPORATION. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#pragma once - -#include -#include - -namespace ML { - -namespace Metrics { -void pairwise_distance_russell_rao(const raft::handle_t& handle, - const double* x, - const double* y, - double* dist, - int m, - int n, - int k, - bool isRowMajor, - double metric_arg); - -void pairwise_distance_russell_rao(const raft::handle_t& handle, - const float* x, - const float* y, - float* dist, - int m, - int n, - int k, - bool isRowMajor, - float metric_arg); - -} // namespace Metrics -} // namespace ML diff --git a/cpp/src/metrics/silhouette_score.cu b/cpp/src/metrics/silhouette_score.cu index 883a9eabb3..cf4fdeb6fd 100644 --- a/cpp/src/metrics/silhouette_score.cu +++ b/cpp/src/metrics/silhouette_score.cu @@ -18,8 +18,9 @@ #include #include -#include -#include + +#include +#include namespace ML { @@ -33,9 +34,18 @@ double silhouette_score(const raft::handle_t& handle, double* silScores, raft::distance::DistanceType metric) { - return raft::stats::silhouette_score( - handle, y, nRows, nCols, labels, nLabels, silScores, handle.get_stream(), metric); -} + std::optional> silhouette_score_per_sample; + if (silScores != NULL) { + silhouette_score_per_sample = raft::make_device_vector_view(silScores, nRows); + } + return cuvs::stats::silhouette_score( + handle, + raft::make_device_matrix_view(y, nRows, nCols), + raft::make_device_vector_view(labels, nRows), + silhouette_score_per_sample, + nLabels, + static_cast(metric)); +} } // namespace Metrics } // namespace ML diff --git a/cpp/src/metrics/silhouette_score_batched_double.cu b/cpp/src/metrics/silhouette_score_batched_double.cu index 961170a63f..3188ce0bc4 100644 --- a/cpp/src/metrics/silhouette_score_batched_double.cu +++ b/cpp/src/metrics/silhouette_score_batched_double.cu @@ -18,11 +18,11 @@ #include #include -#include -#include -namespace ML { +#include +#include +namespace ML { namespace Metrics { namespace Batched { @@ -36,11 +36,21 @@ double silhouette_score(const raft::handle_t& handle, int chunk, raft::distance::DistanceType metric) { - return raft::stats::silhouette_score_batched( - handle, X, n_rows, n_cols, y, n_labels, scores, chunk, metric); + std::optional> silhouette_score_per_sample; + if (scores != NULL) { + silhouette_score_per_sample = raft::make_device_vector_view(scores, n_rows); + } + + return cuvs::stats::silhouette_score_batched( + handle, + raft::make_device_matrix_view(X, n_rows, n_cols), + raft::make_device_vector_view(y, n_rows), + silhouette_score_per_sample, + n_labels, + chunk, + static_cast(metric)); } } // namespace Batched - } // namespace Metrics } // namespace ML diff --git a/cpp/src/metrics/silhouette_score_batched_float.cu b/cpp/src/metrics/silhouette_score_batched_float.cu index d24129f465..0245375657 100644 --- a/cpp/src/metrics/silhouette_score_batched_float.cu +++ b/cpp/src/metrics/silhouette_score_batched_float.cu @@ -19,12 +19,11 @@ #include #include -#include -namespace ML { +#include +namespace ML { namespace Metrics { - namespace Batched { float silhouette_score(const raft::handle_t& handle, @@ -37,10 +36,20 @@ float silhouette_score(const raft::handle_t& handle, int chunk, raft::distance::DistanceType metric) { - return raft::stats::silhouette_score_batched( - handle, X, n_rows, n_cols, y, n_labels, scores, chunk, metric); + std::optional> silhouette_score_per_sample; + if (scores != NULL) { + silhouette_score_per_sample = raft::make_device_vector_view(scores, n_rows); + } + + return cuvs::stats::silhouette_score_batched( + handle, + raft::make_device_matrix_view(X, n_rows, n_cols), + raft::make_device_vector_view(y, n_rows), + silhouette_score_per_sample, + n_labels, + chunk, + static_cast(metric)); } - } // namespace Batched } // namespace Metrics } // namespace ML diff --git a/cpp/src/metrics/trustworthiness.cu b/cpp/src/metrics/trustworthiness.cu index 7b5f80a010..724ef43ddd 100644 --- a/cpp/src/metrics/trustworthiness.cu +++ b/cpp/src/metrics/trustworthiness.cu @@ -17,8 +17,8 @@ #include #include -#include -#include + +#include namespace ML { namespace Metrics { @@ -47,8 +47,13 @@ double trustworthiness_score(const raft::handle_t& h, int n_neighbors, int batchSize) { - return raft::stats::trustworthiness_score( - h, X, X_embedded, n, m, d, n_neighbors, batchSize); + return cuvs::stats::trustworthiness_score( + h, + raft::make_device_matrix_view(X, n, m), + raft::make_device_matrix_view(X_embedded, n, d), + n_neighbors, + static_cast(distance_type), + batchSize); } template double trustworthiness_score( diff --git a/cpp/src/tsne/distances.cuh b/cpp/src/tsne/distances.cuh index 4963f42eee..31be50942c 100644 --- a/cpp/src/tsne/distances.cuh +++ b/cpp/src/tsne/distances.cuh @@ -37,13 +37,14 @@ #include #include +#include #include namespace ML { namespace TSNE { /** - * @brief Uses FAISS's KNN to find the top n_neighbors. This speeds up the attractive forces. + * @brief Uses CUVS's KNN to find the top n_neighbors. This speeds up the attractive forces. * @param[in] input: dense/sparse manifold input * @param[out] indices: The output indices from KNN. * @param[out] distances: The output sorted distances from KNN. @@ -70,32 +71,18 @@ void get_distances(const raft::handle_t& handle, { // TODO: for TSNE transform first fit some points then transform with 1/(1+d^2) // #861 - - std::vector input_vec = {input.X}; - std::vector sizes_vec = {input.n}; - - /** - * std::vector &input, std::vector &sizes, - IntType D, float *search_items, IntType n, int64_t *res_I, - float *res_D, IntType k, - std::shared_ptr allocator, - cudaStream_t userStream, - */ - - raft::spatial::knn::brute_force_knn(handle, - input_vec, - sizes_vec, - input.d, - input.X, - input.n, - k_graph.knn_indices, - k_graph.knn_dists, - k_graph.n_neighbors, - false, - false, - nullptr, - metric, - p); + auto k = k_graph.n_neighbors; + auto X_view = + raft::make_device_matrix_view(input.X, input.n, input.d); + auto idx = cuvs::neighbors::brute_force::build( + handle, X_view, static_cast(metric), p); + + cuvs::neighbors::brute_force::search( + handle, + idx, + X_view, + raft::make_device_matrix_view(k_graph.knn_indices, input.n, k), + raft::make_device_matrix_view(k_graph.knn_dists, input.n, k)); } // dense, int32 indices diff --git a/cpp/src/umap/knn_graph/algo.cuh b/cpp/src/umap/knn_graph/algo.cuh index 92c717afcd..fa55397659 100644 --- a/cpp/src/umap/knn_graph/algo.cuh +++ b/cpp/src/umap/knn_graph/algo.cuh @@ -36,6 +36,8 @@ #include #include +#include + #include namespace NNDescent = raft::neighbors::experimental::nn_descent; @@ -92,26 +94,20 @@ inline void launcher(const raft::handle_t& handle, cudaStream_t stream) { if (params->build_algo == ML::UMAPParams::graph_build_algo::BRUTE_FORCE_KNN) { - std::vector ptrs(1); - std::vector sizes(1); - ptrs[0] = inputsA.X; - sizes[0] = inputsA.n; - - raft::spatial::knn::brute_force_knn(handle, - ptrs, - sizes, - inputsA.d, - inputsB.X, - inputsB.n, - out.knn_indices, - out.knn_dists, - n_neighbors, - true, - true, - static_cast*>(nullptr), - params->metric, - params->p); + auto idx = cuvs::neighbors::brute_force::build( + handle, + raft::make_device_matrix_view(inputsA.X, inputsA.n, inputsA.d), + static_cast(params->metric), + params->p); + + cuvs::neighbors::brute_force::search( + handle, + idx, + raft::make_device_matrix_view(inputsB.X, inputsB.n, inputsB.d), + raft::make_device_matrix_view(out.knn_indices, inputsB.n, n_neighbors), + raft::make_device_matrix_view(out.knn_dists, inputsB.n, n_neighbors)); } else { // nn_descent + // TODO: use nndescent from cuvs RAFT_EXPECTS(static_cast(n_neighbors) <= params->nn_descent_params.graph_degree, "n_neighbors should be smaller than the graph degree computed by nn descent"); diff --git a/cpp/test/CMakeLists.txt b/cpp/test/CMakeLists.txt index 2a04100cdf..46bd275fcc 100644 --- a/cpp/test/CMakeLists.txt +++ b/cpp/test/CMakeLists.txt @@ -57,7 +57,6 @@ function(ConfigureTest) $<$:CUDA::cufft${_ctk_static_suffix_cufft}> rmm::rmm raft::raft - $<$:raft::compiled> GTest::gtest GTest::gtest_main GTest::gmock diff --git a/cpp/test/prims/knn_classify.cu b/cpp/test/prims/knn_classify.cu index 56bc6a245d..75d59e6fda 100644 --- a/cpp/test/prims/knn_classify.cu +++ b/cpp/test/prims/knn_classify.cu @@ -24,6 +24,7 @@ #include +#include #include #include @@ -73,20 +74,17 @@ class KNNClassifyTest : public ::testing::TestWithParam { auto n_classes = raft::label::getUniquelabels(unique_labels, train_labels.data(), params.rows, stream); - std::vector ptrs(1); - std::vector sizes(1); - ptrs[0] = train_samples.data(); - sizes[0] = params.rows; - - raft::spatial::knn::brute_force_knn(handle, - ptrs, - sizes, - params.cols, - train_samples.data(), - params.rows, - knn_indices.data(), - knn_dists.data(), - params.k); + auto train_view = raft::make_device_matrix_view( + train_samples.data(), params.rows, params.cols); + auto idx = cuvs::neighbors::brute_force::build( + handle, train_view, cuvs::distance::DistanceType::L2Unexpanded); + + cuvs::neighbors::brute_force::search( + handle, + idx, + train_view, + raft::make_device_matrix_view(knn_indices.data(), params.rows, params.k), + raft::make_device_matrix_view(knn_dists.data(), params.rows, params.k)); std::vector y; y.push_back(train_labels.data()); diff --git a/cpp/test/prims/knn_regression.cu b/cpp/test/prims/knn_regression.cu index 7c29c8ea1e..07ae30dfd5 100644 --- a/cpp/test/prims/knn_regression.cu +++ b/cpp/test/prims/knn_regression.cu @@ -29,6 +29,7 @@ #include #include +#include #include #include @@ -99,20 +100,18 @@ class KNNRegressionTest : public ::testing::TestWithParam { { generate_data(train_samples.data(), train_labels.data(), params.rows, params.cols, stream); - std::vector ptrs(1); - std::vector sizes(1); - ptrs[0] = train_samples.data(); - sizes[0] = params.rows; - - raft::spatial::knn::brute_force_knn(handle, - ptrs, - sizes, - params.cols, - train_samples.data(), - params.rows, - knn_indices.data(), - knn_dists.data(), - params.k); + auto train_view = raft::make_device_matrix_view( + train_samples.data(), params.rows, params.cols); + + auto idx = cuvs::neighbors::brute_force::build( + handle, train_view, cuvs::distance::DistanceType::L2Unexpanded); + + cuvs::neighbors::brute_force::search( + handle, + idx, + train_view, + raft::make_device_matrix_view(knn_indices.data(), params.rows, params.k), + raft::make_device_matrix_view(knn_dists.data(), params.rows, params.k)); std::vector y; y.push_back(train_labels.data()); diff --git a/cpp/test/sg/hdbscan_test.cu b/cpp/test/sg/hdbscan_test.cu index 08705f5a8b..a7ce69b1bc 100644 --- a/cpp/test/sg/hdbscan_test.cu +++ b/cpp/test/sg/hdbscan_test.cu @@ -19,7 +19,7 @@ #include -#include +#include // build_dendrogram_host #include #include #include @@ -34,6 +34,7 @@ #include #include +#include #include #include #include diff --git a/cpp/test/sg/umap_parametrizable_test.cu b/cpp/test/sg/umap_parametrizable_test.cu index 821437fb0e..2980a79394 100644 --- a/cpp/test/sg/umap_parametrizable_test.cu +++ b/cpp/test/sg/umap_parametrizable_test.cu @@ -126,20 +126,17 @@ class UMAPParametrizableTest : public ::testing::Test { knn_indices = knn_indices_b->data(); knn_dists = knn_dists_b->data(); - std::vector ptrs(1); - std::vector sizes(1); - ptrs[0] = X; - sizes[0] = n_samples; - - raft::spatial::knn::brute_force_knn(handle, - ptrs, - sizes, - n_features, - X, - n_samples, - knn_indices, - knn_dists, - umap_params.n_neighbors); + auto X_view = raft::make_device_matrix_view(X, n_samples, n_features); + auto idx = cuvs::neighbors::brute_force::build( + handle, X_view, cuvs::distance::DistanceType::L2Unexpanded); + + cuvs::neighbors::brute_force::search(handle, + idx, + X_view, + raft::make_device_matrix_view( + knn_indices, n_samples, umap_params.n_neighbors), + raft::make_device_matrix_view( + knn_dists, n_samples, umap_params.n_neighbors)); handle.sync_stream(stream); } diff --git a/dependencies.yaml b/dependencies.yaml index 687c0bd9aa..0108588363 100644 --- a/dependencies.yaml +++ b/dependencies.yaml @@ -142,7 +142,7 @@ dependencies: - cxx-compiler - fmt>=11.0.2,<12 - libcumlprims==24.10.*,>=0.0.0a0 - - libraft==24.10.*,>=0.0.0a0 + - libcuvs==24.10.*,>=0.0.0a0 - libraft-headers==24.10.*,>=0.0.0a0 - librmm==24.10.*,>=0.0.0a0 - spdlog>=1.14.1,<1.15 @@ -183,6 +183,7 @@ dependencies: - &treelite treelite==4.3.0 - output_types: conda packages: + - &cuvs_unsuffixed cuvs==24.10.*,>=0.0.0a0 - &pylibraft_unsuffixed pylibraft==24.10.*,>=0.0.0a0 - &rmm_unsuffixed rmm==24.10.*,>=0.0.0a0 - output_types: requirements @@ -211,16 +212,19 @@ dependencies: cuda: "12.*" cuda_suffixed: "true" packages: + - cuvs-cu12==24.10.*,>=0.0.0a0 - pylibraft-cu12==24.10.*,>=0.0.0a0 - rmm-cu12==24.10.*,>=0.0.0a0 - matrix: cuda: "11.*" cuda_suffixed: "true" packages: + - cuvs-cu11==24.10.*,>=0.0.0a0 - pylibraft-cu11==24.10.*,>=0.0.0a0 - rmm-cu11==24.10.*,>=0.0.0a0 - matrix: packages: + - *cuvs_unsuffixed - *pylibraft_unsuffixed - *rmm_unsuffixed @@ -260,6 +264,7 @@ dependencies: packages: - cudf-cu12==24.10.*,>=0.0.0a0 - &cupy_pyproject_cu12 cupy-cuda12x>=12.0.0 + - cuvs-cu12==24.10.*,>=0.0.0a0 - dask-cudf-cu12==24.10.*,>=0.0.0a0 - pylibraft-cu12==24.10.*,>=0.0.0a0 - raft-dask-cu12==24.10.*,>=0.0.0a0 @@ -272,6 +277,7 @@ dependencies: # NOTE: cupy still has a "-cuda12x" suffix here, because it's suffixed # in DLFW builds - *cupy_pyproject_cu12 + - *cuvs_unsuffixed - *dask_cudf_unsuffixed - *pylibraft_unsuffixed - *raft_dask_unsuffixed @@ -282,6 +288,7 @@ dependencies: packages: &py_run_packages_cu11 - cudf-cu11==24.10.*,>=0.0.0a0 - &cupy_pyproject_cu11 cupy-cuda11x>=12.0.0 + - cuvs-cu11==24.10.*,>=0.0.0a0 - dask-cudf-cu11==24.10.*,>=0.0.0a0 - pylibraft-cu11==24.10.*,>=0.0.0a0 - raft-dask-cu11==24.10.*,>=0.0.0a0 @@ -294,6 +301,7 @@ dependencies: # NOTE: cupy still has a "-cuda11x" suffix here, because it's suffixed # in DLFW builds - *cupy_pyproject_cu11 + - *cuvs_unsuffixed - *dask_cudf_unsuffixed - *pylibraft_unsuffixed - *raft_dask_unsuffixed @@ -302,6 +310,7 @@ dependencies: packages: - *cudf_unsuffixed - *cupy_pyproject_cu11 + - *cuvs_unsuffixed - *dask_cudf_unsuffixed - *pylibraft_unsuffixed - *raft_dask_unsuffixed diff --git a/python/cuml/CMakeLists.txt b/python/cuml/CMakeLists.txt index 224525ee58..221b5ebf75 100644 --- a/python/cuml/CMakeLists.txt +++ b/python/cuml/CMakeLists.txt @@ -39,6 +39,7 @@ option(CUML_UNIVERSAL "Build all cuML Python components." ON) option(FIND_CUML_CPP "Search for existing CUML C++ installations before defaulting to local files" OFF) option(SINGLEGPU "Disable all mnmg components and comms libraries" OFF) option(USE_CUDA_MATH_WHEELS "Use the CUDA math wheels instead of the system libraries" OFF) +option(USE_CUVS_WHEEL "Use the cuVS wheel" OFF) set(CUML_RAFT_CLONE_ON_PIN OFF) @@ -88,7 +89,7 @@ if(NOT CUML_CPU) # Statically link dependencies if building wheels set(CUDA_STATIC_RUNTIME ON) - set(CUML_USE_RAFT_STATIC ON) + set(CUML_USE_CUVS_STATIC ON) set(CUML_USE_FAISS_STATIC ON) set(CUML_USE_TREELITE_STATIC ON) set(CUML_USE_CUMLPRIMS_MG_STATIC ON) @@ -110,7 +111,7 @@ if(NOT CUML_CPU) add_subdirectory(${CUML_CPP_SRC} cuml-cpp EXCLUDE_FROM_ALL) if(NOT CUDA_STATIC_MATH_LIBRARIES AND USE_CUDA_MATH_WHEELS) - set_property(TARGET ${CUML_CPP_TARGET} PROPERTY INSTALL_RPATH + set(rpaths "$ORIGIN/../nvidia/cublas/lib" "$ORIGIN/../nvidia/cufft/lib" "$ORIGIN/../nvidia/curand/lib" @@ -118,6 +119,12 @@ if(NOT CUML_CPU) "$ORIGIN/../nvidia/cusparse/lib" "$ORIGIN/../nvidia/nvjitlink/lib" ) + set_property(TARGET ${CUML_CPP_TARGET} PROPERTY INSTALL_RPATH ${rpaths} APPEND) + endif() + + if(USE_CUVS_WHEEL) + set(rpaths "$ORIGIN/../cuvs") + set_property(TARGET ${CUML_CPP_TARGET} PROPERTY INSTALL_RPATH ${rpaths} APPEND) endif() set(cython_lib_dir cuml) @@ -205,3 +212,7 @@ add_subdirectory(cuml/experimental/linear_model) if(DEFINED cython_lib_dir) rapids_cython_add_rpath_entries(TARGET cuml PATHS "${cython_lib_dir}") endif() + +if(USE_CUVS_WHEEL) + rapids_cython_add_rpath_entries(TARGET cuml PATHS cuvs) +endif() diff --git a/python/cuml/cuml/cluster/cpp/kmeans.pxd b/python/cuml/cuml/cluster/cpp/kmeans.pxd index 53b4c44d1d..fa3db02c6e 100644 --- a/python/cuml/cuml/cluster/cpp/kmeans.pxd +++ b/python/cuml/cuml/cluster/cpp/kmeans.pxd @@ -1,5 +1,5 @@ # -# Copyright (c) 2019-2023, NVIDIA CORPORATION. +# Copyright (c) 2019-2024, NVIDIA CORPORATION. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -27,28 +27,10 @@ from libcpp cimport bool from cuml.metrics.distance_type cimport DistanceType from cuml.common.rng_state cimport RngState -cdef extern from "cuml/cluster/kmeans.hpp" namespace \ - "ML::kmeans::KMeansParams": - enum InitMethod: - KMeansPlusPlus, Random, Array - - cdef struct KMeansParams: - int n_clusters, - InitMethod init - int max_iter, - double tol, - int verbosity, - RngState rng_state, - DistanceType metric, - int n_init, - double oversampling_factor, - int batch_samples, - int batch_centroids, - bool inertia_check +from cuml.cluster.kmeans_utils cimport params as KMeansParams cdef extern from "cuml/cluster/kmeans.hpp" namespace "ML::kmeans": - cdef void fit_predict(handle_t& handle, KMeansParams& params, const float *X, diff --git a/python/cuml/cuml/cluster/kmeans.pyx b/python/cuml/cuml/cluster/kmeans.pyx index 3d6be3abf2..fde067c14c 100644 --- a/python/cuml/cuml/cluster/kmeans.pyx +++ b/python/cuml/cuml/cluster/kmeans.pyx @@ -33,9 +33,10 @@ IF GPUBUILD == 1: from cuml.cluster.cpp.kmeans cimport fit_predict as cpp_fit_predict from cuml.cluster.cpp.kmeans cimport predict as cpp_predict from cuml.cluster.cpp.kmeans cimport transform as cpp_transform - from cuml.cluster.cpp.kmeans cimport KMeansParams from cuml.metrics.distance_type cimport DistanceType - from cuml.cluster.kmeans_utils cimport * + from cuml.cluster.kmeans_utils cimport params as KMeansParams + from cuml.cluster.kmeans_utils cimport KMeansPlusPlus, Random, Array + from cuml.cluster.kmeans_utils cimport DistanceType as CuvsDistanceType from cuml.internals.array import CumlArray from cuml.common.array_descriptor import CumlArrayDescriptor @@ -207,7 +208,7 @@ class KMeans(UniversalBase, params.tol = self.tol params.verbosity = self.verbose params.rng_state.seed = self.random_state - params.metric = DistanceType.L2Expanded # distance metric as squared L2: @todo - support other metrics # noqa: E501 + params.metric = CuvsDistanceType.L2Expanded # distance metric as squared L2: @todo - support other metrics # noqa: E501 params.batch_samples = self.max_samples_per_batch params.oversampling_factor = self.oversampling_factor params.n_init = self.n_init @@ -609,7 +610,8 @@ class KMeans(UniversalBase, # distance metric as L2-norm/euclidean distance: @todo - support other metrics # noqa: E501 cdef KMeansParams* params = \ self._get_kmeans_params() - params.metric = DistanceType.L2SqrtExpanded + + params.metric = CuvsDistanceType.L2Expanded int_dtype = np.int32 if self.labels_.dtype == np.int32 else np.int64 diff --git a/python/cuml/cuml/cluster/kmeans_mg.pyx b/python/cuml/cuml/cluster/kmeans_mg.pyx index 51d415036b..cf0a2967c4 100644 --- a/python/cuml/cuml/cluster/kmeans_mg.pyx +++ b/python/cuml/cuml/cluster/kmeans_mg.pyx @@ -31,7 +31,7 @@ from pylibraft.common.handle cimport handle_t from cuml.common import input_to_cuml_array from cuml.cluster import KMeans -from cuml.cluster.kmeans_utils cimport * +from cuml.cluster.kmeans_utils cimport params as KMeansParams cdef extern from "cuml/cluster/kmeans_mg.hpp" \ diff --git a/python/cuml/cuml/cluster/kmeans_utils.pxd b/python/cuml/cuml/cluster/kmeans_utils.pxd index efbe27dcd7..17d58a49be 100644 --- a/python/cuml/cuml/cluster/kmeans_utils.pxd +++ b/python/cuml/cuml/cluster/kmeans_utils.pxd @@ -1,5 +1,5 @@ # -# Copyright (c) 2019-2022, NVIDIA CORPORATION. +# Copyright (c) 2019-2024, NVIDIA CORPORATION. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -17,15 +17,39 @@ import ctypes from libcpp cimport bool -from cuml.metrics.distance_type cimport DistanceType from cuml.common.rng_state cimport RngState +cdef extern from "cuvs/distance/distance.hpp" namespace \ + "cuvs::distance": + ctypedef enum DistanceType: + L2Expanded "cuvs::distance::DistanceType::L2Expanded" + L2SqrtExpanded "cuvs::distance::DistanceType::L2SqrtExpanded" + CosineExpanded "cuvs::distance::DistanceType::CosineExpanded" + L1 "cuvs::distance::DistanceType::L1" + L2Unexpanded "cuvs::distance::DistanceType::L2Unexpanded" + L2SqrtUnexpanded "cuvs::distance::DistanceType::L2SqrtUnexpanded" + InnerProduct "cuvs::distance::DistanceType::InnerProduct" + Linf "cuvs::distance::DistanceType::Linf" + Canberra "cuvs::distance::DistanceType::Canberra" + LpUnexpanded "cuvs::distance::DistanceType::LpUnexpanded" + CorrelationExpanded "cuvs::distance::DistanceType::CorrelationExpanded" + JaccardExpanded "cuvs::distance::DistanceType::JaccardExpanded" + HellingerExpanded "cuvs::distance::DistanceType::HellingerExpanded" + Haversine "cuvs::distance::DistanceType::Haversine" + BrayCurtis "cuvs::distance::DistanceType::BrayCurtis" + JensenShannon "cuvs::distance::DistanceType::JensenShannon" + HammingUnexpanded "cuvs::distance::DistanceType::HammingUnexpanded" + KLDivergence "cuvs::distance::DistanceType::KLDivergence" + RusselRaoExpanded "cuvs::distance::DistanceType::RusselRaoExpanded" + DiceExpanded "cuvs::distance::DistanceType::DiceExpanded" + cdef extern from "cuml/cluster/kmeans.hpp" namespace \ - "ML::kmeans::KMeansParams": + "cuvs::cluster::kmeans::params": enum InitMethod: KMeansPlusPlus, Random, Array - - cdef struct KMeansParams: +cdef extern from "cuvs/cluster/kmeans.hpp" namespace \ + "cuvs::cluster::kmeans": + cdef struct params: int n_clusters, InitMethod init int max_iter, diff --git a/python/cuml/cuml/neighbors/ann.pxd b/python/cuml/cuml/neighbors/ann.pxd index 8819794b8f..f98e26b7ce 100644 --- a/python/cuml/cuml/neighbors/ann.pxd +++ b/python/cuml/cuml/neighbors/ann.pxd @@ -1,5 +1,5 @@ # -# Copyright (c) 2019-2021, NVIDIA CORPORATION. +# Copyright (c) 2019-2024, NVIDIA CORPORATION. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -21,8 +21,8 @@ from libc.stdint cimport uintptr_t from libcpp cimport bool -cdef extern from "raft/spatial/knn/ann_common.h" \ - namespace "raft::spatial::knn": +cdef extern from "cuml/neighbors/knn.hpp" \ + namespace "ML": cdef cppclass knnIndex: pass @@ -30,15 +30,6 @@ cdef extern from "raft/spatial/knn/ann_common.h" \ cdef cppclass knnIndexParam: pass - ctypedef enum QuantizerType: - QT_8bit, - QT_4bit, - QT_8bit_uniform, - QT_4bit_uniform, - QT_fp16, - QT_8bit_direct, - QT_6bit - cdef cppclass IVFParam(knnIndexParam): int nlist int nprobe diff --git a/python/cuml/cuml/tests/test_nearest_neighbors.py b/python/cuml/cuml/tests/test_nearest_neighbors.py index 9f5764a7e9..aa612b7763 100644 --- a/python/cuml/cuml/tests/test_nearest_neighbors.py +++ b/python/cuml/cuml/tests/test_nearest_neighbors.py @@ -573,12 +573,14 @@ def test_nearest_neighbors_rbc(distance_dims, n_neighbors, nrows): X[:query_rows, :], n_neighbors=n_neighbors ) - assert len(brute_d[brute_d != rbc_d]) == 0 + cp.testing.assert_allclose(brute_d, rbc_d, atol=1e-3, rtol=1e-3) # All the distances match so allow a couple mismatched indices # through from potential non-determinism in exact matching # distances - assert len(brute_i[brute_i != rbc_i]) <= 3 + assert ( + len(brute_i[brute_i != rbc_i]) <= 3 if distance != "haversine" else 10 + ) @pytest.mark.parametrize("metric", valid_metrics_sparse()) diff --git a/python/cuml/pyproject.toml b/python/cuml/pyproject.toml index 228cb92b5c..899baf535d 100644 --- a/python/cuml/pyproject.toml +++ b/python/cuml/pyproject.toml @@ -82,6 +82,7 @@ requires-python = ">=3.10" dependencies = [ "cudf==24.10.*,>=0.0.0a0", "cupy-cuda11x>=12.0.0", + "cuvs==24.10.*,>=0.0.0a0", "dask-cuda==24.10.*,>=0.0.0a0", "dask-cudf==24.10.*,>=0.0.0a0", "joblib>=0.11", @@ -164,6 +165,7 @@ matrix-entry = "cuda_suffixed=true;use_cuda_wheels=true" requires = [ "cmake>=3.26.4,!=3.30.0", "cuda-python", + "cuvs==24.10.*,>=0.0.0a0", "cython>=3.0.0", "ninja", "pylibraft==24.10.*,>=0.0.0a0", From 9b8ebbc7b2b7bc74d3500fe2bb4821ffe3d20265 Mon Sep 17 00:00:00 2001 From: Ray Douglass Date: Wed, 9 Oct 2024 09:38:48 -0400 Subject: [PATCH 2/2] Update Changelog [skip ci] --- CHANGELOG.md | 55 ++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 55 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index fb2ee90fa8..b7b682bea6 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,58 @@ +# cuml 24.10.00 (9 Oct 2024) + +## 🚨 Breaking Changes + +- Remove old dask-glm based logistic regression ([#6028](https://github.com/rapidsai/cuml/pull/6028)) [@dantegd](https://github.com/dantegd) + +## 🐛 Bug Fixes + +- Fix train_test_split for string columns ([#6088](https://github.com/rapidsai/cuml/pull/6088)) [@dantegd](https://github.com/dantegd) +- Stop shadowing free function ([#6076](https://github.com/rapidsai/cuml/pull/6076)) [@vyasr](https://github.com/vyasr) +- Set default values for conftest options. ([#6067](https://github.com/rapidsai/cuml/pull/6067)) [@bdice](https://github.com/bdice) +- Add license file to conda packages ([#6061](https://github.com/rapidsai/cuml/pull/6061)) [@raydouglass](https://github.com/raydouglass) +- Fix np.NAN to np.nan. ([#6056](https://github.com/rapidsai/cuml/pull/6056)) [@bdice](https://github.com/bdice) +- Reenable `pytest cuml-dask` for CUDA 12.5 wheel CI tests ([#6051](https://github.com/rapidsai/cuml/pull/6051)) [@divyegala](https://github.com/divyegala) +- Fix for `simplicial_set_embedding` ([#6043](https://github.com/rapidsai/cuml/pull/6043)) [@viclafargue](https://github.com/viclafargue) +- MAINT: Allow for error message to contain ``np.float32(1.0)`` ([#6030](https://github.com/rapidsai/cuml/pull/6030)) [@seberg](https://github.com/seberg) +- Stop exporting fill_k kernel as that causes ODR violations ([#6021](https://github.com/rapidsai/cuml/pull/6021)) [@robertmaynard](https://github.com/robertmaynard) +- Avoid cudf column APIs after cudf.Series disallows column inputs ([#6019](https://github.com/rapidsai/cuml/pull/6019)) [@mroeschke](https://github.com/mroeschke) +- Use HDBSCAN package pin to `0.8.38` ([#5906](https://github.com/rapidsai/cuml/pull/5906)) [@divyegala](https://github.com/divyegala) + +## 📖 Documentation + +- Update UMAP doc ([#6064](https://github.com/rapidsai/cuml/pull/6064)) [@viclafargue](https://github.com/viclafargue) +- Update README in experimental FIL ([#6052](https://github.com/rapidsai/cuml/pull/6052)) [@hcho3](https://github.com/hcho3) +- add docs for simplicial_set ([#6042](https://github.com/rapidsai/cuml/pull/6042)) [@Intron7](https://github.com/Intron7) + +## 🚀 New Features + +- TSNE CPU/GPU Interop ([#6063](https://github.com/rapidsai/cuml/pull/6063)) [@divyegala](https://github.com/divyegala) +- Enable GPU `fit` and CPU `transform` in UMAP ([#6032](https://github.com/rapidsai/cuml/pull/6032)) [@divyegala](https://github.com/divyegala) + +## 🛠️ Improvements + +- Migrate to use cuVS for vector search ([#6085](https://github.com/rapidsai/cuml/pull/6085)) [@benfred](https://github.com/benfred) +- Support all-zeroes feature vectors for MG sparse logistic regression ([#6082](https://github.com/rapidsai/cuml/pull/6082)) [@lijinf2](https://github.com/lijinf2) +- Update update-version.sh to use packaging lib ([#6081](https://github.com/rapidsai/cuml/pull/6081)) [@AyodeAwe](https://github.com/AyodeAwe) +- Use CI workflow branch 'branch-24.10' again ([#6072](https://github.com/rapidsai/cuml/pull/6072)) [@jameslamb](https://github.com/jameslamb) +- Update fmt (to 11.0.2) and spdlog (to 1.14.1), add those libraries to libcuml conda host dependencies ([#6071](https://github.com/rapidsai/cuml/pull/6071)) [@jameslamb](https://github.com/jameslamb) +- Update flake8 to 7.1.1. ([#6070](https://github.com/rapidsai/cuml/pull/6070)) [@bdice](https://github.com/bdice) +- Add support for Python 3.12, update to umap-learn==0.5.6 ([#6060](https://github.com/rapidsai/cuml/pull/6060)) [@jameslamb](https://github.com/jameslamb) +- Fix compiler warning about signed vs unsigned ints ([#6053](https://github.com/rapidsai/cuml/pull/6053)) [@hcho3](https://github.com/hcho3) +- Update rapidsai/pre-commit-hooks ([#6048](https://github.com/rapidsai/cuml/pull/6048)) [@KyleFromNVIDIA](https://github.com/KyleFromNVIDIA) +- Drop Python 3.9 support ([#6040](https://github.com/rapidsai/cuml/pull/6040)) [@jameslamb](https://github.com/jameslamb) +- Add use_cuda_wheels matrix entry ([#6038](https://github.com/rapidsai/cuml/pull/6038)) [@KyleFromNVIDIA](https://github.com/KyleFromNVIDIA) +- Switch debug build to RelWithDebInfo ([#6033](https://github.com/rapidsai/cuml/pull/6033)) [@rongou](https://github.com/rongou) +- Remove NumPy <2 pin ([#6031](https://github.com/rapidsai/cuml/pull/6031)) [@seberg](https://github.com/seberg) +- Remove old dask-glm based logistic regression ([#6028](https://github.com/rapidsai/cuml/pull/6028)) [@dantegd](https://github.com/dantegd) +- [FEA] UMAP API for building with batched NN Descent ([#6022](https://github.com/rapidsai/cuml/pull/6022)) [@jinsolp](https://github.com/jinsolp) +- Enabling CPU/GPU interop for SVM, DBSCAN and KMeans ([#6020](https://github.com/rapidsai/cuml/pull/6020)) [@viclafargue](https://github.com/viclafargue) +- Update pre-commit hooks ([#6016](https://github.com/rapidsai/cuml/pull/6016)) [@KyleFromNVIDIA](https://github.com/KyleFromNVIDIA) +- Improve update-version.sh ([#6014](https://github.com/rapidsai/cuml/pull/6014)) [@bdice](https://github.com/bdice) +- Use tool.scikit-build.cmake.version, set scikit-build-core minimum-version ([#6012](https://github.com/rapidsai/cuml/pull/6012)) [@jameslamb](https://github.com/jameslamb) +- Merge branch-24.08 into branch-24.10 ([#5981](https://github.com/rapidsai/cuml/pull/5981)) [@jameslamb](https://github.com/jameslamb) +- Use CUDA math wheels ([#5966](https://github.com/rapidsai/cuml/pull/5966)) [@KyleFromNVIDIA](https://github.com/KyleFromNVIDIA) + # cuml 24.08.00 (7 Aug 2024) ## 🐛 Bug Fixes