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|
/*
* Copyright (c) 2016, 2017 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include <arm_neon.h>
#include <cstddef>
#include <cstdint>
#include <tuple>
using namespace arm_compute;
namespace arm_compute
{
class Coordinates;
} // namespace arm_compute
NEGEMMLowpMatrixMultiplyKernel::NEGEMMLowpMatrixMultiplyKernel()
: _input0(nullptr), _input1(nullptr), _output(nullptr), _a_offset(0), _b_offset(0), _output_offset(0), _output_mult_int(0), _shift(0)
{
}
void NEGEMMLowpMatrixMultiplyKernel::configure(const ITensor *input0, const ITensor *input1, ITensor *output,
int32_t a_offset, int32_t b_offset, int32_t output_offset, int32_t output_mult_int, int32_t shift)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::U8);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
_input0 = input0;
_input1 = input1;
_output = output;
_a_offset = a_offset;
_b_offset = b_offset;
_output_offset = output_offset;
_output_mult_int = output_mult_int;
_shift = shift;
constexpr unsigned int num_elems_processed_per_iteration_x = 16;
constexpr unsigned int num_elems_processed_per_iteration_y = 4;
Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
AccessWindowHorizontal in0_access(input0->info(), 0, num_elems_processed_per_iteration_x);
AccessWindowHorizontal in1_access(input1->info(), 0, num_elems_processed_per_iteration_x);
update_window_and_padding(win, in0_access, in1_access, output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->info()->tensor_shape()));
INEKernel::configure(win);
}
void NEGEMMLowpMatrixMultiplyKernel::run(const Window &window)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
const size_t in_b_stride = _input1->info()->strides_in_bytes()[1];
const size_t out_stride = _output->info()->strides_in_bytes()[1];
/* Set step_x and step_y for matrix A. Scale by a factor of 4 the Y range as the input interleaved matrix A has 4 times less the rows of the output matrix */
Window win_a(window);
win_a.set(Window::DimX, Window::Dimension(0, 0, 0));
win_a.set(Window::DimY, Window::Dimension(window.y().start() >> 2, window.y().end() >> 2, 1));
/* Set step_x and step_y for matrix B. Scale by a factor of 16 the X range as the input transposed matrix A has 16 times less the cols of the output matrix */
Window win_b(window);
win_b.set(Window::DimX, Window::Dimension(window.x().start() >> 4, window.x().end() >> 4, in_b_stride));
win_b.set(Window::DimY, Window::Dimension(0, 0, 0));
/* The step x and step y for the output matrix has been already set using in configure() */
Iterator ina(_input0, win_a);
Iterator inb(_input1, win_b);
Iterator out(_output, window);
const int32x4_t voffset_a = vdupq_n_s32(_a_offset);
const int32x4_t voffset_b = vdupq_n_s32(_b_offset);
const int32x4_t vshiftr = vdupq_n_s32(-_shift);
const int width_b = _input1->info()->dimension(0);
// The implementation assumes that the matrix A and Matrix B have been reshaped respectively with NEGEMMInterleave4x4 and NEGEMMTranspose1xW
// The reshaping of the matrices helps to have a cache friendly implementation and helps to avoid the data re-arrangements needed for computing 16x4 elements per iteration
// All the values needed for computing a single 4x4 block will be read from consecutive memory positions
execute_window_loop(window, [&](const Coordinates &)
{
const uint8_t *mtx_a0 = ina.ptr();
const uint8_t *mtx_b0 = inb.ptr();
// Accumulators for the block 0
int32x4x4_t c0 =
{
{
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset)
}
};
// Accumulators for the block 1
int32x4x4_t c1 =
{
{
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset)
}
};
// Accumulators for the block 2
int32x4x4_t c2 =
{
{
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset)
}
};
// Accumulators for the block 3
int32x4x4_t c3 =
{
{
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset),
vdupq_n_s32(_output_offset)
}
};
int k = 0;
// This for loop performs 4 accumulations per iteration
for(; k <= (width_b - 64); k += 64, mtx_a0 += 16, mtx_b0 += 64)
{
const uint8x8_t p00 = vld1_u8(mtx_a0 + 0);
const uint8x8_t p01 = vld1_u8(mtx_a0 + 8);
const uint8x8_t q00l = vld1_u8(mtx_b0 + 0);
const uint8x8_t q00h = vld1_u8(mtx_b0 + 8);
const uint8x8_t q01l = vld1_u8(mtx_b0 + 16);
const uint8x8_t q01h = vld1_u8(mtx_b0 + 24);
const uint8x8_t q02l = vld1_u8(mtx_b0 + 32);
const uint8x8_t q02h = vld1_u8(mtx_b0 + 40);
const uint8x8_t q03l = vld1_u8(mtx_b0 + 48);
const uint8x8_t q03h = vld1_u8(mtx_b0 + 56);
const int32x4_t ia0l = vaddw_s16(voffset_a, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(p00))));
const int32x4_t ia0h = vaddw_s16(voffset_a, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(p00))));
const int32x4_t ia1l = vaddw_s16(voffset_a, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(p01))));
const int32x4_t ia1h = vaddw_s16(voffset_a, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(p01))));
const int32x2x4_t ia0 =
{
{
vget_low_s32(ia0l),
vget_high_s32(ia0l),
vget_low_s32(ia0h),
vget_high_s32(ia0h)
}
};
const int32x2x4_t ia1 =
{
{
vget_low_s32(ia1l),
vget_high_s32(ia1l),
vget_low_s32(ia1h),
vget_high_s32(ia1h)
}
};
const int32x4x4_t ib0 =
{
{
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q00l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q00l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q00h)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q00h))))
}
};
const int32x4x4_t ib1 =
{
{
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q01l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q01l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q01h)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q01h))))
}
};
const int32x4x4_t ib2 =
{
{
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q02l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q02l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q02h)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q02h))))
}
};
const int32x4x4_t ib3 =
{
{
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q03l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q03l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q03h)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q03h))))
}
};
// 4x4 block 0 - Accumulation 0
c0.val[0] = vmlaq_lane_s32(c0.val[0], ib0.val[0], ia0.val[0], 0);
c0.val[1] = vmlaq_lane_s32(c0.val[1], ib0.val[0], ia0.val[0], 1);
c0.val[2] = vmlaq_lane_s32(c0.val[2], ib0.val[0], ia0.val[1], 0);
c0.val[3] = vmlaq_lane_s32(c0.val[3], ib0.val[0], ia0.val[1], 1);
// 4x4 block 0 - Accumulation 1
c0.val[0] = vmlaq_lane_s32(c0.val[0], ib1.val[0], ia0.val[2], 0);
c0.val[1] = vmlaq_lane_s32(c0.val[1], ib1.val[0], ia0.val[2], 1);
c0.val[2] = vmlaq_lane_s32(c0.val[2], ib1.val[0], ia0.val[3], 0);
c0.val[3] = vmlaq_lane_s32(c0.val[3], ib1.val[0], ia0.val[3], 1);
// 4x4 block 0 - Accumulation 2
c0.val[0] = vmlaq_lane_s32(c0.val[0], ib2.val[0], ia1.val[0], 0);
c0.val[1] = vmlaq_lane_s32(c0.val[1], ib2.val[0], ia1.val[0], 1);
c0.val[2] = vmlaq_lane_s32(c0.val[2], ib2.val[0], ia1.val[1], 0);
c0.val[3] = vmlaq_lane_s32(c0.val[3], ib2.val[0], ia1.val[1], 1);
// 4x4 block 0 - Accumulation 3
c0.val[0] = vmlaq_lane_s32(c0.val[0], ib3.val[0], ia1.val[2], 0);
c0.val[1] = vmlaq_lane_s32(c0.val[1], ib3.val[0], ia1.val[2], 1);
c0.val[2] = vmlaq_lane_s32(c0.val[2], ib3.val[0], ia1.val[3], 0);
c0.val[3] = vmlaq_lane_s32(c0.val[3], ib3.val[0], ia1.val[3], 1);
// 4x4 block 1 - Accumulation 0
c1.val[0] = vmlaq_lane_s32(c1.val[0], ib0.val[1], ia0.val[0], 0);
c1.val[1] = vmlaq_lane_s32(c1.val[1], ib0.val[1], ia0.val[0], 1);
c1.val[2] = vmlaq_lane_s32(c1.val[2], ib0.val[1], ia0.val[1], 0);
c1.val[3] = vmlaq_lane_s32(c1.val[3], ib0.val[1], ia0.val[1], 1);
// 4x4 block 1 - Accumulation 1
c1.val[0] = vmlaq_lane_s32(c1.val[0], ib1.val[1], ia0.val[2], 0);
c1.val[1] = vmlaq_lane_s32(c1.val[1], ib1.val[1], ia0.val[2], 1);
c1.val[2] = vmlaq_lane_s32(c1.val[2], ib1.val[1], ia0.val[3], 0);
c1.val[3] = vmlaq_lane_s32(c1.val[3], ib1.val[1], ia0.val[3], 1);
// 4x4 block 1 - Accumulation 2
c1.val[0] = vmlaq_lane_s32(c1.val[0], ib2.val[1], ia1.val[0], 0);
c1.val[1] = vmlaq_lane_s32(c1.val[1], ib2.val[1], ia1.val[0], 1);
c1.val[2] = vmlaq_lane_s32(c1.val[2], ib2.val[1], ia1.val[1], 0);
c1.val[3] = vmlaq_lane_s32(c1.val[3], ib2.val[1], ia1.val[1], 1);
// 4x4 block 1 - Accumulation 3
c1.val[0] = vmlaq_lane_s32(c1.val[0], ib3.val[1], ia1.val[2], 0);
c1.val[1] = vmlaq_lane_s32(c1.val[1], ib3.val[1], ia1.val[2], 1);
c1.val[2] = vmlaq_lane_s32(c1.val[2], ib3.val[1], ia1.val[3], 0);
c1.val[3] = vmlaq_lane_s32(c1.val[3], ib3.val[1], ia1.val[3], 1);
// 4x4 block 2 - Accumulation 0
c2.val[0] = vmlaq_lane_s32(c2.val[0], ib0.val[2], ia0.val[0], 0);
c2.val[1] = vmlaq_lane_s32(c2.val[1], ib0.val[2], ia0.val[0], 1);
c2.val[2] = vmlaq_lane_s32(c2.val[2], ib0.val[2], ia0.val[1], 0);
c2.val[3] = vmlaq_lane_s32(c2.val[3], ib0.val[2], ia0.val[1], 1);
// 4x4 block 2 - Accumulation 1
c2.val[0] = vmlaq_lane_s32(c2.val[0], ib1.val[2], ia0.val[2], 0);
c2.val[1] = vmlaq_lane_s32(c2.val[1], ib1.val[2], ia0.val[2], 1);
c2.val[2] = vmlaq_lane_s32(c2.val[2], ib1.val[2], ia0.val[3], 0);
c2.val[3] = vmlaq_lane_s32(c2.val[3], ib1.val[2], ia0.val[3], 1);
// 4x4 block 2 - Accumulation 2
c2.val[0] = vmlaq_lane_s32(c2.val[0], ib2.val[2], ia1.val[0], 0);
c2.val[1] = vmlaq_lane_s32(c2.val[1], ib2.val[2], ia1.val[0], 1);
c2.val[2] = vmlaq_lane_s32(c2.val[2], ib2.val[2], ia1.val[1], 0);
c2.val[3] = vmlaq_lane_s32(c2.val[3], ib2.val[2], ia1.val[1], 1);
// 4x4 block 2 - Accumulation 3
c2.val[0] = vmlaq_lane_s32(c2.val[0], ib3.val[2], ia1.val[2], 0);
c2.val[1] = vmlaq_lane_s32(c2.val[1], ib3.val[2], ia1.val[2], 1);
c2.val[2] = vmlaq_lane_s32(c2.val[2], ib3.val[2], ia1.val[3], 0);
c2.val[3] = vmlaq_lane_s32(c2.val[3], ib3.val[2], ia1.val[3], 1);
// 4x4 block 3 - Accumulation 0
c3.val[0] = vmlaq_lane_s32(c3.val[0], ib0.val[3], ia0.val[0], 0);
c3.val[1] = vmlaq_lane_s32(c3.val[1], ib0.val[3], ia0.val[0], 1);
c3.val[2] = vmlaq_lane_s32(c3.val[2], ib0.val[3], ia0.val[1], 0);
c3.val[3] = vmlaq_lane_s32(c3.val[3], ib0.val[3], ia0.val[1], 1);
// 4x4 block 3 - Accumulation 1
c3.val[0] = vmlaq_lane_s32(c3.val[0], ib1.val[3], ia0.val[2], 0);
c3.val[1] = vmlaq_lane_s32(c3.val[1], ib1.val[3], ia0.val[2], 1);
c3.val[2] = vmlaq_lane_s32(c3.val[2], ib1.val[3], ia0.val[3], 0);
c3.val[3] = vmlaq_lane_s32(c3.val[3], ib1.val[3], ia0.val[3], 1);
// 4x4 block 3 - Accumulation 2
c3.val[0] = vmlaq_lane_s32(c3.val[0], ib2.val[3], ia1.val[0], 0);
c3.val[1] = vmlaq_lane_s32(c3.val[1], ib2.val[3], ia1.val[0], 1);
c3.val[2] = vmlaq_lane_s32(c3.val[2], ib2.val[3], ia1.val[1], 0);
c3.val[3] = vmlaq_lane_s32(c3.val[3], ib2.val[3], ia1.val[1], 1);
// 4x4 block 3 - Accumulation 3
c3.val[0] = vmlaq_lane_s32(c3.val[0], ib3.val[3], ia1.val[2], 0);
c3.val[1] = vmlaq_lane_s32(c3.val[1], ib3.val[3], ia1.val[2], 1);
c3.val[2] = vmlaq_lane_s32(c3.val[2], ib3.val[3], ia1.val[3], 0);
c3.val[3] = vmlaq_lane_s32(c3.val[3], ib3.val[3], ia1.val[3], 1);
}
// This for loop handles the left-over accumulations
for(; k < width_b; k += 16, mtx_a0 += 4, mtx_b0 += 16)
{
const uint8x8_t p00 = vld1_u8(mtx_a0);
const uint8x8_t q00l = vld1_u8(mtx_b0);
const uint8x8_t q00h = vld1_u8(mtx_b0 + 8);
const int32x4_t ia0 = vaddw_s16(voffset_a, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(p00))));
const int32x2x2_t ia =
{
{
vget_low_s32(ia0),
vget_high_s32(ia0)
}
};
const int32x4x4_t ib0 =
{
{
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q00l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q00l)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_low_u16(vmovl_u8(q00h)))),
vaddw_s16(voffset_b, vreinterpret_s16_u16(vget_high_u16(vmovl_u8(q00h))))
}
};
// 4x4 block 0
c0.val[0] = vmlaq_lane_s32(c0.val[0], ib0.val[0], ia.val[0], 0);
c0.val[1] = vmlaq_lane_s32(c0.val[1], ib0.val[0], ia.val[0], 1);
c0.val[2] = vmlaq_lane_s32(c0.val[2], ib0.val[0], ia.val[1], 0);
c0.val[3] = vmlaq_lane_s32(c0.val[3], ib0.val[0], ia.val[1], 1);
// 4x4 block 1
c1.val[0] = vmlaq_lane_s32(c1.val[0], ib0.val[1], ia.val[0], 0);
c1.val[1] = vmlaq_lane_s32(c1.val[1], ib0.val[1], ia.val[0], 1);
c1.val[2] = vmlaq_lane_s32(c1.val[2], ib0.val[1], ia.val[1], 0);
c1.val[3] = vmlaq_lane_s32(c1.val[3], ib0.val[1], ia.val[1], 1);
// 4x4 block 2
c2.val[0] = vmlaq_lane_s32(c2.val[0], ib0.val[2], ia.val[0], 0);
c2.val[1] = vmlaq_lane_s32(c2.val[1], ib0.val[2], ia.val[0], 1);
c2.val[2] = vmlaq_lane_s32(c2.val[2], ib0.val[2], ia.val[1], 0);
c2.val[3] = vmlaq_lane_s32(c2.val[3], ib0.val[2], ia.val[1], 1);
// 4x4 block 3
c3.val[0] = vmlaq_lane_s32(c3.val[0], ib0.val[3], ia.val[0], 0);
c3.val[1] = vmlaq_lane_s32(c3.val[1], ib0.val[3], ia.val[0], 1);
c3.val[2] = vmlaq_lane_s32(c3.val[2], ib0.val[3], ia.val[1], 0);
c3.val[3] = vmlaq_lane_s32(c3.val[3], ib0.val[3], ia.val[1], 1);
}
c0.val[0] = vshlq_s32(vmulq_n_s32(c0.val[0], _output_mult_int), vshiftr);
c0.val[1] = vshlq_s32(vmulq_n_s32(c0.val[1], _output_mult_int), vshiftr);
c0.val[2] = vshlq_s32(vmulq_n_s32(c0.val[2], _output_mult_int), vshiftr);
c0.val[3] = vshlq_s32(vmulq_n_s32(c0.val[3], _output_mult_int), vshiftr);
c1.val[0] = vshlq_s32(vmulq_n_s32(c1.val[0], _output_mult_int), vshiftr);
c1.val[1] = vshlq_s32(vmulq_n_s32(c1.val[1], _output_mult_int), vshiftr);
c1.val[2] = vshlq_s32(vmulq_n_s32(c1.val[2], _output_mult_int), vshiftr);
c1.val[3] = vshlq_s32(vmulq_n_s32(c1.val[3], _output_mult_int), vshiftr);
c2.val[0] = vshlq_s32(vmulq_n_s32(c2.val[0], _output_mult_int), vshiftr);
c2.val[1] = vshlq_s32(vmulq_n_s32(c2.val[1], _output_mult_int), vshiftr);
c2.val[2] = vshlq_s32(vmulq_n_s32(c2.val[2], _output_mult_int), vshiftr);
c2.val[3] = vshlq_s32(vmulq_n_s32(c2.val[3], _output_mult_int), vshiftr);
c3.val[0] = vshlq_s32(vmulq_n_s32(c3.val[0], _output_mult_int), vshiftr);
c3.val[1] = vshlq_s32(vmulq_n_s32(c3.val[1], _output_mult_int), vshiftr);
c3.val[2] = vshlq_s32(vmulq_n_s32(c3.val[2], _output_mult_int), vshiftr);
c3.val[3] = vshlq_s32(vmulq_n_s32(c3.val[3], _output_mult_int), vshiftr);
const uint8x16x4_t r =
{
{
vcombine_u8(vqmovun_s16(vcombine_s16(vqmovn_s32(c0.val[0]), vqmovn_s32(c1.val[0]))),
vqmovun_s16(vcombine_s16(vqmovn_s32(c2.val[0]), vqmovn_s32(c3.val[0])))),
vcombine_u8(vqmovun_s16(vcombine_s16(vqmovn_s32(c0.val[1]), vqmovn_s32(c1.val[1]))),
vqmovun_s16(vcombine_s16(vqmovn_s32(c2.val[1]), vqmovn_s32(c3.val[1])))),
vcombine_u8(vqmovun_s16(vcombine_s16(vqmovn_s32(c0.val[2]), vqmovn_s32(c1.val[2]))),
vqmovun_s16(vcombine_s16(vqmovn_s32(c2.val[2]), vqmovn_s32(c3.val[2])))),
vcombine_u8(vqmovun_s16(vcombine_s16(vqmovn_s32(c0.val[3]), vqmovn_s32(c1.val[3]))),
vqmovun_s16(vcombine_s16(vqmovn_s32(c2.val[3]), vqmovn_s32(c3.val[3]))))
}
};
uint8_t *const mtx_out = out.ptr();
vst1q_u8(mtx_out + 0 * out_stride, r.val[0]);
vst1q_u8(mtx_out + 1 * out_stride, r.val[1]);
vst1q_u8(mtx_out + 2 * out_stride, r.val[2]);
vst1q_u8(mtx_out + 3 * out_stride, r.val[3]);
},
ina, inb, out);
}
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