/*******************************************************************************
* Copyright 2017-2022 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 CPU_REF_SUM_HPP
#define CPU_REF_SUM_HPP

#include "common/engine.hpp"
#include "common/memory_tracking.hpp"
#include "common/primitive.hpp"
#include "common/reorder.hpp"
#include "common/reorder_pd.hpp"

#include "cpu/cpu_sum_pd.hpp"

namespace dnnl {
namespace impl {
namespace cpu {

struct ref_sum_t : public primitive_t {
    struct pd_t : public cpu_sum_pd_t {
        using cpu_sum_pd_t::cpu_sum_pd_t;

        pd_t(const pd_t &rhs) = default;

        DECLARE_SUM_PD_T("ref:any", ref_sum_t);

        status_t init(engine_t *engine) {
            bool ok = cpu_sum_pd_t::init(engine) == status::success;
            if (!ok) return status::unimplemented;

            if (has_zero_dim_memory()) return status::success;

            reorder_pds_.resize(n_ + need_output_reorder());
            for (int i = 0; i < n_; ++i) {
                primitive_attr_t r_attr;
                r_attr.scales_.set(DNNL_ARG_SRC, 0);
                if (i != 0) r_attr.post_ops_.append_sum(1.0);
                CHECK(reorder_primitive_desc_create(reorder_pds_[i], engine,
                        src_md(i), dst_acc_md(), &r_attr));
            }

            if (need_output_reorder()) {
                CHECK(reorder_primitive_desc_create(
                        reorder_pds_[n_], engine, dst_acc_md(), dst_md()));
            }

            init_scratchpad();
            return status::success;
        }

        std::vector<std::shared_ptr<primitive_desc_t>> reorder_pds_;

    private:
        void init_scratchpad() {
            using namespace memory_tracking::names;
            auto scratchpad = scratchpad_registry().registrar();
            if (need_output_reorder()) {
                const memory_desc_wrapper dst_acc_d(dst_acc_md());
                scratchpad.book(key_sum_reduction, dst_acc_d.size(), 1,
                        dst_acc_d.data_type_size());
            }

            for (size_t i = 0; i < reorder_pds_.size(); i++) {
                scratchpad.book(key_nested_multiple + (int)i,
                        reorder_pds_[i]->scratchpad_registry());
            }
        };
    };

    ref_sum_t(const pd_t *apd) : primitive_t(apd) {}

    status_t init(engine_t *engine) override {
        const size_t n = pd()->reorder_pds_.size();
        reorders_.resize(n);
        for (size_t i = 0; i < n; ++i)
            pd()->reorder_pds_[i]->create_primitive(reorders_[i], engine);

        memory_desc_t scales_md;
        scales_md.ndims = 1;
        scales_md.dims[0] = 1;
        scales_md.data_type = data_type::f32;
        CHECK(memory_desc_init_by_tag(scales_md, format_tag::x));
        const float *scales = pd()->scales();

        scales_mem_.resize(n);
        for (size_t i = 0; i < n; ++i)
            scales_mem_[i] = std::make_shared<memory_t>(get_service_engine(),
                    &scales_md, use_runtime_ptr,
                    const_cast<float *>(&(scales[i])));
        return status::success;
    }

    status_t execute(const exec_ctx_t &ctx) const override {
        using namespace memory_tracking::names;

        if (pd()->has_zero_dim_memory()) return status::success;

        const auto n = pd()->n_inputs();
        exec_args_t r_args;

        auto sum_reduce = pd()->need_output_reorder()
                ? ctx.get_scratchpad_grantor().get_memory_storage(
                        key_sum_reduction)
                : nullptr;
        auto dst = ctx.args().at(DNNL_ARG_DST);
        memory_t acc(
                dst.mem->engine(), pd()->dst_acc_md(), std::move(sum_reduce));
        memory_arg_t dst_acc = {&acc, false};

        /* fix: clang MemorySanitizer: use-of-uninitialized-value */
        if (pd()->need_output_reorder()) {
            const memory_desc_wrapper acc_d(acc.md());
            std::memset(acc.memory_storage()->data_handle(), 0, acc_d.size());
        }

        for (int i = 0; i < n; ++i) {
            r_args[DNNL_ARG_SRC] = ctx.args().at(DNNL_ARG_MULTIPLE_SRC + i);
            r_args[DNNL_ARG_DST] = pd()->need_output_reorder() ? dst_acc : dst;
            r_args[DNNL_ARG_ATTR_SCALES | DNNL_ARG_SRC]
                    = {scales_mem_[i].get(), true};

            exec_ctx_t r_ctx(ctx, std::move(r_args));

            nested_scratchpad_t ns(ctx, key_nested_multiple + i, reorders_[i]);
            r_ctx.set_scratchpad_grantor(ns.grantor());
            reorders_[i]->execute(r_ctx);
        }

        if (pd()->need_output_reorder()) {
            dst_acc = {&acc, true};
            r_args[DNNL_ARG_SRC] = dst_acc;
            r_args[DNNL_ARG_DST] = dst;
            exec_ctx_t r_ctx(ctx, std::move(r_args));

            nested_scratchpad_t ns(ctx, key_nested_multiple + n, reorders_[n]);
            r_ctx.set_scratchpad_grantor(ns.grantor());
            reorders_[n]->execute(r_ctx);
        }
        return status::success;
    }

private:
    const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }
    std::vector<std::shared_ptr<primitive_t>> reorders_;
    std::vector<std::shared_ptr<memory_t>> scales_mem_;
};

} // namespace cpu
} // namespace impl
} // namespace dnnl

#endif
