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implement dpnp.bitwise_count #2308

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1 change: 1 addition & 0 deletions dpnp/backend/extensions/ufunc/CMakeLists.txt
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# *****************************************************************************

set(_elementwise_sources
${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/bitwise_count.cpp
${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/common.cpp
${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/degrees.cpp
${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/fabs.cpp
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//*****************************************************************************
// Copyright (c) 2025, Intel Corporation
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
// - Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// - Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
// THE POSSIBILITY OF SUCH DAMAGE.
//*****************************************************************************

#include <sycl/sycl.hpp>

#include "dpctl4pybind11.hpp"

#include "bitwise_count.hpp"
#include "kernels/elementwise_functions/bitwise_count.hpp"
#include "populate.hpp"

// include a local copy of elementwise common header from dpctl tensor:
// dpctl/tensor/libtensor/source/elementwise_functions/elementwise_functions.hpp
// TODO: replace by including dpctl header once available
#include "../../elementwise_functions/elementwise_functions.hpp"

// dpctl tensor headers
#include "kernels/elementwise_functions/common.hpp"
#include "utils/type_dispatch.hpp"

namespace dpnp::extensions::ufunc
{
namespace py = pybind11;
namespace py_int = dpnp::extensions::py_internal;

namespace impl
{
namespace ew_cmn_ns = dpctl::tensor::kernels::elementwise_common;
namespace td_ns = dpctl::tensor::type_dispatch;

/**
* @brief A factory to define pairs of supported types for which
* sycl::bitwise_count<T> function is available.
*
* @tparam T Type of input vector `a` and of result vector `y`.
*/
template <typename T>
struct OutputType
{
using value_type = typename std::disjunction<
td_ns::TypeMapResultEntry<T, std::uint8_t, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::int8_t, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::uint16_t, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::int16_t, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::uint32_t, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::int32_t, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::uint64_t, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::int64_t, std::uint8_t>,
td_ns::DefaultResultEntry<void>>::result_type;
};

using dpnp::kernels::bitwise_count::BitwiseCountFunctor;

template <typename argT,
typename resT = argT,
unsigned int vec_sz = 4,
unsigned int n_vecs = 2,
bool enable_sg_loadstore = true>
using ContigFunctor =
ew_cmn_ns::UnaryContigFunctor<argT,
resT,
BitwiseCountFunctor<argT, resT>,
vec_sz,
n_vecs,
enable_sg_loadstore>;

template <typename argTy, typename resTy, typename IndexerT>
using StridedFunctor =
ew_cmn_ns::UnaryStridedFunctor<argTy,
resTy,
IndexerT,
BitwiseCountFunctor<argTy, resTy>>;

using ew_cmn_ns::unary_contig_impl_fn_ptr_t;
using ew_cmn_ns::unary_strided_impl_fn_ptr_t;

static unary_contig_impl_fn_ptr_t
bitwise_count_contig_dispatch_vector[td_ns::num_types];
static int bitwise_count_output_typeid_vector[td_ns::num_types];
static unary_strided_impl_fn_ptr_t
bitwise_count_strided_dispatch_vector[td_ns::num_types];

MACRO_POPULATE_DISPATCH_VECTORS(bitwise_count);
} // namespace impl

void init_bitwise_count(py::module_ m)
{
using arrayT = dpctl::tensor::usm_ndarray;
using event_vecT = std::vector<sycl::event>;
{
impl::populate_bitwise_count_dispatch_vectors();
using impl::bitwise_count_contig_dispatch_vector;
using impl::bitwise_count_output_typeid_vector;
using impl::bitwise_count_strided_dispatch_vector;

auto bitwise_count_pyapi = [&](const arrayT &src, const arrayT &dst,
sycl::queue &exec_q,
const event_vecT &depends = {}) {
return py_int::py_unary_ufunc(
src, dst, exec_q, depends, bitwise_count_output_typeid_vector,
bitwise_count_contig_dispatch_vector,
bitwise_count_strided_dispatch_vector);
};
m.def("_bitwise_count", bitwise_count_pyapi, "", py::arg("src"),
py::arg("dst"), py::arg("sycl_queue"),
py::arg("depends") = py::list());

auto bitwise_count_result_type_pyapi = [&](const py::dtype &dtype) {
return py_int::py_unary_ufunc_result_type(
dtype, bitwise_count_output_typeid_vector);
};
m.def("_bitwise_count_result_type", bitwise_count_result_type_pyapi);
}
}
} // namespace dpnp::extensions::ufunc
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//*****************************************************************************
// Copyright (c) 2025, Intel Corporation
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
// - Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// - Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
// THE POSSIBILITY OF SUCH DAMAGE.
//*****************************************************************************

#pragma once

#include <pybind11/pybind11.h>

namespace py = pybind11;

namespace dpnp::extensions::ufunc
{
void init_bitwise_count(py::module_ m);
} // namespace dpnp::extensions::ufunc
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Expand Up @@ -25,6 +25,7 @@

#include <pybind11/pybind11.h>

#include "bitwise_count.hpp"
#include "degrees.hpp"
#include "fabs.hpp"
#include "fix.hpp"
Expand Down Expand Up @@ -52,6 +53,7 @@ namespace dpnp::extensions::ufunc
*/
void init_elementwise_functions(py::module_ m)
{
init_bitwise_count(m);
init_degrees(m);
init_fabs(m);
init_fix(m);
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54 changes: 54 additions & 0 deletions dpnp/backend/kernels/elementwise_functions/bitwise_count.hpp
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//*****************************************************************************
// Copyright (c) 2025, Intel Corporation
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
// - Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// - Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
// THE POSSIBILITY OF SUCH DAMAGE.
//*****************************************************************************

#pragma once

#include <sycl/sycl.hpp>

namespace dpnp::kernels::bitwise_count
{
template <typename argT, typename resT>
struct BitwiseCountFunctor
{
// is function constant for given argT
using is_constant = typename std::false_type;
// constant value, if constant
// constexpr resT constant_value = resT{};
// is function defined for sycl::vec
using supports_vec = typename std::false_type;
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Do we need to have a vector implementation, since sycl::popcount support that?
And we have options here: it can be supported either only for int8_t where no casting is needed or for all integer types through explicit vector casting, like dpctl does:

    template <int vec_sz>
    sycl::vec<resT, vec_sz> operator()(const sycl::vec<argT, vec_sz> &x) const
    {
        if constexpr (std::is_unsigned_v<argT>) {
            auto const &res_vec = sycl::popcount(x);

            using deducedT = typename std::remove_cv_t<
                    std::remove_reference_t<decltype(res_vec)>>::element_type;

            return vec_cast<std::uint8_t, deducedT, vec_sz>(res_vec);
        }
        else {
            auto const &res_vec = sycl::popcount(sycl::abs(x));

            using deducedT = typename std::remove_cv_t<
                    std::remove_reference_t<decltype(res_vec)>>::element_type;

            return vec_cast<std::uint8_t, deducedT, vec_sz>(res_vec);
        }
    }

The question only if any of that will bring performance benefits.

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I would be curious to know as well.

In the dpctl PR which started work on adding vector overloads for unary functions (IntelPython/dpctl#1223), little benefit was found, subgroup store/load seemed to make much more of a difference.

// do both argT and resT support subgroup store/load operation
using supports_sg_loadstore = typename std::true_type;

resT operator()(const argT &x) const
{
if constexpr (std::is_unsigned_v<argT>) {
return sycl::popcount(x);
}
else {
return sycl::popcount(sycl::abs(x));
}
}
};
} // namespace dpnp::kernels::bitwise_count
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