16322011799

Committed 16 Jul 2025 02:17PM UTC coverage: 72.092%. Remained the same

Build # 16322011799

Build Type

Pull #2529

github

Committed by

web-flow

Commit Message

Merge 7b8386ae6 into e2c04695c

Pull Request Pull Request #2529: Remove use of `numpy.testing.suppress_warnings` in tests

Run Details

4899 of 9892 branches covered (49.52%)

Branch coverage included in aggregate %.

18339 of 22342 relevant lines covered (82.08%)

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0.0

/dpnp/backend/kernels/elementwise_functions/fmax.hpp

//*****************************************************************************
// Copyright (c) 2024-2025, 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>

// dpctl tensor headers
#include "utils/math_utils.hpp"
#include "utils/type_utils.hpp"

namespace dpnp::kernels::fmax
{
namespace mu_ns = dpctl::tensor::math_utils;
namespace tu_ns = dpctl::tensor::type_utils;

template <typename argT1, typename argT2, typename resT>
struct FmaxFunctor
{
    using supports_sg_loadstore = std::negation<
        std::disjunction<tu_ns::is_complex<argT1>, tu_ns::is_complex<argT2>>>;
    using supports_vec =
        std::conjunction<std::is_same<argT1, argT2>,
                         std::disjunction<std::is_floating_point<argT1>,
                                          std::is_same<argT1, sycl::half>>>;

    resT operator()(const argT1 &in1, const argT2 &in2) const
    {
        if constexpr (std::is_integral_v<argT1> && std::is_integral_v<argT2>) {
            return in1 >= in2 ? in1 : in2;
        }
        else if constexpr (tu_ns::is_complex<argT1>::value &&
                           tu_ns::is_complex<argT2>::value)
        {
            static_assert(std::is_same_v<argT1, argT2>);

            using realT = typename argT1::value_type;
            const realT in2r = std::real(in2);
            const realT in2i = std::imag(in2);

            if (sycl::isnan(in2r) || sycl::isnan(in2i) ||
                mu_ns::greater_equal_complex<argT1>(in1, in2))
            {
                return in1;
            }
            return in2;
        }
        else {
            return sycl::fmax(in1, in2);
        }
    }

    template <int vec_sz>
    sycl::vec<resT, vec_sz>
        operator()(const sycl::vec<argT1, vec_sz> &in1,
                   const sycl::vec<argT2, vec_sz> &in2) const
    {
        return sycl::fmax(in1, in2);
    }
};
} // namespace dpnp::kernels::fmax

1	//*****************************************************************************
2	// Copyright (c) 2024-2025, Intel Corporation
3	// All rights reserved.
4	//
5	// Redistribution and use in source and binary forms, with or without
6	// modification, are permitted provided that the following conditions are met:
7	// - Redistributions of source code must retain the above copyright notice,
8	// this list of conditions and the following disclaimer.
9	// - Redistributions in binary form must reproduce the above copyright notice,
10	// this list of conditions and the following disclaimer in the documentation
11	// and/or other materials provided with the distribution.
12	//
13	// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
14	// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
15	// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
16	// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
17	// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
18	// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
19	// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
20	// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
21	// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
22	// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
23	// THE POSSIBILITY OF SUCH DAMAGE.
24	//*****************************************************************************
25
26	#pragma once
27
28	#include <sycl/sycl.hpp>
29
30	// dpctl tensor headers
31	#include "utils/math_utils.hpp"
32	#include "utils/type_utils.hpp"
33
34	namespace dpnp::kernels::fmax
35	{
36	namespace mu_ns = dpctl::tensor::math_utils;
37	namespace tu_ns = dpctl::tensor::type_utils;
38
39	template <typename argT1, typename argT2, typename resT>
40	struct FmaxFunctor
41	{
42	using supports_sg_loadstore = std::negation<
43	std::disjunction<tu_ns::is_complex<argT1>, tu_ns::is_complex<argT2>>>;
44	using supports_vec =
45	std::conjunction<std::is_same<argT1, argT2>,
46	std::disjunction<std::is_floating_point<argT1>,
47	std::is_same<argT1, sycl::half>>>;
48
49	resT operator()(const argT1 &in1, const argT2 &in2) const
50	{	×
51	if constexpr (std::is_integral_v<argT1> && std::is_integral_v<argT2>) {	×
52	return in1 >= in2 ? in1 : in2;	×
53	}
54	else if constexpr (tu_ns::is_complex<argT1>::value &&
55	tu_ns::is_complex<argT2>::value)
56	{	×
57	static_assert(std::is_same_v<argT1, argT2>);	×
58
59	using realT = typename argT1::value_type;	×
60	const realT in2r = std::real(in2);	×
61	const realT in2i = std::imag(in2);	×
62
63	if (sycl::isnan(in2r) \|\| sycl::isnan(in2i) \|\|	×
64	mu_ns::greater_equal_complex<argT1>(in1, in2))	×
65	{	×
66	return in1;	×
67	}	×
68	return in2;	×
69	}
70	else {	×
71	return sycl::fmax(in1, in2);	×
72	}	×
73	}	×
74
75	template <int vec_sz>
76	sycl::vec<resT, vec_sz>
77	operator()(const sycl::vec<argT1, vec_sz> &in1,
78	const sycl::vec<argT2, vec_sz> &in2) const
79	{	×
80	return sycl::fmax(in1, in2);	×
81	}	×
82	};
83	} // namespace dpnp::kernels::fmax

IntelPython / dpnp / 16322011799

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