onednn-src 0.1.13

/*******************************************************************************
* Copyright 2023 Intel Corporation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*     http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/

#ifndef GPU_INTEL_REDUCTION_REUSABLE_REF_HPP
#define GPU_INTEL_REDUCTION_REUSABLE_REF_HPP

#include "common/c_types_map.hpp"
#include "common/primitive.hpp"
#include "common/serialization.hpp"
#include "gpu/intel/compute/device_info.hpp"
#include "gpu/intel/compute/dispatch_reusable.hpp"
#include "gpu/intel/primitive.hpp"
#include "gpu/intel/reduction/config.hpp"
#include "gpu/intel/reduction/utils.hpp"

namespace dnnl {
namespace impl {
namespace gpu {
namespace intel {
namespace reduction {

struct ref_key_params_t : trivially_serializable_t<ref_key_params_t> {
    status_t create_generator(const intel::engine_t &engine,
            compute::kernel_bundle_t &bundle) const {
        compute::kernel_ctx_t kernel_ctx;
        CHECK(get_kernel_ctx(kernel_ctx));
        auto status = engine.create_kernel_bundle(
                bundle, get_kernel_names(), kernel_ctx);
        return status;
    }

    const std::vector<const char *> &get_kernel_names() const {
        static const std::vector<const char *> kernel_names
                = {"reusable_ref_reduce"};
        return kernel_names;
    }

    status_t get_kernel_ctx(compute::kernel_ctx_t &) const;

    alg_kind_t alg;
    data_type_t src_dt, dst_dt;
    int32_t threads_per_eu;

    compute::dispatch_compile_params_t params;
};
DNNL_ASSERT_TRIVIALLY_SERIALIZABLE(ref_key_params_t);

struct ref_conf_t {
    ref_conf_t(const subproblem_t &subprb, alg_kind_t alg, data_type_t src_dt,
            data_type_t dst_dt, const compute::device_info_t &device_info,
            gpu_primitive_attr_t *gpu_attr);
    status_t init_dispatcher(const subproblem_t &subprb,
            const intel::engine_t &engine, gpu_primitive_attr_t *gpu_attr);
    ref_key_params_t conf;
    stride_t reduction_stride;
    dim_t reduction_size;
    size_t num_dst_elems; // used for scratchpad initialization
    compute::dispatch_runtime_params_t rt_conf;
};

struct reusable_ref_t : public primitive_t {
    using primitive_t::primitive_t;
    struct pd_t : public reduction::pd_t {
        using reduction::pd_t::pd_t;

        DECLARE_COMMON_PD_T("ocl:reusable:ref", reusable_ref_t);

        status_t init(impl::engine_t *engine) {
            using smask_t = primitive_attr_t::skip_mask_t;
            const auto attr_skip_mask = smask_t::gpu_attr;
            VDISPATCH_REDUCTION_SC(
                    set_default_params(), VERBOSE_UNSUPPORTED_TAG);
            VDISPATCH_REDUCTION(attr()->has_default_values(attr_skip_mask),
                    VERBOSE_UNSUPPORTED_ATTR);
            VDISPATCH_REDUCTION(memory_desc_ndims_ok(src_md(), dst_md()),
                    VERBOSE_INCONSISTENT_NDIMS_WITH_VALS, "src", "dst",
                    src_md()->ndims, dst_md()->ndims);
            VDISPATCH_REDUCTION_SC(attr_.set_default_formats(dst_md(0)),
                    VERBOSE_UNSUPPORTED_TAG);
            CHECK(init_conf(engine));
            init_scratchpad();

            return status::success;
        }

        status_t init_conf(impl::engine_t *engine);
        void init_scratchpad();

        dim_t div = 0;
        std::vector<ref_conf_t> phases;
    };

    status_t init(impl::engine_t *engine) override {
        auto &phases = pd()->phases;

        for (auto &phase : phases) {
            compute::kernel_t kernel;
            CHECK(create_kernel(engine, kernel,
                    phase.conf.get_kernel_names()[0], phase.conf));
            kernels_.push_back(std::move(kernel));
        }
        return status::success;
    }

    status_t execute(const exec_ctx_t &ctx) const override;

private:
    const pd_t *pd() const {
        return reinterpret_cast<const pd_t *>(primitive_t::pd().get());
    }

    std::vector<compute::kernel_t> kernels_;
};

} // namespace reduction
} // namespace intel
} // namespace gpu
} // namespace impl
} // namespace dnnl

#endif