onednn-src 0.1.13

/*******************************************************************************
* Copyright 2021 Intel Corporation
* Copyright 2024 FUJITSU LIMITED
* Copyright 2025 Arm Ltd. and affiliates
*
* 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_AARCH64_JIT_BRGEMM_1X1_CONV_HPP
#define CPU_AARCH64_JIT_BRGEMM_1X1_CONV_HPP

#include "common/c_types_map.hpp"
#include "common/dnnl_thread.hpp"
#include "common/memory_tracking.hpp"
#include "common/primitive.hpp"
#include "common/utils.hpp"

#include "cpu/cpu_convolution_pd.hpp"
#include "cpu/platform.hpp"

#include "cpu/aarch64/brgemm/brgemm.hpp"
#include "cpu/aarch64/brgemm/brgemm_containers.hpp"
#include "cpu/aarch64/cpu_barrier.hpp"
#include "cpu/aarch64/cpu_reducer.hpp"
#include "cpu/aarch64/jit_brgemm_conv_trans_kernel.hpp"
#include "cpu/aarch64/jit_brgemm_conv_utils.hpp"
#include "cpu/aarch64/jit_brgemm_post_ops.hpp"

namespace dnnl {
namespace impl {
namespace cpu {
namespace aarch64 {

template <cpu_isa_t isa>
struct brgemm_1x1_convolution_fwd_t : public primitive_t {
    struct pd_t : public cpu_convolution_fwd_pd_t {
        using cpu_convolution_fwd_pd_t::cpu_convolution_fwd_pd_t;

        DECLARE_COMMON_PD_T(JIT_IMPL_NAME_HELPER("brgconv_1x1:", isa, ""),
                brgemm_1x1_convolution_fwd_t);

        status_t init(engine_t *engine);

        std::shared_ptr<brgemm_containers::brgemm_desc_container_t> brgs_;
        bool with_sum = false;
        float sum_scale = 0.f;

        bool need_postwork;
        int ic_chunks;

        jit_brgemm_conv_conf_t jcp_ = utils::zero<decltype(jcp_)>();

    protected:
        bool zero_points_ok() const {
            const auto &zp = attr()->zero_points_;

            if (!zp.has_default_values(DNNL_ARG_SRC)) {
                int mask_src = zp.get_mask(DNNL_ARG_SRC);
                const bool ok = mask_src == 0;
                if (!ok) return false;
            }
            if (!zp.has_default_values(DNNL_ARG_DST)) {
                int mask_dst = zp.get_mask(DNNL_ARG_DST);
                const bool ok = mask_dst == 0;
                if (!ok) return false;
            }

            return zp.has_default_values(DNNL_ARG_WEIGHTS);
        }
    };

    brgemm_1x1_convolution_fwd_t(const pd_t *apd)
        : primitive_t(apd), bias_d(pd()->weights_md(1)) {}

    ~brgemm_1x1_convolution_fwd_t() override = default;

    status_t execute(const exec_ctx_t &ctx) const override {
        execute_forward_all(ctx);

        if (pd()->wants_zero_pad_dst()) ctx.memory(DNNL_ARG_DST)->zero_pad(ctx);

        return status::success;
    }

protected:
    status_t init(engine_t *engine) override;

private:
    //  brgemm convolution execution context
    struct brgemm_exec_ctx_t {
        brgemm_exec_ctx_t(const exec_ctx_t &ctx, const pd_t *pd)
            : src(CTX_IN_MEM(const char *, DNNL_ARG_SRC))
            , weights(CTX_IN_MEM(const char *, DNNL_ARG_WEIGHTS))
            , bias(CTX_IN_MEM(const char *, DNNL_ARG_BIAS))
            , dst(CTX_OUT_MEM(char *, DNNL_ARG_DST))
            , post_ops_binary_rhs_arg_vec(binary_injector::prepare_binary_args(
                      pd->attr()->post_ops_, ctx)) {}
        const char *const __restrict src;
        const char *const __restrict weights;
        const char *const __restrict bias;
        char *const __restrict dst;
        const std::vector<const void *> post_ops_binary_rhs_arg_vec;
    };

    void maybe_rtus(int ithr, const char *__restrict src,
            char *__restrict inp_buffer, uint8_t *__restrict inp_buffer_mask,
            int g, int n, int icc, int od, int oh, int ow) const;
    void exec_ker(const brgemm_exec_ctx_t &brgemm_ctx, int ithr,
            brgemm_batch_element_t *const __restrict brg_batch,
            char *const c_buffer, const char *inp_buffer, int g, int n, int ocb,
            int od, int oh, int ow, int icc, int *last_brg_idx,
            const float *oscales, int32_t src_zp_vals, int32_t *src_zp_comp,
            const int32_t *dst_zero_points, int32_t *s8s8_compensation,
            const float *dst_scales) const;
    status_t execute_forward_all(const exec_ctx_t &ctx) const;
    const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }

    static int get_brg_idx(bool do_initialization, int is_M_tail,
            bool is_N_tail, bool is_K_tail) {
        return (((int)do_initialization * 2 + (int)is_M_tail) * 2
                       + (int)is_N_tail)
                * 2
                + (int)is_K_tail;
    }

    static int get_ker_po_idx(int is_M_tail, bool is_N_tail) {
        return (int)is_M_tail * 2 + (int)is_N_tail;
    }

    brgemm_containers::brgemm_kernel_container_t brg_kernels_ {16};

    std::unique_ptr<jit_sve_core_brgemm_conv_trans_kernel::
                    jit_sve_core_brgemm_conv_rtus_kernel_t>
            rtus_kernel_;

    const memory_desc_wrapper bias_d;

    int ID, IH, IW, OD, OH, OW, SD, SH, SW;
    size_t bia_dsz, acc_dsz, src_dsz, wei_dsz;
    // const variables used for address calculations
    dim_t src_w_sz, src_h_sz, src_d_sz, dst_w_sz, dst_h_sz, dst_d_sz;
    dim_t wei_g_stride, wei_ic_stride, wei_ocb_stride;
    dim_t wei_kw_stride, wei_kh_stride, wei_kd_stride;
};

} // namespace aarch64
} // namespace cpu
} // namespace impl
} // namespace dnnl

#endif

// vim: et ts=4 sw=4 cindent cino+=l0,\:4,N-s