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initial commit for adding boost lib #2985

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initial commit for adding boost lib #2985

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2dc78c7
initial commit for adding boost lib
Alexandr-Solovev Nov 20, 2024
4c88001
add eigen lib
Alexandr-Solovev Nov 21, 2024
6f75e43
minor fix
Alexandr-Solovev Nov 21, 2024
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16 changes: 16 additions & 0 deletions WORKSPACE
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Expand Up @@ -106,13 +106,29 @@ onedal_repo(
root_env_var = "DALROOT",
)

http_archive(
name = "boost",
url = "https://archives.boost.io/release/1.86.0/source/boost_1_86_0.tar.gz",
sha256 = "2575e74ffc3ef1cd0babac2c1ee8bdb5782a0ee672b1912da40e5b4b591ca01f",
strip_prefix = "boost_1_86_0",
build_file = "@onedal//dev/bazel/deps:boost.tpl.BUILD",
)

http_archive(
name = "catch2",
url = "https://github.com/catchorg/Catch2/archive/v3.7.1.tar.gz",
sha256 = "c991b247a1a0d7bb9c39aa35faf0fe9e19764213f28ffba3109388e62ee0269c",
strip_prefix = "Catch2-3.7.1",
)

http_archive(
name = "eigen",
url = "https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.tar.gz",
sha256 = "8586084f71f9bde545ee7fa6d00288b264a2b7ac3607b974e54d13e7162c1c72",
build_file = "@onedal//dev/bazel/deps:eigen.tpl.BUILD",
strip_prefix = "eigen-3.4.0",
)

http_archive(
name = "fmt",
url = "https://github.com/fmtlib/fmt/archive/11.0.2.tar.gz",
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41 changes: 41 additions & 0 deletions cpp/oneapi/dal/backend/primitives/lapack/test/syevd_dpc.cpp
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Expand Up @@ -128,6 +128,46 @@ class syevd_test : public te::float_algo_fixture<Float> {
}
}

void check_eigvals_with_eigen(const la::matrix<Float>& s,
const la::matrix<Float>& eigvecs,
const la::matrix<Float>& eigvals) const {
INFO("convert results to float64");
const auto s_f64 = la::astype<double>(s);
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As an alternative, perhaps the input values could be hard-coded along with the solutions instead of checking them against a different library.

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Yes, but with this solution there is no opportunity to use random generated data(I mean extend tests with for example row_count = GENERATE(3, 28, 125, 256);) and also it will be complicated to check results for big datasets

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How about putting them in the existing folders with .csv files that have data and expected results?

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It's possible, but let's say for pca it's necessary to contain gold eigenvectors, eigenvalues, and it will increase the total size of the repo, especially with big datasets. I see no reasons to avoid this pr tbh

const auto eigvals_f64 = la::astype<double>(eigvals);
const auto eigvecs_f64 = la::astype<double>(eigvecs);
std::int64_t row_count = s.get_row_count();
std::int64_t column_count = s.get_column_count();
const Float* data = s.get_data();

Eigen::Matrix<Float, Eigen::Dynamic, Eigen::Dynamic> eigen_matrix(row_count, column_count);
for (int i = 0; i < eigen_matrix.rows(); ++i) {
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An Eigen matrix can also be created from a non-owned pointer for float/double data. I think something along the lines of Eigen::map< Eigen::Matrix<info, incl. row/col major> , alignment, stride >.

for (int j = 0; j < eigen_matrix.cols(); ++j) {
eigen_matrix(i, j) = data[i * column_count + j];
}
}

Eigen::SelfAdjointEigenSolver<Eigen::Matrix<Float, Eigen::Dynamic, Eigen::Dynamic>> es(
eigen_matrix);

auto eigenvalues = es.eigenvalues().real();
INFO("oneDAL eigvals vs Eigen eigvals");
la::enumerate_linear(eigvals_f64, [&](std::int64_t i, Float x) {
REQUIRE(abs(eigvals_f64.get(i) - eigenvalues(i)) < 0.1);
});

INFO("oneDAL eigvectors vs Eigen eigvectors");
auto eigenvectors = es.eigenvectors().real();

const double* eigenvec_ptr = eigvecs_f64.get_data();
//TODO: investigate Eigen classes and align checking between oneDAL and Eigen classes.
for (int j = 0; j < eigvecs.get_column_count(); ++j) {
auto column_eigen = eigenvectors.col(j);
for (int i = 0; i < eigvecs.get_row_count(); ++i) {
REQUIRE((abs(eigenvec_ptr[j * row_count + i]) - abs(column_eigen(i))) < 0.1);
}
}
}

void check_eigvals_are_ascending(const la::matrix<Float>& eigvals) const {
INFO("check eigenvalues order is ascending");
la::enumerate_linear(eigvals, [&](std::int64_t i, Float x) {
Expand Down Expand Up @@ -158,6 +198,7 @@ TEMPLATE_LIST_TEST_M(syevd_test, "test syevd with pos def matrix", "[sym_eigvals

this->check_eigvals_definition(s, eigenvectors, eigenvalues);
this->check_eigvals_are_ascending(eigenvalues);
this->check_eigvals_with_eigen(s, eigenvectors, eigenvalues);
}

TEMPLATE_LIST_TEST_M(syevd_test, "test syevd with pos def matrix 2", "[sym_eigvals]", eigen_types) {
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2 changes: 2 additions & 0 deletions cpp/oneapi/dal/test/engine/BUILD
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Expand Up @@ -22,7 +22,9 @@ dal_test_module(
"@onedal//cpp/oneapi/dal/test/engine/metrics",
],
extra_deps = [
"@boost//:boost",
"@catch2//:catch2",
"@eigen//:eigen",
"@fmt//:fmt",
],
)
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5 changes: 5 additions & 0 deletions cpp/oneapi/dal/test/engine/common.hpp
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Expand Up @@ -22,6 +22,11 @@
#include <type_traits>

#include <fmt/core.h>
//Necessary headers from boost
#include <boost/process.hpp>

#include <Eigen/Dense>
#include <Eigen/Eigenvalues>

#include "oneapi/dal/train.hpp"
#include "oneapi/dal/infer.hpp"
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18 changes: 18 additions & 0 deletions dev/bazel/deps/boost.tpl.BUILD
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@@ -0,0 +1,18 @@
package(default_visibility = ["//visibility:public"])

cc_library(
name = "boost",
srcs = glob([
"libs/libboost*.a",
]),
hdrs = glob([
"boost/**/*.h",
"boost/**/*.hpp",
"boost/**/*.ipp",
]),
includes = [
".",
],
visibility = ["//visibility:public"],
)

8 changes: 8 additions & 0 deletions dev/bazel/deps/eigen.tpl.BUILD
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@@ -0,0 +1,8 @@
package(default_visibility = ["//visibility:public"])

cc_library(
name = "eigen",
hdrs = glob(["Eigen/**"]),
includes = [""],
visibility = ["//visibility:public"],
)
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