sycl_interop_buffer cpp

Intel® oneAPI Deep Neural Network Developer Guide and Reference

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ID 768875

Date 6/20/2024

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sycl_interop_buffer cpp

Annotated version: Getting started on both CPU and GPU with SYCL extensions API

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* Copyright 2019-2023 Intel Corporation
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* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
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*     http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
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// [Prologue]

#include "example_utils.hpp"
#include "oneapi/dnnl/dnnl.hpp"
#include "oneapi/dnnl/dnnl_debug.h"
#include "oneapi/dnnl/dnnl_sycl.hpp"

#if __has_include(<sycl/sycl.hpp>)
#include <sycl/sycl.hpp>
#elif __has_include(<CL/sycl.hpp>)
#include <CL/sycl.hpp>
#else
#error "Unsupported compiler"
#endif

#include <cassert>
#include <iostream>
#include <numeric>

using namespace dnnl;
using namespace sycl;
// [Prologue]

class kernel_tag;

void sycl_interop_buffer_tutorial(engine::kind engine_kind) {

    // [Initialize engine]
    engine eng(engine_kind, 0);
    // [Initialize engine]

    // [Initialize stream]
    dnnl::stream strm(eng);
    // [Initialize stream]

    //  [memory alloc]
    memory::dims tz_dims = {2, 3, 4, 5};
    const size_t N = std::accumulate(tz_dims.begin(), tz_dims.end(), (size_t)1,
            std::multiplies<size_t>());

    memory::desc mem_d(
            tz_dims, memory::data_type::f32, memory::format_tag::nchw);

    memory mem = sycl_interop::make_memory(
            mem_d, eng, sycl_interop::memory_kind::buffer);
    //  [memory alloc]

    // [get sycl buf]
    auto sycl_buf = sycl_interop::get_buffer<float>(mem);
    // [get sycl buf]

    // [sycl kernel exec]
    queue q = sycl_interop::get_queue(strm);
    q.submit([&](handler &cgh) {
        auto a = sycl_buf.get_access<access::mode::write>(cgh);
        cgh.parallel_for<kernel_tag>(range<1>(N), [=](id<1> i) {
            int idx = (int)i[0];
            a[idx] = (idx % 2) ? -idx : idx;
        });
    });
    // [sycl kernel exec]

    //  [relu creation]
    auto relu_pd = eltwise_forward::primitive_desc(eng, prop_kind::forward,
            algorithm::eltwise_relu, mem_d, mem_d, 0.0f);
    auto relu = eltwise_forward(relu_pd);
    //  [relu creation]

    // [relu exec]
    relu.execute(strm, {{DNNL_ARG_SRC, mem}, {DNNL_ARG_DST, mem}});
    strm.wait();
    // [relu exec]

    // [Check the results]
    auto host_acc = sycl_buf.get_host_access();
    for (size_t i = 0; i < N; i++) {
        float exp_value = (i % 2) ? 0.0f : i;
        if (host_acc[i] != (float)exp_value)
            throw std::string(
                    "Unexpected output, find a negative value after the ReLU "
                    "execution.");
    }
    // [Check the results]
}

// [Main]
int main(int argc, char **argv) {
    int exit_code = 0;

    engine::kind engine_kind = parse_engine_kind(argc, argv);
    try {
        sycl_interop_buffer_tutorial(engine_kind);
    } catch (dnnl::error &e) {
        std::cout << "oneDNN error caught: " << std::endl
                  << "\tStatus: " << dnnl_status2str(e.status) << std::endl
                  << "\tMessage: " << e.what() << std::endl;
        exit_code = 1;
    } catch (std::string &e) {
        std::cout << "Error in the example: " << e << "." << std::endl;
        exit_code = 2;
    } catch (exception &e) {
        std::cout << "Error in the example: " << e.what() << "." << std::endl;
        exit_code = 3;
    }

    std::cout << "Example " << (exit_code ? "failed" : "passed") << " on "
              << engine_kind2str_upper(engine_kind) << "." << std::endl;
    finalize();
    return exit_code;
}
// [Main]

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Intel® oneAPI Deep Neural Network Developer Guide and Reference

sycl_interop_buffer cpp