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Merge branch 'uxlfoundation:main' into dev/add_azp_codecov
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@icfaust
icfaust authored Jan 9, 2025
2 parents 2ab7d2c + 45ce38c commit daa0ad4
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3 changes: 3 additions & 0 deletions .clang-format
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@@ -0,0 +1,3 @@
---
DisableFormat: true
...
19 changes: 12 additions & 7 deletions .github/CODEOWNERS
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Validating CODEOWNERS rules …
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@@ -1,25 +1,27 @@
# Infra and tools
.* @napetrov @Alexsandruss @homksei @ahuber21 @ethanglaser
.ci/ @napetrov @Alexsandruss @homksei @ahuber21 @ethanglaser
.github/ @napetrov @Alexsandruss @homksei @ahuber21 @ethanglaser @samir-nasibli @icfaust
.circleci/ @napetrov @Alexsandruss @homksei @ahuber21 @ethanglaser
.github/ @napetrov @Alexsandruss @homksei @ahuber21 @ethanglaser @samir-nasibli @icfaust

# Docs
*.md @maria-Petrova @napetrov @Alexsandruss @samir-nasibli @icfaust @david-cortes-intel
doc/ @maria-Petrova @napetrov @Alexsandruss @samir-nasibli @icfaust @david-cortes-intel
requirements-doc.txt @Alexsandruss @samir-nasibli @icfaust @david-cortes-intel

# DPC++
# sklearnex
onedal/ @Alexsandruss @samir-nasibli @icfaust
sklearnex/ @Alexsandruss @samir-nasibli @icfaust

# Examples
examples/ @maria-Petrova @Alexsandruss @samir-nasibli @napetrov

# Dependencies
setup.py @napetrov @Alexsandruss @samir-nasibli @icfaust
requirements* @napetrov @Alexsandruss @samir-nasibli @homksei @ahuber21 @ethanglaser
dependencies-dev @napetrov @Alexsandruss @samir-nasibli @homksei @ahuber21 @ethanglaser
conda-recipe/ @napetrov @Alexsandruss
dependencies-dev @napetrov @Alexsandruss @samir-nasibli @homksei @ahuber21 @ethanglaser
pyproject.toml @napetrov @Alexsandruss @samir-nasibli @homksei @ahuber21 @ethanglaser
requirements* @napetrov @Alexsandruss @samir-nasibli @homksei @ahuber21 @ethanglaser
setup.* @napetrov @Alexsandruss @samir-nasibli @icfaust

# Model builders
*model_builders* @razdoburdin @ahuber21 @avolkov-intel
Expand All @@ -29,13 +31,16 @@ conda-recipe/ @napetrov @Alexsandruss

# Testing
**/test*.py @Alexsandruss @samir-nasibli @icfaust
deselected_tests.yaml @Alexsandruss @samir-nasibli @icfaust
tests/ @Alexsandruss @samir-nasibli @icfaust

# Distributed
*spmd* @samir-nasibli @ethanglaser

# Scikit-learn patching
# daal4py
daal4py/sklearn/ @Alexsandruss @samir-nasibli @icfaust

# Core
src/ @Alexsandruss @samir-nasibli @icfaust
generator/ @Alexsandruss @samir-nasibli @icfaust
scripts/ @Alexsandruss @samir-nasibli @icfaust
src/ @Alexsandruss @samir-nasibli @icfaust
4 changes: 4 additions & 0 deletions .pre-commit-config.yaml
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Expand Up @@ -25,3 +25,7 @@ repos:
hooks:
- id: isort
language_version: python3.10
- repo: https://github.com/pre-commit/mirrors-clang-format
rev: v14.0.6
hooks:
- id: clang-format
2 changes: 1 addition & 1 deletion dependencies-dev
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Original file line number Diff line number Diff line change
Expand Up @@ -4,4 +4,4 @@ numpy==2.0.1 ; python_version <= '3.9'
numpy==2.2.1 ; python_version > '3.9'
pybind11==2.13.6
cmake==3.31.2
setuptools==75.7.0
setuptools==75.8.0
10 changes: 9 additions & 1 deletion generator/gen_daal4py.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1220,9 +1220,17 @@ def gen_daal4py(dalroot, outdir, version, warn_all=False, no_dist=False, no_stre
algo_path = jp(head_path, "algorithms")
rmtree(head_path, ignore_errors=True)
copytree(orig_path, head_path)
formatfile = jp("src", ".clang-format")
for dirpath, dirnames, filenames in os.walk(algo_path):
for filename in filenames:
call([shutil.which("clang-format"), "-i", jp(dirpath, filename)])
call(
[
shutil.which("clang-format"),
"-i",
jp(dirpath, filename),
"-style=file:" + formatfile,
]
)
iface = cython_interface(algo_path)
iface.read()
print("Generating sources...")
Expand Down
84 changes: 44 additions & 40 deletions onedal/basic_statistics/basic_statistics.cpp
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Expand Up @@ -114,9 +114,9 @@ auto get_onedal_result_options(const py::dict& params) {
struct params2desc {
template <typename Float, typename Method, typename Task>
auto operator()(const py::dict& params) {
auto desc = dal::basic_statistics::descriptor<Float,
Method, dal::basic_statistics::task::compute>()
.set_result_options(get_onedal_result_options(params));
auto desc =
dal::basic_statistics::descriptor<Float, Method, dal::basic_statistics::task::compute>()
.set_result_options(get_onedal_result_options(params));
return desc;
}
};
Expand All @@ -126,54 +126,53 @@ struct params2desc_incremental {
template <typename Float, typename Method, typename Task>
auto operator()(const py::dict& params) {
auto desc = dal::basic_statistics::descriptor<Float,
dal::basic_statistics::method::dense, dal::basic_statistics::task::compute>()
.set_result_options(get_onedal_result_options(params));
dal::basic_statistics::method::dense,
dal::basic_statistics::task::compute>()
.set_result_options(get_onedal_result_options(params));
return desc;
}
};

template <typename Policy, typename Task>
void init_compute_ops(py::module& m) {
m.def("compute", [](
const Policy& policy,
const py::dict& params,
const table& data,
const table& weights) {
m.def(
"compute",
[](const Policy& policy, const py::dict& params, const table& data, const table& weights) {
using namespace dal::basic_statistics;
using input_t = compute_input<Task>;

compute_ops ops(policy, input_t{ data, weights }, params2desc{});
return fptype2t{ method2t{ Task{}, ops } }(params);
}
);
});
}


template <typename Policy, typename Task>
void init_partial_compute_ops(py::module& m) {
using prev_result_t = dal::basic_statistics::partial_compute_result<Task>;
m.def("partial_compute", [](
const Policy& policy,
const py::dict& params,
const prev_result_t& prev,
const table& data,
const table& weights) {
using namespace dal::basic_statistics;
using input_t = partial_compute_input<Task>;
partial_compute_ops ops(policy, input_t{ prev, data, weights }, params2desc_incremental{});
return fptype2t{ method2t{ Task{}, ops } }(params);
}
);
m.def("partial_compute",
[](const Policy& policy,
const py::dict& params,
const prev_result_t& prev,
const table& data,
const table& weights) {
using namespace dal::basic_statistics;
using input_t = partial_compute_input<Task>;
partial_compute_ops ops(policy,
input_t{ prev, data, weights },
params2desc_incremental{});
return fptype2t{ method2t{ Task{}, ops } }(params);
});
}

template <typename Policy, typename Task>
void init_finalize_compute_ops(pybind11::module_& m) {
using namespace dal::basic_statistics;
using input_t = partial_compute_result<Task>;
m.def("finalize_compute", [](const Policy& policy, const pybind11::dict& params, const input_t& data) {
finalize_compute_ops ops(policy, data, params2desc_incremental{});
return fptype2t{ method2t{ Task{}, ops } }(params);
});
m.def("finalize_compute",
[](const Policy& policy, const pybind11::dict& params, const input_t& data) {
finalize_compute_ops ops(policy, data, params2desc_incremental{});
return fptype2t{ method2t{ Task{}, ops } }(params);
});
}

template <typename Task>
Expand Down Expand Up @@ -216,23 +215,28 @@ void init_partial_compute_result(py::module_& m) {
py::cast<py::object>(convert_to_pyobject(res.get_partial_max())),
py::cast<py::object>(convert_to_pyobject(res.get_partial_sum())),
py::cast<py::object>(convert_to_pyobject(res.get_partial_sum_squares())),
py::cast<py::object>(convert_to_pyobject(res.get_partial_sum_squares_centered()))
);
py::cast<py::object>(
convert_to_pyobject(res.get_partial_sum_squares_centered())));
},
[](py::tuple t) {
if (t.size() != 6)
throw std::runtime_error("Invalid state!");
result_t res;
if (py::cast<int>(t[0].attr("size")) != 0) res.set_partial_n_rows(convert_to_table(t[0]));
if (py::cast<int>(t[1].attr("size")) != 0) res.set_partial_min(convert_to_table(t[1]));
if (py::cast<int>(t[2].attr("size")) != 0) res.set_partial_max(convert_to_table(t[2]));
if (py::cast<int>(t[3].attr("size")) != 0) res.set_partial_sum(convert_to_table(t[3]));
if (py::cast<int>(t[4].attr("size")) != 0) res.set_partial_sum_squares(convert_to_table(t[4]));
if (py::cast<int>(t[5].attr("size")) != 0) res.set_partial_sum_squares_centered(convert_to_table(t[5]));

if (py::cast<int>(t[0].attr("size")) != 0)
res.set_partial_n_rows(convert_to_table(t[0]));
if (py::cast<int>(t[1].attr("size")) != 0)
res.set_partial_min(convert_to_table(t[1]));
if (py::cast<int>(t[2].attr("size")) != 0)
res.set_partial_max(convert_to_table(t[2]));
if (py::cast<int>(t[3].attr("size")) != 0)
res.set_partial_sum(convert_to_table(t[3]));
if (py::cast<int>(t[4].attr("size")) != 0)
res.set_partial_sum_squares(convert_to_table(t[4]));
if (py::cast<int>(t[5].attr("size")) != 0)
res.set_partial_sum_squares_centered(convert_to_table(t[5]));

return res;
}
));
}));
}

ONEDAL_PY_DECLARE_INSTANTIATOR(init_compute_result);
Expand Down
20 changes: 9 additions & 11 deletions onedal/cluster/dbscan.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -100,17 +100,15 @@ struct params2desc {

template <typename Policy, typename Task>
void init_compute_ops(py::module_& m) {
m.def("compute",
[](const Policy& policy,
const py::dict& params,
const table& data,
const table& weights) {
using namespace dbscan;
using input_t = compute_input<Task>;

compute_ops ops(policy, input_t{ data, weights }, params2desc{});
return fptype2t{ method2t{ Task{}, ops } }(params);
});
m.def(
"compute",
[](const Policy& policy, const py::dict& params, const table& data, const table& weights) {
using namespace dbscan;
using input_t = compute_input<Task>;

compute_ops ops(policy, input_t{ data, weights }, params2desc{});
return fptype2t{ method2t{ Task{}, ops } }(params);
});
}

template <typename Task>
Expand Down
15 changes: 7 additions & 8 deletions onedal/cluster/kmeans_common.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -23,13 +23,11 @@

#include "onedal/common/pybind11_helpers.hpp"

namespace oneapi::dal::python{
namespace oneapi::dal::python {

namespace kmeans {

bool is_same_clustering(const dal::table& left,
const dal::table& right,
std::int64_t n_clusters) {
bool is_same_clustering(const dal::table& left, const dal::table& right, std::int64_t n_clusters) {
if (!left.has_data() || !right.has_data())
throw std::invalid_argument("Empty input table");

Expand All @@ -39,15 +37,16 @@ bool is_same_clustering(const dal::table& left,
if (left.get_column_count() > 1 || right.get_column_count() > 1)
throw std::length_error("Too many columns in input table");

const auto l_arr = l_acc.pull({0, -1});
const auto r_arr = r_acc.pull({0, -1});
const auto l_arr = l_acc.pull({ 0, -1 });
const auto r_arr = r_acc.pull({ 0, -1 });

if (n_clusters < 1)
throw std::invalid_argument("Invalid number of clusters");

constexpr std::int32_t minus_one = -1;
auto map = dal::array<std::int32_t>::full( //
n_clusters, minus_one);
n_clusters,
minus_one);

auto* const m_ptr = map.get_mutable_data();

Expand Down Expand Up @@ -85,4 +84,4 @@ ONEDAL_PY_INIT_MODULE(kmeans_common) {
sub.def("_is_same_clustering", &kmeans::is_same_clustering);
} // ONEDAL_PY_INIT_MODULE(kmeans_common)

} // namespace oneapi::dal::python::kmeans
} // namespace oneapi::dal::python
12 changes: 6 additions & 6 deletions onedal/common.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -16,12 +16,12 @@

#pragma once

#define OVERFLOW_CHECK_BY_ADDING(type, op1, op2) \
{ \
volatile type r = (op1) + (op2); \
r -= (op1); \
if (!(r == (op2))) \
throw std::runtime_error("Integer overflow by adding"); \
#define OVERFLOW_CHECK_BY_ADDING(type, op1, op2) \
{ \
volatile type r = (op1) + (op2); \
r -= (op1); \
if (!(r == (op2))) \
throw std::runtime_error("Integer overflow by adding"); \
}

#define OVERFLOW_CHECK_BY_MULTIPLICATION(type, op1, op2) \
Expand Down
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