src/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.cpp - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 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/NEGEMMLowpOffsetContributionKernel.h"

 #include "arm_compute/core/AccessWindowStatic.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>

 using namespace arm_compute;

 namespace arm_compute
 {
 class Coordinates;
 } // namespace arm_compute

 NEGEMMLowpOffsetContributionKernel::NEGEMMLowpOffsetContributionKernel()
     : _vector_sum_col(nullptr), _vector_sum_row(nullptr), _mm_result(nullptr), _a_offset(0), _b_offset(0), _k_offset(0), _slide_vector_sum_col(true)
 {
 }

 void NEGEMMLowpOffsetContributionKernel::configure(ITensor *mm_result, const ITensor *vector_sum_col, const ITensor *vector_sum_row, int32_t k, int32_t a_offset, int32_t b_offset)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32);

     // If a_offset == 0, vector_sum_col can be a nullptr
     if(a_offset != 0)
     {
         ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
         ARM_COMPUTE_ERROR_ON(vector_sum_col->info()->dimension(0) != mm_result->info()->dimension(0));

         TensorShape vector_sum_col_shape = vector_sum_col->info()->tensor_shape();
         vector_sum_col_shape.collapse(1);

         // Check if vector_sum_col_shape should be slidden or not
         // Don't slide vector_sum_col_shape along the y dimension if vector_sum_col_shape has just 1 dimension and vector_sum_row_shape more than 1
         // This scenario can happen when the the matrix multiplication is used to perform a convolution operation
         _slide_vector_sum_col = vector_sum_col_shape[1] != 1;
     }

     // If b_offset == 0, vector_sum_row can be a nullptr
     if(b_offset != 0)
     {
         ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
         ARM_COMPUTE_ERROR_ON(vector_sum_row->info()->dimension(0) != mm_result->info()->dimension(1));

         TensorShape output_shape         = mm_result->info()->tensor_shape();
         TensorShape vector_sum_row_shape = vector_sum_row->info()->tensor_shape();
         vector_sum_row_shape.collapse(1);
         output_shape.collapse(2);

         ARM_COMPUTE_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[2], "mm_result tensor must have the same number of batches of output tensor");

         if(a_offset != 0)
         {
             TensorShape vector_sum_col_shape = vector_sum_col->info()->tensor_shape();
             vector_sum_col_shape.collapse(1);

             ARM_COMPUTE_ERROR_ON_MSG(vector_sum_col_shape[1] != 1
                                      && vector_sum_col_shape[1] != vector_sum_row_shape[1],
                                      "vector_sum_col tensor must have the same number of batches of vector_sum_row_shape or the number of batches must be set to 1");
         }
     }

     _vector_sum_col = vector_sum_col;
     _vector_sum_row = vector_sum_row;
     _mm_result      = mm_result;
     _a_offset       = a_offset;
     _b_offset       = b_offset;
     _k_offset       = a_offset * b_offset * k;

     constexpr unsigned int num_elems_processed_per_iteration = 16;

     // Configure kernel window
     Window win = calculate_max_window(*mm_result->info(), Steps(num_elems_processed_per_iteration));

     AccessWindowHorizontal mm_result_access(mm_result->info(), 0, num_elems_processed_per_iteration);

     // Accordingly with a_offset and b_offset, we can have 4 cases:
     // a_offset != 0 && b_offset != 0
     // a_offset  = 0 && b_offset != 0
     // a_offset != 0 && b_offset  = 0
     // a_offset  = 0 && b_offset  = 0
     if(a_offset != 0 && b_offset != 0)
     {
         AccessWindowStatic     vector_sum_row_access(vector_sum_row->info(), 0, 0, vector_sum_row->info()->dimension(0), 0);
         AccessWindowHorizontal vector_sum_col_access(vector_sum_col->info(), 0, num_elems_processed_per_iteration);

         update_window_and_padding(win,
                                   vector_sum_col_access,
                                   vector_sum_row_access,
                                   mm_result_access);
     }
     else if(a_offset == 0 && b_offset != 0)
     {
         AccessWindowStatic vector_sum_row_access(vector_sum_row->info(), 0, 0, vector_sum_row->info()->dimension(0), 0);

         update_window_and_padding(win,
                                   vector_sum_row_access,
                                   mm_result_access);
     }
     else if(a_offset != 0 && b_offset == 0)
     {
         AccessWindowHorizontal vector_sum_col_access(vector_sum_col->info(), 0, num_elems_processed_per_iteration);

         update_window_and_padding(win,
                                   vector_sum_col_access,
                                   mm_result_access);
     }
     else
     {
         update_window_and_padding(win,
                                   mm_result_access);
     }

     INEKernel::configure(win);
 }

 void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadInfo &info)
 {
     ARM_COMPUTE_UNUSED(info);
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

     Window collapsed_window = window.collapse_if_possible(IKernel::window(), Window::DimZ);

     if(_a_offset != 0 && _b_offset != 0) // true, true
     {
         // Set window for vector_sum_col
         Window win_vector_sum_col(collapsed_window);
         win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0));
         if(!_slide_vector_sum_col)
         {
             win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
         }

         // Set window for vector_sum_row
         Window win_vector_sum_row(collapsed_window);
         win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0));
         win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0));

         Iterator vector_sum_col(_vector_sum_col, win_vector_sum_col);
         Iterator vector_sum_row(_vector_sum_row, win_vector_sum_row);
         Iterator mm_result(_mm_result, window);

         execute_window_loop(window, [&](const Coordinates & id)
         {
             // Compute the leftover term due to a_offset.
             int32x4x4_t a_offset_term_s32 =
             {
                 {
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 0),
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 4),
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 8),
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 12)
                 }
             };

             a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], _a_offset);
             a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], _a_offset);
             a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], _a_offset);
             a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], _a_offset);

             // Compute the leftover term due to b_offset.
             int32x4_t b_offset_term_s32 = vld1q_dup_s32(reinterpret_cast<const int32_t *>(vector_sum_row.ptr()) + id.y());
             b_offset_term_s32           = vmulq_n_s32(b_offset_term_s32, _b_offset);

             // Add a_offset_term_s32 and b_offset_term_s32
             int32x4x4_t offset_term_s32 =
             {
                 {
                     vdupq_n_s32(_k_offset),
                     vdupq_n_s32(_k_offset),
                     vdupq_n_s32(_k_offset),
                     vdupq_n_s32(_k_offset)
                 }
             };

             offset_term_s32.val[0] = vaddq_s32(offset_term_s32.val[0], vaddq_s32(a_offset_term_s32.val[0], b_offset_term_s32));
             offset_term_s32.val[1] = vaddq_s32(offset_term_s32.val[1], vaddq_s32(a_offset_term_s32.val[1], b_offset_term_s32));
             offset_term_s32.val[2] = vaddq_s32(offset_term_s32.val[2], vaddq_s32(a_offset_term_s32.val[2], b_offset_term_s32));
             offset_term_s32.val[3] = vaddq_s32(offset_term_s32.val[3], vaddq_s32(a_offset_term_s32.val[3], b_offset_term_s32));

             int32x4x4_t in_s32 =
             {
                 {
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12)
                 }
             };

             // Add the offset terms to GEMM's result
             in_s32.val[0] = vaddq_s32(in_s32.val[0], offset_term_s32.val[0]);
             in_s32.val[1] = vaddq_s32(in_s32.val[1], offset_term_s32.val[1]);
             in_s32.val[2] = vaddq_s32(in_s32.val[2], offset_term_s32.val[2]);
             in_s32.val[3] = vaddq_s32(in_s32.val[3], offset_term_s32.val[3]);

             // Store the result with the offset contribution
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]);
         },
         vector_sum_col, vector_sum_row, mm_result);
     }
     else if((_a_offset == 0) && (_b_offset != 0)) // false, true
     {
         // Set window for vector_sum_row
         Window win_vector_sum_row(collapsed_window);
         win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0));
         win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0));

         Iterator vector_sum_row(_vector_sum_row, win_vector_sum_row);
         Iterator mm_result(_mm_result, window);

         execute_window_loop(window, [&](const Coordinates & id)
         {
             // Compute the leftover term due to b_offset.
             int32x4_t b_offset_term_s32 = vld1q_dup_s32(reinterpret_cast<const int32_t *>(vector_sum_row.ptr()) + id.y());
             b_offset_term_s32           = vmulq_n_s32(b_offset_term_s32, _b_offset);

             int32x4x4_t in_s32 =
             {
                 {
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12)
                 }
             };

             // Add the offset terms to GEMM's result
             in_s32.val[0] = vaddq_s32(in_s32.val[0], b_offset_term_s32);
             in_s32.val[1] = vaddq_s32(in_s32.val[1], b_offset_term_s32);
             in_s32.val[2] = vaddq_s32(in_s32.val[2], b_offset_term_s32);
             in_s32.val[3] = vaddq_s32(in_s32.val[3], b_offset_term_s32);

             // Store the result with the offset contribution
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]);
         },
         vector_sum_row, mm_result);
     }
     else if((_a_offset != 0) && (_b_offset == 0)) // true, false
     {
         // Set window for vector_sum_col
         Window win_vector_sum_col(collapsed_window);
         win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0));
         if(!_slide_vector_sum_col)
         {
             win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
         }

         Iterator vector_sum_col(_vector_sum_col, win_vector_sum_col);
         Iterator mm_result(_mm_result, window);

         execute_window_loop(window, [&](const Coordinates & id)
         {
             // Compute the leftover term due to a_offset.
             int32x4x4_t a_offset_term_s32 =
             {
                 {
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 0),
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 4),
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 8),
                     vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 12)
                 }
             };

             a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], _a_offset);
             a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], _a_offset);
             a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], _a_offset);
             a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], _a_offset);

             int32x4x4_t in_s32 =
             {
                 {
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8),
                     vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12)
                 }
             };

             // Add the offset terms to GEMM's result
             in_s32.val[0] = vaddq_s32(in_s32.val[0], a_offset_term_s32.val[0]);
             in_s32.val[1] = vaddq_s32(in_s32.val[1], a_offset_term_s32.val[1]);
             in_s32.val[2] = vaddq_s32(in_s32.val[2], a_offset_term_s32.val[2]);
             in_s32.val[3] = vaddq_s32(in_s32.val[3], a_offset_term_s32.val[3]);

             // Store the result with the offset contribution
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]);
             vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]);
         },
         vector_sum_col, mm_result);
     }
     else // false, false
     {
         // No offset contribution from matrix A and matrix B
         return;
     }
 }
	/*
	* Copyright (c) 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/NEGEMMLowpOffsetContributionKernel.h"

	#include "arm_compute/core/AccessWindowStatic.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>

	using namespace arm_compute;

	namespace arm_compute
	{
	class Coordinates;
	} // namespace arm_compute

	NEGEMMLowpOffsetContributionKernel::NEGEMMLowpOffsetContributionKernel()
	: _vector_sum_col(nullptr), _vector_sum_row(nullptr), _mm_result(nullptr), _a_offset(0), _b_offset(0), _k_offset(0), _slide_vector_sum_col(true)
	{
	}

	void NEGEMMLowpOffsetContributionKernel::configure(ITensor mm_result, const ITensor vector_sum_col, const ITensor *vector_sum_row, int32_t k, int32_t a_offset, int32_t b_offset)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32);

	// If a_offset == 0, vector_sum_col can be a nullptr
	if(a_offset != 0)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
	ARM_COMPUTE_ERROR_ON(vector_sum_col->info()->dimension(0) != mm_result->info()->dimension(0));

	TensorShape vector_sum_col_shape = vector_sum_col->info()->tensor_shape();
	vector_sum_col_shape.collapse(1);

	// Check if vector_sum_col_shape should be slidden or not
	// Don't slide vector_sum_col_shape along the y dimension if vector_sum_col_shape has just 1 dimension and vector_sum_row_shape more than 1
	// This scenario can happen when the the matrix multiplication is used to perform a convolution operation
	_slide_vector_sum_col = vector_sum_col_shape[1] != 1;
	}

	// If b_offset == 0, vector_sum_row can be a nullptr
	if(b_offset != 0)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
	ARM_COMPUTE_ERROR_ON(vector_sum_row->info()->dimension(0) != mm_result->info()->dimension(1));

	TensorShape output_shape = mm_result->info()->tensor_shape();
	TensorShape vector_sum_row_shape = vector_sum_row->info()->tensor_shape();
	vector_sum_row_shape.collapse(1);
	output_shape.collapse(2);

	ARM_COMPUTE_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[2], "mm_result tensor must have the same number of batches of output tensor");

	if(a_offset != 0)
	{
	TensorShape vector_sum_col_shape = vector_sum_col->info()->tensor_shape();
	vector_sum_col_shape.collapse(1);

	ARM_COMPUTE_ERROR_ON_MSG(vector_sum_col_shape[1] != 1
	&& vector_sum_col_shape[1] != vector_sum_row_shape[1],
	"vector_sum_col tensor must have the same number of batches of vector_sum_row_shape or the number of batches must be set to 1");
	}
	}

	_vector_sum_col = vector_sum_col;
	_vector_sum_row = vector_sum_row;
	_mm_result = mm_result;
	_a_offset = a_offset;
	_b_offset = b_offset;
	_k_offset = a_offset * b_offset * k;

	constexpr unsigned int num_elems_processed_per_iteration = 16;

	// Configure kernel window
	Window win = calculate_max_window(*mm_result->info(), Steps(num_elems_processed_per_iteration));

	AccessWindowHorizontal mm_result_access(mm_result->info(), 0, num_elems_processed_per_iteration);

	// Accordingly with a_offset and b_offset, we can have 4 cases:
	// a_offset != 0 && b_offset != 0
	// a_offset = 0 && b_offset != 0
	// a_offset != 0 && b_offset = 0
	// a_offset = 0 && b_offset = 0
	if(a_offset != 0 && b_offset != 0)
	{
	AccessWindowStatic vector_sum_row_access(vector_sum_row->info(), 0, 0, vector_sum_row->info()->dimension(0), 0);
	AccessWindowHorizontal vector_sum_col_access(vector_sum_col->info(), 0, num_elems_processed_per_iteration);

	update_window_and_padding(win,
	vector_sum_col_access,
	vector_sum_row_access,
	mm_result_access);
	}
	else if(a_offset == 0 && b_offset != 0)
	{
	AccessWindowStatic vector_sum_row_access(vector_sum_row->info(), 0, 0, vector_sum_row->info()->dimension(0), 0);

	update_window_and_padding(win,
	vector_sum_row_access,
	mm_result_access);
	}
	else if(a_offset != 0 && b_offset == 0)
	{
	AccessWindowHorizontal vector_sum_col_access(vector_sum_col->info(), 0, num_elems_processed_per_iteration);

	update_window_and_padding(win,
	vector_sum_col_access,
	mm_result_access);
	}
	else
	{
	update_window_and_padding(win,
	mm_result_access);
	}

	INEKernel::configure(win);
	}

	void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadInfo &info)
	{
	ARM_COMPUTE_UNUSED(info);
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

	Window collapsed_window = window.collapse_if_possible(IKernel::window(), Window::DimZ);

	if(_a_offset != 0 && _b_offset != 0) // true, true
	{
	// Set window for vector_sum_col
	Window win_vector_sum_col(collapsed_window);
	win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0));
	if(!_slide_vector_sum_col)
	{
	win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
	}

	// Set window for vector_sum_row
	Window win_vector_sum_row(collapsed_window);
	win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0));
	win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0));

	Iterator vector_sum_col(_vector_sum_col, win_vector_sum_col);
	Iterator vector_sum_row(_vector_sum_row, win_vector_sum_row);
	Iterator mm_result(_mm_result, window);

	execute_window_loop(window, [&](const Coordinates & id)
	{
	// Compute the leftover term due to a_offset.
	int32x4x4_t a_offset_term_s32 =
	{
	{
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 0),
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 4),
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 8),
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 12)
	}
	};

	a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], _a_offset);
	a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], _a_offset);
	a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], _a_offset);
	a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], _a_offset);

	// Compute the leftover term due to b_offset.
	int32x4_t b_offset_term_s32 = vld1q_dup_s32(reinterpret_cast<const int32_t *>(vector_sum_row.ptr()) + id.y());
	b_offset_term_s32 = vmulq_n_s32(b_offset_term_s32, _b_offset);

	// Add a_offset_term_s32 and b_offset_term_s32
	int32x4x4_t offset_term_s32 =
	{
	{
	vdupq_n_s32(_k_offset),
	vdupq_n_s32(_k_offset),
	vdupq_n_s32(_k_offset),
	vdupq_n_s32(_k_offset)
	}
	};

	offset_term_s32.val[0] = vaddq_s32(offset_term_s32.val[0], vaddq_s32(a_offset_term_s32.val[0], b_offset_term_s32));
	offset_term_s32.val[1] = vaddq_s32(offset_term_s32.val[1], vaddq_s32(a_offset_term_s32.val[1], b_offset_term_s32));
	offset_term_s32.val[2] = vaddq_s32(offset_term_s32.val[2], vaddq_s32(a_offset_term_s32.val[2], b_offset_term_s32));
	offset_term_s32.val[3] = vaddq_s32(offset_term_s32.val[3], vaddq_s32(a_offset_term_s32.val[3], b_offset_term_s32));

	int32x4x4_t in_s32 =
	{
	{
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12)
	}
	};

	// Add the offset terms to GEMM's result
	in_s32.val[0] = vaddq_s32(in_s32.val[0], offset_term_s32.val[0]);
	in_s32.val[1] = vaddq_s32(in_s32.val[1], offset_term_s32.val[1]);
	in_s32.val[2] = vaddq_s32(in_s32.val[2], offset_term_s32.val[2]);
	in_s32.val[3] = vaddq_s32(in_s32.val[3], offset_term_s32.val[3]);

	// Store the result with the offset contribution
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]);
	},
	vector_sum_col, vector_sum_row, mm_result);
	}
	else if((_a_offset == 0) && (_b_offset != 0)) // false, true
	{
	// Set window for vector_sum_row
	Window win_vector_sum_row(collapsed_window);
	win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0));
	win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0));

	Iterator vector_sum_row(_vector_sum_row, win_vector_sum_row);
	Iterator mm_result(_mm_result, window);

	execute_window_loop(window, [&](const Coordinates & id)
	{
	// Compute the leftover term due to b_offset.
	int32x4_t b_offset_term_s32 = vld1q_dup_s32(reinterpret_cast<const int32_t *>(vector_sum_row.ptr()) + id.y());
	b_offset_term_s32 = vmulq_n_s32(b_offset_term_s32, _b_offset);

	int32x4x4_t in_s32 =
	{
	{
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12)
	}
	};

	// Add the offset terms to GEMM's result
	in_s32.val[0] = vaddq_s32(in_s32.val[0], b_offset_term_s32);
	in_s32.val[1] = vaddq_s32(in_s32.val[1], b_offset_term_s32);
	in_s32.val[2] = vaddq_s32(in_s32.val[2], b_offset_term_s32);
	in_s32.val[3] = vaddq_s32(in_s32.val[3], b_offset_term_s32);

	// Store the result with the offset contribution
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]);
	},
	vector_sum_row, mm_result);
	}
	else if((_a_offset != 0) && (_b_offset == 0)) // true, false
	{
	// Set window for vector_sum_col
	Window win_vector_sum_col(collapsed_window);
	win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0));
	if(!_slide_vector_sum_col)
	{
	win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
	}

	Iterator vector_sum_col(_vector_sum_col, win_vector_sum_col);
	Iterator mm_result(_mm_result, window);

	execute_window_loop(window, [&](const Coordinates & id)
	{
	// Compute the leftover term due to a_offset.
	int32x4x4_t a_offset_term_s32 =
	{
	{
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 0),
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 4),
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 8),
	vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 12)
	}
	};

	a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], _a_offset);
	a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], _a_offset);
	a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], _a_offset);
	a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], _a_offset);

	int32x4x4_t in_s32 =
	{
	{
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8),
	vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12)
	}
	};

	// Add the offset terms to GEMM's result
	in_s32.val[0] = vaddq_s32(in_s32.val[0], a_offset_term_s32.val[0]);
	in_s32.val[1] = vaddq_s32(in_s32.val[1], a_offset_term_s32.val[1]);
	in_s32.val[2] = vaddq_s32(in_s32.val[2], a_offset_term_s32.val[2]);
	in_s32.val[3] = vaddq_s32(in_s32.val[3], a_offset_term_s32.val[3]);

	// Store the result with the offset contribution
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]);
	vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]);
	},
	vector_sum_col, mm_result);
	}
	else // false, false
	{
	// No offset contribution from matrix A and matrix B
	return;
	}
	}