/*******************************************************************************
* Copyright 2017-2021 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.
*******************************************************************************/

#include <assert.h>

#ifdef __INTEL_COMPILER
#include <immintrin.h>
#endif

#include "oneapi/dnnl/dnnl_types.h"

#include "common/c_types_map.hpp"
#include "common/dnnl_thread.hpp"
#include "common/type_helpers.hpp"
#include "common/utils.hpp"

#include "cpu/platform.hpp"

#include "cpu/x64/jit_avx512_common_convolution_winograd.hpp"

#define _64byte_align ((1 << 6) - 1)
#define IS_ALIGNED(byte_blk, byte_align) (((byte_blk) & (byte_align)) == 0)

#ifndef _MSC_VER
#define pragma_unroll _Pragma("unroll")
#else
#define pragma_unroll
#endif

namespace dnnl {
namespace impl {
namespace cpu {
namespace x64 {

using namespace memory_tracking::names;

namespace {

void inline load_ps(float *dest, const float *src_mem) {
#ifdef __INTEL_COMPILER
    assert(IS_ALIGNED(reinterpret_cast<ptrdiff_t>(dest), _64byte_align));
    __m512 *Iv512 = (__m512 *)dest;
    Iv512[0] = _mm512_loadu_ps(src_mem);
#else
    PRAGMA_OMP_SIMD()
    for (int v = 0; v < simd_w; v++)
        dest[v] = src_mem[v];
#endif
}

void inline store_output(float *dest, const float *data, bool streamout) {
#ifdef __INTEL_COMPILER
    if (streamout) {
        assert(IS_ALIGNED(reinterpret_cast<ptrdiff_t>(dest), _64byte_align));
        _mm512_stream_ps(dest, *((__m512 *)data));
    } else
        _mm512_storeu_ps(dest, *((__m512 *)data));
#else
    PRAGMA_OMP_SIMD()
    for (int v = 0; v < simd_w; v++)
        dest[v] = data[v];
#endif
}

void inline accum_output(
        float *dest, float *data, bool streamout, bool with_relu_postsum) {
#ifdef __INTEL_COMPILER
    __m512 _data = _mm512_loadu_ps(data);
    __m512 _dest = _mm512_loadu_ps(dest);
    _data = _mm512_add_ps(_data, _dest);
    if (with_relu_postsum) _data = _mm512_max_ps(_data, _mm512_setzero_ps());
    if (streamout) {
        assert(IS_ALIGNED(reinterpret_cast<ptrdiff_t>(dest), _64byte_align));
        _mm512_stream_ps(dest, _data);
    } else
        _mm512_storeu_ps(dest, _data);
#else
    PRAGMA_OMP_SIMD()
    for (int v = 0; v < simd_w; v++)
        data[v] += dest[v];

    if (with_relu_postsum) {
        PRAGMA_OMP_SIMD()
        for (int v = 0; v < simd_w; v++)
            if (data[v] < 0.f) data[v] = 0.f;
    }

    PRAGMA_OMP_SIMD()
    for (int v = 0; v < simd_w; v++)
        dest[v] = data[v];
#endif
}
} // namespace

using namespace dnnl::impl::status;
using namespace dnnl::impl::utils;

void trans_W_4x4_3x3(float Fw_[6][6][16][16], float F[3][3][16][16]) {
    float Fw[6][16];
    float T[6][3][16];
    float t0[16];
    float t1[16];
    float t2[16];

    for (int j = 0; j < 16; j++) {
#pragma unroll
        for (int i = 0; i < 3; i++) {
            PRAGMA_OMP_SIMD()
            for (int k = 0; k < 16; k++) {
                t0[k] = 0.26890756302521f * F[2][i][j][k];
                t1[k] = -t0[k] - 0.688403361344538f * F[0][i][j][k];
                t2[k] = t0[k] + 0.119514472455649f * F[0][i][j][k];

                T[0][i][k] = 1.13777777777778f * F[0][i][j][k];
                T[1][i][k] = t1[k] - 0.430252100840336f * F[1][i][j][k];
                T[2][i][k] = t1[k] + 0.430252100840336f * F[1][i][j][k];
                T[3][i][k] = t2[k] + 0.179271708683473f * F[1][i][j][k];
                T[4][i][k] = t2[k] - 0.179271708683473f * F[1][i][j][k];
                T[5][i][k] = F[2][i][j][k];
            }
        }
#pragma unroll
        for (int i = 0; i < 6; i++) {
            PRAGMA_OMP_SIMD()
            for (int k = 0; k < 16; k++) {
                t0[k] = 0.26890756302521f * T[i][2][k];
                t1[k] = -t0[k] - 0.688403361344538f * T[i][0][k];
                t2[k] = t0[k] + 0.119514472455649f * T[i][0][k];

                Fw[0][k] = 1.13777777777778f * T[i][0][k];
                Fw[1][k] = t1[k] - 0.430252100840336f * T[i][1][k];
                Fw[2][k] = t1[k] + 0.430252100840336f * T[i][1][k];
                Fw[3][k] = t2[k] + 0.179271708683473f * T[i][1][k];
                Fw[4][k] = t2[k] - 0.179271708683473f * T[i][1][k];
                Fw[5][k] = T[i][2][k];
#pragma unroll
                for (int l = 0; l < 6; l++) {
                    Fw_[i][l][j][k] = Fw[l][k];
                }
            }
        }
    }
}

void trans_O_4x4_3x3(float Mw[6][6][16], float O[4][4][16]) {
    float T[4][6][16];
    float t0[16];
    float t1[16];
    float t2[16];
    float t3[16];

#pragma unroll
    for (int i = 0; i < 6; i++) {
        PRAGMA_OMP_SIMD()
        for (int v = 0; v < 16; v++) {
            t0[v] = Mw[1][i][v] + Mw[2][i][v];
            t1[v] = Mw[3][i][v] + Mw[4][i][v];
            t2[v] = Mw[1][i][v] - Mw[2][i][v];
            t3[v] = Mw[3][i][v] - Mw[4][i][v];

            T[0][i][v] = t0[v] + t1[v] + Mw[0][i][v];
            T[1][i][v] = t2[v] * 0.625f + t3[v] * 1.5f;
            T[2][i][v] = t0[v] * 0.390625f + t1[v] * 2.25f;
            T[3][i][v] = t2[v] * 0.244140625f + t3[v] * 3.375f + Mw[5][i][v];
        }
    }
#pragma unroll
    for (int i = 0; i < 4; i++) {
        PRAGMA_OMP_SIMD()
        for (int v = 0; v < 16; v++) {
            t0[v] = T[i][1][v] + T[i][2][v];
            t1[v] = T[i][3][v] + T[i][4][v];
            t2[v] = T[i][1][v] - T[i][2][v];
            t3[v] = T[i][3][v] - T[i][4][v];

            O[i][0][v] = t0[v] + t1[v] + T[i][0][v];
            O[i][1][v] = t2[v] * 0.625f + t3[v] * 1.5f;
            O[i][2][v] = t0[v] * 0.390625f + t1[v] * 2.25f;
            O[i][3][v] = t2[v] * 0.244140625f + t3[v] * 3.375f + T[i][5][v];
        }
    }
}

void trans_W_3x3_4x4(float Fw[6][6][16], float F[4][6][16]) {
    const float rcp3 = 1.0f / 3.0f;
    const float rcp4 = 1.0f / 4.0f;
    const float rcp6 = 1.0f / 6.0f;
    const float rcp12 = 1.0f / 12.0f;
    const float rcp24 = 1.0f / 24.0f;
    float t0[16];
    float t1[16];
    float t2[16];
    float t3[16];
    float t4[16];
    float T[6][4][16];

    pragma_unroll for (int i = 0; i < 4; i++) {
        PRAGMA_OMP_SIMD()
        for (int j = 0; j < 16; j++) {
            t0[j] = F[2][i][j] * rcp6;
            t1[j] = F[0][i][j] * -rcp6 - t0[j];
            t2[j] = F[0][i][j] * rcp24 + t0[j];
            t3[j] = (F[1][i][j] + F[3][i][j]) * rcp6;
            t4[j] = F[1][i][j] * rcp12 + F[3][i][j] * rcp3;

            T[0][i][j] = F[0][i][j] * rcp4;
            T[1][i][j] = t1[j] - t3[j];
            T[2][i][j] = t1[j] + t3[j];
            T[3][i][j] = t2[j] + t4[j];
            T[4][i][j] = t2[j] - t4[j];
            T[5][i][j] = F[3][i][j];
        }
    }
    pragma_unroll for (int i = 0; i < 6; i++) {
        PRAGMA_OMP_SIMD()
        for (int j = 0; j < 16; j++) {
            t0[j] = T[i][2][j] * rcp6;
            t1[j] = T[i][0][j] * -rcp6 - t0[j];
            t2[j] = T[i][0][j] * rcp24 + t0[j];
            t3[j] = (T[i][1][j] + T[i][3][j]) * rcp6;
            t4[j] = T[i][1][j] * rcp12 + T[i][3][j] * rcp3;

            Fw[i][0][j] = T[i][0][j] * rcp4;
            Fw[i][1][j] = t1[j] - t3[j];
            Fw[i][2][j] = t1[j] + t3[j];
            Fw[i][3][j] = t2[j] + t4[j];
            Fw[i][4][j] = t2[j] - t4[j];
            Fw[i][5][j] = T[i][3][j];
        }
    }
}

void trans_O_3x3_4x4(float Mw[6][6][16][16], float M[3][3][16][16]) {
    float T[4][6][16];
    float M_[3][16];
    float t0[16];
    float t1[16];
    float t2[16];

    for (int j = 0; j < 16; j++) {
        pragma_unroll for (int i = 0; i < 6; i++) {
            PRAGMA_OMP_SIMD()
            for (int l = 0; l < 16; l++) {
                t0[l] = Mw[1][i][j][l] + Mw[2][i][j][l];
                t1[l] = Mw[3][i][j][l] + Mw[4][i][j][l];
                t2[l] = t1[l] * 4.0f + Mw[5][i][j][l];

                T[0][i][l] = Mw[0][i][j][l] + t0[l] + t1[l];
                T[1][i][l] = (Mw[1][i][j][l] - Mw[2][i][j][l])
                        + 2.0f * (Mw[3][i][j][l] - Mw[4][i][j][l]);
                T[2][i][l] = t0[l] + t2[l];
            }
        }
        pragma_unroll for (int i = 0; i < 3; i++) {
            PRAGMA_OMP_SIMD()
            for (int l = 0; l < 16; l++) {
                t0[l] = T[i][1][l] + T[i][2][l];
                t1[l] = T[i][3][l] + T[i][4][l];
                t2[l] = t1[l] * 4.0f + T[i][5][l];

                M_[0][l] = T[i][0][l] + t0[l] + t1[l];
                M_[1][l] = (T[i][1][l] - T[i][2][l])
                        + 2.0f * (T[i][3][l] - T[i][4][l]);
                M_[2][l] = t0[l] + t2[l];

                for (int k = 0; k < 3; k++) {
                    M[i][k][j][l] = M_[k][l];
                }
            }
        }
    }
}

void trans_I_4x4_3x3(float Iw[6][6][16], float I[6][6][16]) {
    float T[6][6][16];
    float t0[16];
    float t1[16];
    float t2[16];
    float t3[16];
    float t4[16];
    float t5[16];

    pragma_unroll for (int i = 0; i < 6; i++) {
        PRAGMA_OMP_SIMD()
        for (int v = 0; v < 16; v++) {
            t0[v] = I[2][i][v] * -2.25f + I[4][i][v];
            t1[v] = I[1][i][v] * -2.25f + I[3][i][v];
            t2[v] = I[2][i][v] * -0.390625f + I[4][i][v];
            t3[v] = I[1][i][v] * -0.390625f + I[3][i][v];
            t4[v] = I[0][i][v] * 0.87890625f + I[4][i][v];
            t5[v] = I[1][i][v] * 0.87890625f + I[5][i][v];

            T[0][i][v] = I[2][i][v] * -2.640625f + t4[v];
            T[1][i][v] = t1[v] * 0.625f + t0[v];
            T[2][i][v] = t1[v] * -0.625f + t0[v];
            T[3][i][v] = t3[v] * 1.5f + t2[v];
            T[4][i][v] = t3[v] * -1.5f + t2[v];
            T[5][i][v] = I[3][i][v] * -2.640625f + t5[v];
        }
    }

    pragma_unroll for (int i = 0; i < 6; i++) {
        PRAGMA_OMP_SIMD()
        for (int v = 0; v < 16; v++) {
            t0[v] = T[i][2][v] * -2.25f + T[i][4][v];
            t1[v] = T[i][1][v] * -2.25f + T[i][3][v];
            t2[v] = T[i][2][v] * -0.390625f + T[i][4][v];
            t3[v] = T[i][1][v] * -0.390625f + T[i][3][v];
            t4[v] = T[i][0][v] * 0.87890625f + T[i][4][v];
            t5[v] = T[i][1][v] * 0.87890625f + T[i][5][v];

            Iw[i][0][v] = T[i][2][v] * -2.640625f + t4[v];
            Iw[i][1][v] = t1[v] * 0.625f + t0[v];
            Iw[i][2][v] = t1[v] * -0.625f + t0[v];
            Iw[i][3][v] = t3[v] * 1.5f + t2[v];
            Iw[i][4][v] = t3[v] * -1.5f + t2[v];
            Iw[i][5][v] = T[i][3][v] * -2.640625f + t5[v];
        }
    }
}

void trans_W_3x3_4x4_wu(float Fw[6][6][16], float F[4][6][16]) {
    float T[6][4][16];
    float t0[16];
    float t1[16];
    float t2[16];
    float t3[16];
    float t4[16];

    pragma_unroll for (int i = 0; i < 4; i++) {
        PRAGMA_OMP_SIMD()
        for (int v = 0; v < 16; v++) {
            t0[v] = F[2][i][v] * 0.26890756302521f;
            t1[v] = F[0][i][v] * -0.688403361344538f - t0[v];
            t2[v] = F[0][i][v] * 0.119514472455649f + t0[v];
            t3[v] = F[1][i][v] * 0.430252100840336f
                    + F[3][i][v] * 0.168067226890756f;
            t4[v] = F[1][i][v] * 0.179271708683473f
                    + F[3][i][v] * 0.403361344537815f;

            T[0][i][v] = F[0][i][v] * 1.13777777777778f;
            T[1][i][v] = t1[v] - t3[v];
            T[2][i][v] = t1[v] + t3[v];
            T[3][i][v] = t2[v] + t4[v];
            T[4][i][v] = t2[v] - t4[v];
            T[5][i][v] = F[3][i][v];
        }
    }
    pragma_unroll for (int i = 0; i < 6; i++) {
        for (int v = 0; v < 16; v++) {
            t0[v] = T[i][2][v] * 0.26890756302521f;
            t1[v] = T[i][0][v] * -0.688403361344538f - t0[v];
            t2[v] = T[i][0][v] * 0.119514472455649f + t0[v];
            t3[v] = T[i][1][v] * 0.430252100840336f
                    + T[i][3][v] * 0.168067226890756f;
            t4[v] = T[i][1][v] * 0.179271708683473f
                    + T[i][3][v] * 0.403361344537815f;

            Fw[i][0][v] = T[i][0][v] * 1.13777777777778f;
            Fw[i][1][v] = t1[v] - t3[v];
            Fw[i][2][v] = t1[v] + t3[v];
            Fw[i][3][v] = t2[v] + t4[v];
            Fw[i][4][v] = t2[v] - t4[v];
            Fw[i][5][v] = T[i][3][v];
        }
    }
}

void trans_O_3x3_4x4_wu(float Mw[6][6][16][16], float M[3][3][16][16]) {
    float T[3][6][16];
    float t0[16];
    float t1[16];
    float t2[16];
    float M_[3][16];

    for (int j = 0; j < 16; j++) {
        pragma_unroll for (int i = 0; i < 6; i++) {
            PRAGMA_OMP_SIMD()
            for (int v = 0; v < 16; v++) {
                t0[v] = Mw[1][i][j][v] + Mw[2][i][j][v];
                t1[v] = Mw[3][i][j][v] + Mw[4][i][j][v];
                t2[v] = t1[v] * 2.25f + Mw[5][i][j][v];

                T[0][i][v] = Mw[0][i][j][v] + t0[v] + t1[v];
                T[1][i][v] = 0.625f * (Mw[1][i][j][v] - Mw[2][i][j][v])
                        + 1.5f * (Mw[3][i][j][v] - Mw[4][i][j][v]);
                T[2][i][v] = t0[v] * 0.390625f + t2[v];
            }
        }
        pragma_unroll for (int i = 0; i < 3; i++) {
            PRAGMA_OMP_SIMD()
            for (int v = 0; v < 16; v++) {
                t0[v] = T[i][1][v] + T[i][2][v];
                t1[v] = T[i][3][v] + T[i][4][v];
                t2[v] = t1[v] * 2.25f + T[i][5][v];

                M_[0][v] = T[i][0][v] + t0[v] + t1[v];
                M_[1][v] = 0.625f * (T[i][1][v] - T[i][2][v])
                        + 1.5f * (T[i][3][v] - T[i][4][v]);
                M_[2][v] = t0[v] * 0.390625f + t2[v];
            }

            pragma_unroll for (int k = 0; k < 3; k++) {
                PRAGMA_OMP_SIMD()
                for (int v = 0; v < 16; v++) {
                    M[i][k][j][v] = M_[k][v];
                }
            }
        }
    }
}

template <bool is_fwd>
void input_transform_data(int image, const jit_conv_winograd_conf_t &jcp,
        float *inp, float *tinp, bool streamout = true) {
    const int inpw = is_fwd ? jcp.iw : jcp.ow;
    const int inph = is_fwd ? jcp.ih : jcp.oh;
    const int l_pad = is_fwd ? jcp.l_pad : jcp.iw + jcp.r_pad - jcp.ow;
    const int t_pad = is_fwd ? jcp.t_pad : jcp.ih + jcp.t_pad - jcp.oh;
    const int wp_max = inpw + l_pad;
    const int hp_max = inph + t_pad;
    alignas(64) float Iw[alpha][alpha][simd_w];
    alignas(64) float I[alpha][alpha][simd_w];

    array_offset_calculator<float, 5> input(
            inp, jcp.mb, jcp.dimK / simd_w, inph, inpw, simd_w);
    array_offset_calculator<float, 8> output(tinp, jcp.dimN_nb_block, alpha,
            alpha, jcp.dimN_block, jcp.dimK_nb_block, jcp.dimK_block,
            jcp.dimN_reg_block, jcp.dimK_reg_block);

    int tile_base_index = image * jcp.itiles * jcp.jtiles;
    int tile_block_ur = tile_base_index % jcp.tile_block_ur;
    int nb_tile_block_ur
            = (tile_base_index / jcp.tile_block_ur) % jcp.nb_tile_block_ur;
    int tile_block
            = (tile_base_index / jcp.tile_block_ur) / jcp.nb_tile_block_ur;

    bool is_access_aligned
            = IS_ALIGNED(reinterpret_cast<ptrdiff_t>(tinp), _64byte_align)
            // check if the inner-most dimension size matches the alignment
            // stride.
            && IS_ALIGNED(jcp.dimK_reg_block * sizeof(float), _64byte_align);

    for (int tj = 0; tj < jcp.jtiles; tj++) {
        for (int ti = 0; ti < jcp.itiles; ti++) {
            for (int j = 0; j < alpha; j++) {
                int ydim = tj * tile_size + j;
                if ((t_pad <= ydim) && (ydim < hp_max)) {
                    float *pinp_j = inp + (ydim - t_pad) * inpw * 16;
                    for (int i = 0; i < alpha; i++) {
                        int xdim = ti * tile_size + i;
                        if ((l_pad <= xdim) && (xdim < wp_max)) {
                            float *pinp_i = pinp_j + (xdim - l_pad) * 16;
                            load_ps(I[j][i], pinp_i);
                        } else {
                            PRAGMA_OMP_SIMD()
                            for (int v = 0; v < simd_w; v++) {
                                I[j][i][v] = 0.0f;
                            }
                        }
                    }
                } else {
                    for (int i = 0; i < alpha; i++) {
                        PRAGMA_OMP_SIMD()
                        for (int v = 0; v < simd_w; v++) {
                            I[j][i][v] = 0.0f;
                        }
                    }
                }
            }

            trans_I_4x4_3x3(Iw, I);

            for (int j = 0; j < alpha; j++) {
                for (int i = 0; i < alpha; i++) {
                    store_output(&(output(tile_block, j, i, nb_tile_block_ur, 0,
                                         0, tile_block_ur, 0)),
                            Iw[j][i], is_access_aligned && streamout);
                }
            }
            tile_block_ur++;
            if (tile_block_ur >= jcp.tile_block_ur) {
                tile_block_ur = 0;
                nb_tile_block_ur++;
            }
            if (nb_tile_block_ur >= jcp.nb_tile_block_ur) {
                nb_tile_block_ur = 0;
                tile_block++;
            }
        }
    }
}

template <bool is_fwd>
void weight_transform_data(
        const jit_conv_winograd_conf_t &jcp, float *wp, float *twp) {
    const int kh = 3;
    const int kw = 3;
    array_offset_calculator<float, 6> input(wp, jcp.oc / jcp.oc_simd_block,
            jcp.ic / jcp.ic_simd_block, jcp.kh, jcp.kw, simd_w, simd_w);
    array_offset_calculator<float, 8> output(twp, jcp.dimM_nb_block, alpha,
            alpha, jcp.dimK_nb_block, jcp.dimM_block, jcp.dimK_block, simd_w,
            simd_w);
    float Fw[alpha][alpha][simd_w][simd_w];
    float F[kh][kw][simd_w][simd_w];

    for (int j = 0; j < kh; j++) {
        for (int i = 0; i < kw; i++) {
            for (int v1 = 0; v1 < simd_w; v1++) {
                float *base_inp = is_fwd ? &(input(0, 0, j, i, v1, 0))
                                         : &(input(0, 0, 2 - j, 2 - i, v1, 0));
                PRAGMA_OMP_SIMD()
                for (int v2 = 0; v2 < simd_w; v2++) {
                    if (is_fwd)
                        F[j][i][v1][v2] = *(base_inp + v2);
                    else
                        F[j][i][v2][v1] = *(base_inp + v2);
                }
            }
        }
    }

    trans_W_4x4_3x3(Fw, F);

    for (int j = 0; j < alpha; j++) {
        for (int i = 0; i < alpha; i++) {
            for (int v1 = 0; v1 < simd_w; v1++) {
                PRAGMA_OMP_SIMD()
                for (int v2 = 0; v2 < simd_w; v2++) {
                    output(0, j, i, 0, 0, 0, v1, v2) = Fw[j][i][v1][v2];
                }
            }
        }
    }
}

template <bool is_fwd, bool with_bias, bool with_relu_presum, bool with_sum>
void output_transform_data(int image, const jit_conv_winograd_conf_t &jcp,
        float *toutp, float *pout_b, float *bias, bool streamout = true) {
    alignas(64) float Ow[alpha][alpha][simd_w];
    alignas(64) float O[tile_size][tile_size][simd_w];
    int outw = is_fwd ? jcp.ow : jcp.iw;
    int outh = is_fwd ? jcp.oh : jcp.ih;

    /* Prepare for PostOps */
    bool with_relu_postsum = jcp.with_eltwise;

    array_offset_calculator<float, 8> input(toutp, jcp.dimN_nb_block,
            jcp.dimM_nb_block, alpha, alpha, jcp.dimN_block, jcp.dimM_block,
            jcp.dimN_reg_block, jcp.dimM_simd_block);

    int tile_base_index = image * jcp.itiles * jcp.jtiles;
    int tile_block_ur = tile_base_index % jcp.tile_block_ur;
    int nb_tile_block_ur
            = (tile_base_index / jcp.tile_block_ur) % jcp.nb_tile_block_ur;
    int tile_block
            = (tile_base_index / jcp.tile_block_ur) / jcp.nb_tile_block_ur;

    for (int tj = 0; tj < jcp.jtiles; tj++) {
        for (int ti = 0; ti < jcp.itiles; ti++) {
            for (int j = 0; j < alpha; j++) {
                for (int i = 0; i < alpha; i++) {
                    PRAGMA_OMP_SIMD()
                    for (int v = 0; v < simd_w; v++) {
                        Ow[j][i][v] = input(tile_block, 0, j, i,
                                nb_tile_block_ur, 0, tile_block_ur, v);
                    }
                }
            }

            trans_O_4x4_3x3(Ow, O);

            for (int j = 0; j < tile_size; j++) {
                int ydim = tj * tile_size + j;
                if (ydim < outh) {
                    dim_t stride_j = ydim * outw * simd_w;
                    float *pout_j = pout_b + stride_j;
                    for (int i = 0; i < tile_size; i++) {
                        int xdim = ti * tile_size + i;
                        if (xdim < outw) {
                            dim_t stride_i = xdim * simd_w;
                            float *pout_i = pout_j + stride_i;
                            bool is_stride_aligned = IS_ALIGNED(
                                    (stride_j + stride_i) * sizeof(float),
                                    _64byte_align);
                            if (is_fwd) {
                                PRAGMA_OMP_SIMD()
                                for (int v = 0; v < simd_w; v++) {
                                    O[j][i][v] += with_bias ? bias[v] : 0.f;
                                    O[j][i][v] = true && with_relu_presum
                                                    && O[j][i][v] < 0.f
                                            ? O[j][i][v] * jcp.eltwise.alpha
                                            : O[j][i][v];
                                }
                            }
                            const bool is_access_aligned
                                    = streamout && is_stride_aligned;
                            if (with_sum)
                                accum_output(pout_i, O[j][i], is_access_aligned,
                                        with_relu_postsum);
                            else
                                store_output(
                                        pout_i, O[j][i], is_access_aligned);
                        }
                    }
                }
            }
            tile_block_ur++;
            if (tile_block_ur >= jcp.tile_block_ur) {
                tile_block_ur = 0;
                nb_tile_block_ur++;
            }
            if (nb_tile_block_ur >= jcp.nb_tile_block_ur) {
                nb_tile_block_ur = 0;
                tile_block++;
            }
        }
    }
}

template <bool ver_4fma>
void diff_src_transform_bwd_weights(int image,
        const jit_conv_winograd_conf_t &conv, float *inp, float *tinp,
        float *Iw_temp, void (*transpose_4fma_ker)(float *, float *)) {

    const int ifwp = conv.iw + conv.l_pad;
    const int ifhp = conv.ih + conv.t_pad;
    alignas(64) float I[alpha][alpha][simd_w];
    alignas(64) float Iw[alpha][alpha][simd_w];

    array_offset_calculator<float, 4> Iw_trans_temp(
            Iw_temp, alpha, alpha, conv.tile_4fma, simd_w);
    array_offset_calculator<float, 5> input(
            inp, conv.mb, conv.ic / simd_w, conv.ih, conv.iw, simd_w);
    array_offset_calculator<float, 8> output(tinp, conv.nb_ic, alpha, alpha,
            conv.tile_block, conv.ic_block, conv.nb_tile_block_ur,
            conv.tile_block_ur, conv.ic_simd_block * conv.tile_4fma);

    int tile_base_index
            = image * (conv.itiles * conv.jtiles + conv.tile_4fma_padding);
    int tile_4fma = 0;
    int tile_block_ur = (tile_base_index / conv.tile_4fma) % conv.tile_block_ur;
    int nb_tile_block_ur
            = (tile_base_index / conv.tile_4fma / conv.tile_block_ur)
            % conv.nb_tile_block_ur;
    int tile_block = (tile_base_index / conv.tile_4fma / conv.tile_block_ur)
            / conv.nb_tile_block_ur;

    bool is_access_aligned
            = IS_ALIGNED(reinterpret_cast<ptrdiff_t>(tinp), _64byte_align)
            // check if the inner-most dimension size matches the alignment
            // stride.
            && IS_ALIGNED(conv.ic_simd_block * conv.tile_4fma * sizeof(float),
                    _64byte_align);

    for (int tj = 0; tj < conv.jtiles; tj++) {
        for (int ti = 0; ti < conv.itiles; ti++) {
            for (int j = 0; j < alpha; j++) {
                int ydim = tj * tile_size + j;
                if ((conv.t_pad <= ydim) && ydim < ifhp) {
                    for (int i = 0; i < alpha; i++) {
                        int xdim = ti * tile_size + i;
                        if ((conv.l_pad <= xdim) && xdim < ifwp) {
                            PRAGMA_OMP_SIMD()
                            for (int v = 0; v < simd_w; v++) {
                                I[j][i][v] = input(0, 0, ydim - conv.t_pad,
                                        xdim - conv.l_pad, v);
                            }
                        } else {
                            PRAGMA_OMP_SIMD()
                            for (int v = 0; v < simd_w; v++) {
                                I[j][i][v] = 0.0f;
                            }
                        }
                    }
                } else {
                    for (int i = 0; i < alpha; i++) {
                        PRAGMA_OMP_SIMD()
                        for (int v = 0; v < simd_w; v++) {
                            I[j][i][v] = 0.0f;
                        }
                    }
                }
            }
            trans_I_4x4_3x3(Iw, I);

            if (ver_4fma) {
                for (int j = 0; j < alpha; j++) {
                    for (int i = 0; i < alpha; i++) {
                        float *Iw_temp_base
                                = &(Iw_trans_temp(j, i, tile_4fma, 0));
                        PRAGMA_OMP_SIMD()
                        for (int v = 0; v < simd_w; v++) {
                            Iw_temp_base[v] = Iw[j][i][v];
                        }
                    }
                }
                tile_4fma++;
                if (tile_4fma == conv.tile_4fma) {
                    float *outp = &(output(0, 0, 0, tile_block, 0,
                            nb_tile_block_ur, tile_block_ur, 0));
                    transpose_4fma_ker(outp, (float *)Iw_temp);
                    tile_4fma = 0;
                    tile_block_ur++;
                }
            } else {
                for (int j = 0; j < alpha; j++) {
                    for (int i = 0; i < alpha; i++) {
                        store_output(
                                &(output(0, j, i, tile_block, 0,
                                        nb_tile_block_ur, tile_block_ur, 0)),
                                Iw[j][i], is_access_aligned);
                    }
                }
                tile_block_ur++;
            }

            if (tile_block_ur == conv.tile_block_ur) {
                tile_block_ur = 0;
                ++nb_tile_block_ur;
            }
            if (nb_tile_block_ur == conv.nb_tile_block_ur) {
                nb_tile_block_ur = 0;
                tile_block++;
            }
        }
    }

    if (ver_4fma && tile_4fma < conv.tile_4fma && conv.tile_4fma_padding != 0) {

        for (int j = 0; j < alpha; j++) {
            for (int i = 0; i < alpha; i++) {
                for (int tb = tile_4fma; tb < conv.tile_4fma; tb++) {
                    float *Iw_temp_base = &(Iw_trans_temp(j, i, tb, 0));
                    PRAGMA_OMP_SIMD()
                    for (int v = 0; v < simd_w; v++) {
                        Iw_temp_base[v] = 0;
                    }
                }
            }
        }
        float *outp = &(output(
                0, 0, 0, tile_block, 0, nb_tile_block_ur, tile_block_ur, 0));
        transpose_4fma_ker(outp, (float *)Iw_temp);
    }
}

template <bool with_bias>
void diff_dst_transform_bwd_weights(int image,
        const jit_conv_winograd_conf_t &conv, float *inp, float *tinp,
        float *dbias) {

    const int total_tiles = conv.itiles * conv.jtiles + conv.tile_4fma_padding;
    alignas(64) float I[alpha][alpha][simd_w];
    alignas(64) float Iw[alpha][alpha][simd_w];

    array_offset_calculator<float, 5> input(inp, conv.mb, conv.oc / simd_w,
            conv.oh, conv.ow, conv.oc_simd_block);
    array_offset_calculator<float, 8> output(tinp, conv.nb_oc, alpha, alpha,
            conv.tile_block, conv.oc_block, conv.nb_tile_block_ur,
            conv.tile_block_ur * conv.tile_4fma, conv.oc_simd_block);

    int tile_base_index = image * total_tiles;
    int tile_block_ur = tile_base_index % (conv.tile_block_ur * conv.tile_4fma);
    int nb_tile_block_ur
            = (tile_base_index / conv.tile_block_ur / conv.tile_4fma)
            % conv.nb_tile_block_ur;
    int tile_block = (tile_base_index / conv.tile_block_ur / conv.tile_4fma)
            / conv.nb_tile_block_ur;

    bool is_access_aligned
            = IS_ALIGNED(reinterpret_cast<ptrdiff_t>(tinp), _64byte_align)
            // check if the inner-most dimension size matches the alignment
            // stride.
            && IS_ALIGNED(conv.oc_simd_block * sizeof(float), _64byte_align);

    for (int tj = 0; tj < conv.jtiles; tj++) {
        for (int ti = 0; ti < conv.itiles; ti++) {
            for (int j = 0; j < alpha; j++) {
                int ydim = tj * tile_size + j;
                if (ydim < conv.oh) {
                    for (int i = 0; i < alpha; i++) {
                        int xdim = ti * tile_size + i;
                        if (xdim < conv.ow) {
                            float *input_base = &(input(0, 0, ydim, xdim, 0));

                            PRAGMA_OMP_SIMD()
                            for (int v = 0; v < simd_w; v++) {
                                I[j][i][v] = input_base[v];
                            }
                            if (with_bias && j < tile_size && i < tile_size) {
                                PRAGMA_OMP_SIMD()
                                for (int v = 0; v < simd_w; v++) {
                                    dbias[v] += input_base[v];
                                }
                            }
                        } else {
                            PRAGMA_OMP_SIMD()
                            for (int v = 0; v < simd_w; v++) {
                                I[j][i][v] = 0.0f;
                            }
                        }
                    }
                } else {
                    for (int i = 0; i < alpha; i++) {
                        PRAGMA_OMP_SIMD()
                        for (int v = 0; v < simd_w; v++) {
                            I[j][i][v] = 0.0f;
                        }
                    }
                }
            }

            trans_W_3x3_4x4_wu(Iw, I);

            for (int j = 0; j < alpha; j++) {
                for (int i = 0; i < alpha; i++) {
                    store_output(&(output(0, j, i, tile_block, 0,
                                         nb_tile_block_ur, tile_block_ur, 0)),
                            Iw[j][i], is_access_aligned);
                }
            }
            tile_block_ur++;
            if (tile_block_ur >= conv.tile_block_ur * conv.tile_4fma) {
                tile_block_ur = 0;
                nb_tile_block_ur++;
            }
            if (nb_tile_block_ur >= conv.nb_tile_block_ur) {
                nb_tile_block_ur = 0;
                tile_block++;
            }
        }
    }
}

void diff_weights_transform_bwd_weights(
        const jit_conv_winograd_conf_t &conv, float *wp, float *twp) {
    const int kh = 3;
    const int kw = 3;
    alignas(64) float Fw[alpha][alpha][simd_w][simd_w];
    alignas(64) float F[kh][kw][simd_w][simd_w];

    array_offset_calculator<float, 8> input(twp, conv.nb_ic, conv.nb_oc, alpha,
            alpha, conv.oc_block, conv.ic_block, conv.ic_simd_block,
            conv.oc_simd_block);
    array_offset_calculator<float, 6> output(wp, conv.oc / simd_w,
            conv.ic / simd_w, conv.kh, conv.kw, conv.ic_simd_block,
            conv.oc_simd_block);

    bool is_access_aligned
            = IS_ALIGNED(reinterpret_cast<ptrdiff_t>(wp), _64byte_align)
            // check if the inner-most dimension size matches the alignment
            // stride.
            && IS_ALIGNED(conv.oc_simd_block * sizeof(float), _64byte_align);

    for (int j = 0; j < alpha; j++) {
        for (int i = 0; i < alpha; i++) {
            for (int v = 0; v < conv.ic_simd_block; v++) {
                PRAGMA_OMP_SIMD()
                for (int k = 0; k < conv.oc_simd_block; k++) {
                    Fw[j][i][v][k] = input(0, 0, j, i, 0, 0, v, k);
                }
            }
        }
    }

    trans_O_3x3_4x4_wu(Fw, F);

    for (int j = 0; j < kh; j++) {
        for (int i = 0; i < kw; i++) {
            for (int v = 0; v < conv.ic_simd_block; v++) {
                store_output(&(output(0, 0, j, i, v, 0)), F[j][i][v],
                        is_access_aligned);
            }
        }
    }
}

template <bool is_fwd>
void _jit_avx512_common_convolution_winograd_t<is_fwd>::_execute_data_W_S_G_D(
        float *inp_ptr, float *out_ptr, float *wei_ptr, float *bias_ptr,
        const memory_tracking::grantor_t &scratchpad) const {
    const auto &jcp = kernel_->jcp;

    const int inph = is_fwd ? jcp.ih : jcp.oh;
    const int inpw = is_fwd ? jcp.iw : jcp.ow;
    const int outh = is_fwd ? jcp.oh : jcp.ih;
    const int outw = is_fwd ? jcp.ow : jcp.iw;

    /* Note that jcp.with_eltwise is true for both fused conv+relu primitive
     * and conv primitive with PostOps with relu before sum
     * (PostOps relu after sum is handled later) */
    auto output_transform = jcp.with_bias
            ? (jcp.with_eltwise ? (jcp.with_sum
                               ? output_transform_data<is_fwd, true, true, true>
                               : output_transform_data<is_fwd, true, true,
                                       false>)
                                : (jcp.with_sum ? output_transform_data<is_fwd,
                                                true, false, true>
                                                : output_transform_data<is_fwd,
                                                        true, false, false>))
            : (jcp.with_eltwise ? (jcp.with_sum ? output_transform_data<is_fwd,
                                           false, true, true>
                                                : output_transform_data<is_fwd,
                                                        false, true, false>)
                                : (jcp.with_sum ? output_transform_data<is_fwd,
                                                false, false, true>
                                                : output_transform_data<is_fwd,
                                                        false, false, false>));

    /* Notation:
       FWD: dimM:oc, dimN:ntiles, dimK:ic,
       BWD: dimM:ic, dimN:ntiles, dimK:oc,
       FWD/BWD: V: src/diff_dst transform, U:weight transform,
                M:dst/diff_src transform  */
    array_offset_calculator<float, 5> input(inp_ptr, jcp.mb,
            jcp.dimK / jcp.dimK_reg_block, inph, inpw, jcp.dimK_reg_block);
    array_offset_calculator<float, 5> output(out_ptr, jcp.mb,
            jcp.dimM / jcp.dimM_simd_block, outh, outw, jcp.dimM_simd_block);
    array_offset_calculator<float, 6> weights(wei_ptr,
            jcp.oc / jcp.oc_simd_block, jcp.ic / jcp.ic_simd_block, jcp.kh,
            jcp.kw, jcp.ic_simd_block, jcp.oc_simd_block);
    array_offset_calculator<float, 2> bias(
            bias_ptr, jcp.dimM / jcp.dimM_simd_block, jcp.dimM_simd_block);

    array_offset_calculator<float, 8> M(is_fwd
                    ? scratchpad.template get<float>(key_wino_M)
                    : scratchpad.template get<float>(key_wino_V),
            jcp.dimN_nb_block, jcp.dimM_nb_block, alpha, alpha, jcp.dimN_block,
            jcp.dimM_block, jcp.dimN_reg_block, jcp.dimM_simd_block);
    array_offset_calculator<float, 8> U(
            scratchpad.template get<float>(key_wino_U), jcp.dimM_nb_block,
            alpha, alpha, jcp.dimK_nb_block, jcp.dimM_block, jcp.dimK_block,
            jcp.dimK_reg_block, jcp.dimM_simd_block);
    array_offset_calculator<float, 8> V(is_fwd
                    ? scratchpad.template get<float>(key_wino_V)
                    : scratchpad.template get<float>(key_wino_M),
            jcp.dimN_nb_block, alpha, alpha, jcp.dimN_block, jcp.dimK_nb_block,
            jcp.dimK_block, jcp.dimN_reg_block, jcp.dimK_reg_block);

    bool V_streamout = jcp.dimN * jcp.dimK * alpha * alpha * sizeof(float)
            > 2 * platform::get_per_core_cache_size(3) * jcp.nthr;

    const bool output_is_aligned
            = IS_ALIGNED(reinterpret_cast<ptrdiff_t>(out_ptr), _64byte_align);

    const bool wants_padded_bias
            = jcp.with_bias && jcp.oc_without_padding != jcp.oc;
    float last_slice_bias[simd_w] = {0};
    if (wants_padded_bias) {
        for (int oc = 0; oc < jcp.oc_without_padding % jcp.oc_simd_block; ++oc)
            last_slice_bias[oc] = bias(jcp.dimM / jcp.dimM_simd_block - 1, oc);
    }

    parallel_nd(jcp.mb, jcp.dimK_nb_block, jcp.dimK_block,
            [&](dim_t img, dim_t K_blk1, dim_t K_blk2) {
                input_transform_data<is_fwd>(img, jcp,
                        &(input(img, K_blk1 * jcp.dimK_block + K_blk2, 0, 0,
                                0)),
                        &(V(0, 0, 0, 0, K_blk1, K_blk2, 0, 0)), V_streamout);
            });

    parallel_nd(jcp.nb_oc, jcp.nb_ic, jcp.oc_block, jcp.ic_block,
            [&](dim_t ofm1, dim_t ifm1, dim_t ofm2, dim_t ifm2) {
                float *U_base_ptr = is_fwd
                        ? &(U(ofm1, 0, 0, ifm1, ofm2, ifm2, 0, 0))
                        : &(U(ifm1, 0, 0, ofm1, ifm2, ofm2, 0, 0));
                weight_transform_data<is_fwd>(jcp,
                        &(weights(ofm1 * jcp.oc_block + ofm2,
                                ifm1 * jcp.ic_block + ifm2, 0, 0, 0, 0)),
                        U_base_ptr);
            });

    parallel_nd(jcp.dimN_nb_block, alpha, alpha, jcp.dimM_nb_block,
            jcp.dimN_block,
            [&](dim_t N_blk1, dim_t oj, dim_t oi, dim_t M_blk1, dim_t N_blk2) {
                kernel_->gemm_loop_ker_first_iter(
                        (float *)&(M(N_blk1, M_blk1, oj, oi, N_blk2, 0, 0, 0)),
                        (const float *)&(U(M_blk1, oj, oi, 0, 0, 0, 0, 0)),
                        (const float *)&(
                                V(N_blk1, oj, oi, N_blk2, 0, 0, 0, 0)));
                for (dim_t K_blk1 = 1; K_blk1 < jcp.dimK_nb_block; K_blk1++) {
                    kernel_->gemm_loop_ker((float *)&(M(N_blk1, M_blk1, oj, oi,
                                                   N_blk2, 0, 0, 0)),
                            (const float *)&(
                                    U(M_blk1, oj, oi, K_blk1, 0, 0, 0, 0)),
                            (const float *)&(V(
                                    N_blk1, oj, oi, N_blk2, K_blk1, 0, 0, 0)));
                }
            });

    parallel_nd(jcp.mb, jcp.dimM_nb_block, jcp.dimM_block,
            [&](dim_t img, dim_t M_blk1, dim_t M_blk2) {
                const dim_t M_blk = M_blk1 * jcp.dimM_block + M_blk2;

                float *bias_ptr = wants_padded_bias
                                && M_blk == jcp.dimM / jcp.dimM_simd_block - 1
                        ? last_slice_bias
                        : (jcp.with_bias ? &bias(M_blk, 0) : nullptr);

                output_transform(img, jcp,
                        &(M(0, M_blk1, 0, 0, 0, M_blk2, 0, 0)),
                        &(output(img, M_blk, 0, 0, 0)), bias_ptr,
                        output_is_aligned);
            });
}

template struct _jit_avx512_common_convolution_winograd_t<true>;
template struct _jit_avx512_common_convolution_winograd_t<false>;

void jit_avx512_common_convolution_winograd_bwd_weights_t::
        _maybe_execute_diff_bias_copy(float *diff_bias,
                const memory_tracking::grantor_t &scratchpad) const {
    if (pd()->wants_padded_bias()) {
        auto padded_bias = scratchpad.get<float>(key_conv_padded_bias);
        for (int oc = 0; oc < pd()->jcp_.oc_without_padding; ++oc)
            diff_bias[oc] = padded_bias[oc];
    }
}

void jit_avx512_common_convolution_winograd_bwd_weights_t::
        _execute_backward_weights_S_D_G_W(const exec_ctx_t &ctx,
                const memory_tracking::grantor_t &scratchpad) const {
    auto ptr_diff_dst = CTX_IN_MEM(const float *, DNNL_ARG_DIFF_DST);
    auto ptr_src = CTX_IN_MEM(const float *, DNNL_ARG_SRC);
    auto ptr_diff_weights = CTX_OUT_MEM(float *, DNNL_ARG_DIFF_WEIGHTS);
    auto ptr_diff_bias = CTX_OUT_MEM(float *, DNNL_ARG_DIFF_BIAS);

    const auto &jcp = kernel_->jcp;
    const int nthreads = jcp.nthr;

    auto diff_src_transform_bwd_weights_ver = jcp.ver == ver_4fma
            ? diff_src_transform_bwd_weights<true>
            : diff_src_transform_bwd_weights<false>;
    auto diff_dst_transform_bwd_weights_ver = jcp.with_bias
            ? diff_dst_transform_bwd_weights<true>
            : diff_dst_transform_bwd_weights<false>;

    array_offset_calculator<float, 5> src(
            (float *)ptr_src, jcp.mb, jcp.ic / simd_w, jcp.ih, jcp.iw, simd_w);
    array_offset_calculator<float, 5> diff_dst((float *)ptr_diff_dst, jcp.mb,
            jcp.oc / simd_w, jcp.oh, jcp.ow, simd_w);
    array_offset_calculator<float, 6> diff_weights(ptr_diff_weights,
            jcp.oc / simd_w, jcp.ic / simd_w, jcp.kh, jcp.kw, simd_w, simd_w);
    array_offset_calculator<float, 2> diff_bias(pd()->wants_padded_bias()
                    ? scratchpad.get<float>(key_conv_padded_bias)
                    : ptr_diff_bias,
            jcp.oc / simd_w, simd_w);

    array_offset_calculator<float, 8> U(scratchpad.get<float>(key_wino_U),
            jcp.nb_ic, jcp.nb_oc, alpha, alpha, jcp.oc_block, jcp.ic_block,
            jcp.ic_simd_block, jcp.oc_simd_block);

    array_offset_calculator<float, 8> M(scratchpad.get<float>(key_wino_M),
            jcp.nb_oc, alpha, alpha, jcp.tile_block, jcp.oc_block,
            jcp.nb_tile_block_ur, jcp.tile_block_ur * jcp.tile_4fma,
            jcp.oc_simd_block);
    array_offset_calculator<float, 8> V(scratchpad.get<float>(key_wino_V),
            jcp.nb_ic, alpha, alpha, jcp.tile_block, jcp.ic_block,
            jcp.nb_tile_block_ur, jcp.tile_block_ur,
            jcp.ic_simd_block * jcp.tile_4fma);

    const int trans_buffer_size
            = alpha * alpha * jcp.tile_4fma * jcp.ic_simd_block;
    array_offset_calculator<float, 2> trans_buffer(
            scratchpad.get<float>(key_conv_tr_src), nthreads,
            trans_buffer_size);

    array_offset_calculator<float, 2> diff_bias_prv(
            scratchpad.get<float>(key_conv_bia_reduction), nthreads, jcp.oc);

    PRAGMA_OMP(parallel num_threads(nthreads))
    {
        if (jcp.with_bias) {
            parallel_nd_in_omp(nthreads, jcp.oc, [&](dim_t ithr, dim_t ofm) {
                diff_bias_prv(ithr, ofm) = 0.0f;
            });

            PRAGMA_OMP(for nowait)
            for (int bofm = 0; bofm < jcp.oc / simd_w; bofm++) {
                PRAGMA_OMP_SIMD()
                for (int v = 0; v < simd_w; v++)
                    diff_bias(bofm, v) = 0.0f;
            }
        }

        const int ithr = OMP_GET_THREAD_NUM();

        parallel_nd_in_omp(jcp.mb, jcp.nb_ic, jcp.ic_block,
                [&](dim_t img, dim_t ifm1, dim_t ifm2) {
                    float *transb = jcp.ver == ver_4fma
                            ? &(trans_buffer(ithr, 0))
                            : nullptr;
                    diff_src_transform_bwd_weights_ver(img, jcp,
                            &(src(img, ifm1 * jcp.ic_block + ifm2, 0, 0, 0)),
                            &(V(ifm1, 0, 0, 0, ifm2, 0, 0, 0)), transb,
                            kernel_->transpose_4fma_ker);
                });

        parallel_nd_in_omp(jcp.mb, jcp.nb_oc, jcp.oc_block,
                [&](dim_t img, dim_t ofm1, dim_t ofm2) {
                    float *dbias = jcp.with_bias
                            ? &(diff_bias_prv(ithr,
                                    simd_w * (ofm1 * jcp.oc_block + ofm2)))
                            : nullptr;
                    diff_dst_transform_bwd_weights_ver(img, jcp,
                            &(diff_dst(
                                    img, ofm1 * jcp.oc_block + ofm2, 0, 0, 0)),
                            &(M(ofm1, 0, 0, 0, ofm2, 0, 0, 0)), dbias);
                });

        PRAGMA_OMP(barrier)

        for (int ifm1 = 0; ifm1 < jcp.nb_ic; ifm1++) {
            parallel_nd_in_omp(alpha, alpha, jcp.nb_oc,
                    [&](dim_t oj, dim_t oi, dim_t ofm1) {
                        kernel_->gemm_loop_ker_first_iter(
                                (float *)&(U(ifm1, ofm1, oj, oi, 0, 0, 0, 0)),
                                (const float *)&(
                                        M(ofm1, oj, oi, 0, 0, 0, 0, 0)),
                                (const float *)&(
                                        V(ifm1, oj, oi, 0, 0, 0, 0, 0)));
                        for (int tile_block = 1; tile_block < jcp.tile_block;
                                tile_block++) {
                            kernel_->gemm_loop_ker((float *)&(U(ifm1, ofm1, oj,
                                                           oi, 0, 0, 0, 0)),
                                    (const float *)&(M(ofm1, oj, oi, tile_block,
                                            0, 0, 0, 0)),
                                    (const float *)&(V(ifm1, oj, oi, tile_block,
                                            0, 0, 0, 0)));
                        }
                    });
        }

        PRAGMA_OMP(barrier)

        parallel_nd_in_omp(jcp.nb_ic, jcp.nb_oc, jcp.oc_block, jcp.ic_block,
                [&](dim_t ifm1, dim_t ofm1, dim_t ofm2, dim_t ifm2) {
                    diff_weights_transform_bwd_weights(jcp,
                            &(diff_weights(ofm1 * jcp.oc_block + ofm2,
                                    ifm1 * jcp.ic_block + ifm2, 0, 0, 0, 0)),
                            &(U(ifm1, ofm1, 0, 0, ofm2, ifm2, 0, 0)));
                });

        if (jcp.with_bias) {
            PRAGMA_OMP(for)
            for (int ofm1 = 0; ofm1 < jcp.oc / simd_w; ofm1++) {
                for (int ithr = 0; ithr < nthreads; ithr++) {
                    float *base_bias_ptr = &(diff_bias(ofm1, 0));
                    float *base_bias_prv_ptr
                            = &(diff_bias_prv(ithr * jcp.oc + ofm1 * simd_w));
                    PRAGMA_OMP_SIMD()
                    for (int ofm2 = 0; ofm2 < simd_w; ofm2++) {
                        base_bias_ptr[ofm2] += base_bias_prv_ptr[ofm2];
                    }
                }
            }
        }
    }

    _maybe_execute_diff_bias_copy(ptr_diff_bias, scratchpad);
}

} // namespace x64
} // namespace cpu
} // namespace impl
} // namespace dnnl
// vim: et ts=4 sw=4 cindent cino+=l0,\:4,N-s
