src/core/NEON/kernels/NEGaussianPyramidKernel.cpp - platform/external/ComputeLibrary - Git at Google

 /*
  * 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/NEGaussianPyramidKernel.h"

 #include "arm_compute/core/Coordinates.h"
 #include "arm_compute/core/Error.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/NEON/INEKernel.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.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;

 NEGaussianPyramidHorKernel::NEGaussianPyramidHorKernel()
     : _border_size(0), _l2_load_offset(0)
 {
 }

 BorderSize NEGaussianPyramidHorKernel::border_size() const
 {
     return _border_size;
 }

 void NEGaussianPyramidHorKernel::configure(const ITensor *input, ITensor *output, bool border_undefined)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S16);
     ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != 2 * output->info()->dimension(0));
     ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != output->info()->dimension(1));

     for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
     {
         ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i));
     }

     _input       = input;
     _output      = output;
     _border_size = BorderSize(border_undefined ? 0 : 2, 2);

     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
     constexpr unsigned int num_elems_read_per_iteration      = 32;
     constexpr unsigned int num_elems_written_per_iteration   = 8;
     constexpr float        scale_x                           = 0.5f;

     Window                 win = calculate_max_window_horizontal(*input->info(), Steps(num_elems_processed_per_iteration), border_undefined, border_size());
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration, scale_x);

     // Sub sampling selects odd pixels (1, 3, 5, ...) for images with even
     // width and even pixels (0, 2, 4, ...) for images with odd width. (Whether
     // a pixel is even or odd is determined based on the tensor shape not the
     // valid region!)
     // Thus the offset from which the first pixel (L2) for the convolution is
     // loaded depends on the anchor and shape of the valid region.
     // In the case of an even shape (= even image width) we need to load L2
     // from -2 if the anchor is odd and from -1 if the anchor is even. That
     // makes sure that L2 is always loaded from an odd pixel.
     // On the other hand, for an odd shape (= odd image width) we need to load
     // L2 from -1 if the anchor is odd and from -2 if the anchor is even to
     // achieve the opposite effect.
     // The condition can be simplified to checking whether anchor + shape is
     // odd (-2) or even (-1) as only adding an odd and an even number will have
     // an odd result.
     _l2_load_offset = -border_size().left;

     if((_input->info()->valid_region().anchor[0] + _input->info()->valid_region().shape[0]) % 2 == 0)
     {
         _l2_load_offset += 1;
     }

     update_window_and_padding(win,
                               AccessWindowHorizontal(input->info(), _l2_load_offset, num_elems_read_per_iteration),
                               output_access);

     ValidRegion valid_region = input->info()->valid_region();
     valid_region.anchor.set(0, std::ceil((valid_region.anchor[0] + (border_undefined ? border_size().left : 0)) / 2.f));
     valid_region.shape.set(0, (valid_region.shape[0] - (border_undefined ? border_size().right : 0)) / 2 - valid_region.anchor[0]);

     output_access.set_valid_region(win, valid_region);

     INEKernel::configure(win);
 }

 void NEGaussianPyramidHorKernel::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);
     ARM_COMPUTE_ERROR_ON(window.x().step() % 2);

     static const int16x8_t six  = vdupq_n_s16(6);
     static const int16x8_t four = vdupq_n_s16(4);

     Window win_in(window);
     win_in.shift(Window::DimX, _l2_load_offset);

     Iterator in(_input, win_in);

     // The output is half the width of the input
     Window win_out(window);
     win_out.scale(Window::DimX, 0.5f);

     Iterator out(_output, win_out);

     execute_window_loop(window, [&](const Coordinates & id)
     {
         const uint8x16x2_t data_2q   = vld2q_u8(in.ptr());
         const uint8x16_t &data_even = data_2q.val[0];
         const uint8x16_t &data_odd  = data_2q.val[1];

         const int16x8_t data_l2 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(data_even)));
         const int16x8_t data_l1 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(data_odd)));
         const int16x8_t data_m  = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(vextq_u8(data_even, data_even, 1))));
         const int16x8_t data_r1 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(vextq_u8(data_odd, data_odd, 1))));
         const int16x8_t data_r2 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(vextq_u8(data_even, data_even, 2))));

         int16x8_t out_val = vaddq_s16(data_l2, data_r2);
         out_val           = vmlaq_s16(out_val, data_l1, four);
         out_val           = vmlaq_s16(out_val, data_m, six);
         out_val           = vmlaq_s16(out_val, data_r1, four);

         vst1q_s16(reinterpret_cast<int16_t *>(out.ptr()), out_val);
     },
     in, out);
 }

 NEGaussianPyramidVertKernel::NEGaussianPyramidVertKernel()
     : _t2_load_offset(0)
 {
 }

 BorderSize NEGaussianPyramidVertKernel::border_size() const
 {
     return BorderSize(2, 0);
 }

 void NEGaussianPyramidVertKernel::configure(const ITensor *input, ITensor *output, bool border_undefined)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S16);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);

     ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != output->info()->dimension(0));
     ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != 2 * output->info()->dimension(1));

     for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
     {
         ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i));
     }

     _input  = input;
     _output = output;

     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
     constexpr unsigned int num_rows_processed_per_iteration  = 2;

     constexpr unsigned int num_elems_written_per_iteration = 16;
     constexpr unsigned int num_rows_written_per_iteration  = 1;

     constexpr unsigned int num_elems_read_per_iteration = 16;
     constexpr unsigned int num_rows_read_per_iteration  = 5;

     constexpr float scale_y = 0.5f;

     Window                win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration, num_rows_processed_per_iteration), border_undefined, border_size());
     AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration, num_rows_written_per_iteration, 1.f, scale_y);

     // Determine whether we need to load even or odd rows. See above for a
     // detailed explanation.
     _t2_load_offset = -border_size().top;

     if((_input->info()->valid_region().anchor[1] + _input->info()->valid_region().shape[1]) % 2 == 0)
     {
         _t2_load_offset += 1;
     }

     update_window_and_padding(win,
                               AccessWindowRectangle(input->info(), 0, _t2_load_offset, num_elems_read_per_iteration, num_rows_read_per_iteration),
                               output_access);

     ValidRegion valid_region = input->info()->valid_region();
     valid_region.anchor.set(1, std::ceil((valid_region.anchor[1] + (border_undefined ? border_size().top : 0)) / 2.f));
     valid_region.shape.set(1, (valid_region.shape[1] - (border_undefined ? border_size().bottom : 0)) / 2 - valid_region.anchor[1]);

     output_access.set_valid_region(win, valid_region);

     INEKernel::configure(win);
 }

 void NEGaussianPyramidVertKernel::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);
     ARM_COMPUTE_ERROR_ON(window.x().step() != 16);
     ARM_COMPUTE_ERROR_ON(window.y().step() % 2);
     ARM_COMPUTE_ERROR_ON(_input->buffer() == nullptr);

     static const uint16x8_t six  = vdupq_n_u16(6);
     static const uint16x8_t four = vdupq_n_u16(4);

     Window win_in(window);
     // Need to load two times 8 values instead of 16 values once
     win_in.set_dimension_step(Window::DimX, 8);
     win_in.shift(Window::DimY, _t2_load_offset);

     Iterator in(_input, win_in);

     // Output's height is half of input's
     Window win_out(window);
     win_out.scale(Window::DimY, 0.5f);

     Iterator out(_output, win_out);

     const uint8_t *input_top2_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 0));
     const uint8_t *input_top_ptr  = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 1));
     const uint8_t *input_mid_ptr  = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 2));
     const uint8_t *input_low_ptr  = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 3));
     const uint8_t *input_low2_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 4));

     execute_window_loop(window, [&](const Coordinates & id)
     {
         // Low data
         const uint16x8_t data_low_t2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top2_ptr + in.offset())));
         const uint16x8_t data_low_t1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top_ptr + in.offset())));
         const uint16x8_t data_low_m  = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_mid_ptr + in.offset())));
         const uint16x8_t data_low_b1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low_ptr + in.offset())));
         const uint16x8_t data_low_b2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low2_ptr + in.offset())));

         uint16x8_t out_low = vaddq_u16(data_low_t2, data_low_b2);
         out_low            = vmlaq_u16(out_low, data_low_t1, four);
         out_low            = vmlaq_u16(out_low, data_low_m, six);
         out_low            = vmlaq_u16(out_low, data_low_b1, four);

         in.increment(Window::DimX);

         // High data
         const uint16x8_t data_high_t2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top2_ptr + in.offset())));
         const uint16x8_t data_high_t1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top_ptr + in.offset())));
         const uint16x8_t data_high_m  = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_mid_ptr + in.offset())));
         const uint16x8_t data_high_b1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low_ptr + in.offset())));
         const uint16x8_t data_high_b2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low2_ptr + in.offset())));

         uint16x8_t out_high = vaddq_u16(data_high_t2, data_high_b2);
         out_high            = vmlaq_u16(out_high, data_high_t1, four);
         out_high            = vmlaq_u16(out_high, data_high_m, six);
         out_high            = vmlaq_u16(out_high, data_high_b1, four);

         vst1q_u8(out.ptr(), vcombine_u8(vqshrn_n_u16(out_low, 8), vqshrn_n_u16(out_high, 8)));
     },
     in, out);
 }
	/*
	* 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/NEGaussianPyramidKernel.h"

	#include "arm_compute/core/Coordinates.h"
	#include "arm_compute/core/Error.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/ITensor.h"
	#include "arm_compute/core/NEON/INEKernel.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/Types.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;

	NEGaussianPyramidHorKernel::NEGaussianPyramidHorKernel()
	: _border_size(0), _l2_load_offset(0)
	{
	}

	BorderSize NEGaussianPyramidHorKernel::border_size() const
	{
	return _border_size;
	}

	void NEGaussianPyramidHorKernel::configure(const ITensor input, ITensor output, bool border_undefined)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S16);
	ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != 2 * output->info()->dimension(0));
	ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != output->info()->dimension(1));

	for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
	{
	ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i));
	}

	_input = input;
	_output = output;
	_border_size = BorderSize(border_undefined ? 0 : 2, 2);

	// Configure kernel window
	constexpr unsigned int num_elems_processed_per_iteration = 16;
	constexpr unsigned int num_elems_read_per_iteration = 32;
	constexpr unsigned int num_elems_written_per_iteration = 8;
	constexpr float scale_x = 0.5f;

	Window win = calculate_max_window_horizontal(*input->info(), Steps(num_elems_processed_per_iteration), border_undefined, border_size());
	AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration, scale_x);

	// Sub sampling selects odd pixels (1, 3, 5, ...) for images with even
	// width and even pixels (0, 2, 4, ...) for images with odd width. (Whether
	// a pixel is even or odd is determined based on the tensor shape not the
	// valid region!)
	// Thus the offset from which the first pixel (L2) for the convolution is
	// loaded depends on the anchor and shape of the valid region.
	// In the case of an even shape (= even image width) we need to load L2
	// from -2 if the anchor is odd and from -1 if the anchor is even. That
	// makes sure that L2 is always loaded from an odd pixel.
	// On the other hand, for an odd shape (= odd image width) we need to load
	// L2 from -1 if the anchor is odd and from -2 if the anchor is even to
	// achieve the opposite effect.
	// The condition can be simplified to checking whether anchor + shape is
	// odd (-2) or even (-1) as only adding an odd and an even number will have
	// an odd result.
	_l2_load_offset = -border_size().left;

	if((_input->info()->valid_region().anchor[0] + _input->info()->valid_region().shape[0]) % 2 == 0)
	{
	_l2_load_offset += 1;
	}

	update_window_and_padding(win,
	AccessWindowHorizontal(input->info(), _l2_load_offset, num_elems_read_per_iteration),
	output_access);

	ValidRegion valid_region = input->info()->valid_region();
	valid_region.anchor.set(0, std::ceil((valid_region.anchor[0] + (border_undefined ? border_size().left : 0)) / 2.f));
	valid_region.shape.set(0, (valid_region.shape[0] - (border_undefined ? border_size().right : 0)) / 2 - valid_region.anchor[0]);

	output_access.set_valid_region(win, valid_region);

	INEKernel::configure(win);
	}

	void NEGaussianPyramidHorKernel::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);
	ARM_COMPUTE_ERROR_ON(window.x().step() % 2);

	static const int16x8_t six = vdupq_n_s16(6);
	static const int16x8_t four = vdupq_n_s16(4);

	Window win_in(window);
	win_in.shift(Window::DimX, _l2_load_offset);

	Iterator in(_input, win_in);

	// The output is half the width of the input
	Window win_out(window);
	win_out.scale(Window::DimX, 0.5f);

	Iterator out(_output, win_out);

	execute_window_loop(window, [&](const Coordinates & id)
	{
	const uint8x16x2_t data_2q = vld2q_u8(in.ptr());
	const uint8x16_t &data_even = data_2q.val[0];
	const uint8x16_t &data_odd = data_2q.val[1];

	const int16x8_t data_l2 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(data_even)));
	const int16x8_t data_l1 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(data_odd)));
	const int16x8_t data_m = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(vextq_u8(data_even, data_even, 1))));
	const int16x8_t data_r1 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(vextq_u8(data_odd, data_odd, 1))));
	const int16x8_t data_r2 = vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(vextq_u8(data_even, data_even, 2))));

	int16x8_t out_val = vaddq_s16(data_l2, data_r2);
	out_val = vmlaq_s16(out_val, data_l1, four);
	out_val = vmlaq_s16(out_val, data_m, six);
	out_val = vmlaq_s16(out_val, data_r1, four);

	vst1q_s16(reinterpret_cast<int16_t *>(out.ptr()), out_val);
	},
	in, out);
	}

	NEGaussianPyramidVertKernel::NEGaussianPyramidVertKernel()
	: _t2_load_offset(0)
	{
	}

	BorderSize NEGaussianPyramidVertKernel::border_size() const
	{
	return BorderSize(2, 0);
	}

	void NEGaussianPyramidVertKernel::configure(const ITensor input, ITensor output, bool border_undefined)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S16);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);

	ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != output->info()->dimension(0));
	ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != 2 * output->info()->dimension(1));

	for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
	{
	ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i));
	}

	_input = input;
	_output = output;

	// Configure kernel window
	constexpr unsigned int num_elems_processed_per_iteration = 16;
	constexpr unsigned int num_rows_processed_per_iteration = 2;

	constexpr unsigned int num_elems_written_per_iteration = 16;
	constexpr unsigned int num_rows_written_per_iteration = 1;

	constexpr unsigned int num_elems_read_per_iteration = 16;
	constexpr unsigned int num_rows_read_per_iteration = 5;

	constexpr float scale_y = 0.5f;

	Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration, num_rows_processed_per_iteration), border_undefined, border_size());
	AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration, num_rows_written_per_iteration, 1.f, scale_y);

	// Determine whether we need to load even or odd rows. See above for a
	// detailed explanation.
	_t2_load_offset = -border_size().top;

	if((_input->info()->valid_region().anchor[1] + _input->info()->valid_region().shape[1]) % 2 == 0)
	{
	_t2_load_offset += 1;
	}

	update_window_and_padding(win,
	AccessWindowRectangle(input->info(), 0, _t2_load_offset, num_elems_read_per_iteration, num_rows_read_per_iteration),
	output_access);

	ValidRegion valid_region = input->info()->valid_region();
	valid_region.anchor.set(1, std::ceil((valid_region.anchor[1] + (border_undefined ? border_size().top : 0)) / 2.f));
	valid_region.shape.set(1, (valid_region.shape[1] - (border_undefined ? border_size().bottom : 0)) / 2 - valid_region.anchor[1]);

	output_access.set_valid_region(win, valid_region);

	INEKernel::configure(win);
	}

	void NEGaussianPyramidVertKernel::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);
	ARM_COMPUTE_ERROR_ON(window.x().step() != 16);
	ARM_COMPUTE_ERROR_ON(window.y().step() % 2);
	ARM_COMPUTE_ERROR_ON(_input->buffer() == nullptr);

	static const uint16x8_t six = vdupq_n_u16(6);
	static const uint16x8_t four = vdupq_n_u16(4);

	Window win_in(window);
	// Need to load two times 8 values instead of 16 values once
	win_in.set_dimension_step(Window::DimX, 8);
	win_in.shift(Window::DimY, _t2_load_offset);

	Iterator in(_input, win_in);

	// Output's height is half of input's
	Window win_out(window);
	win_out.scale(Window::DimY, 0.5f);

	Iterator out(_output, win_out);

	const uint8_t *input_top2_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 0));
	const uint8_t *input_top_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 1));
	const uint8_t *input_mid_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 2));
	const uint8_t *input_low_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 3));
	const uint8_t *input_low2_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, 4));

	execute_window_loop(window, [&](const Coordinates & id)
	{
	// Low data
	const uint16x8_t data_low_t2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top2_ptr + in.offset())));
	const uint16x8_t data_low_t1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top_ptr + in.offset())));
	const uint16x8_t data_low_m = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_mid_ptr + in.offset())));
	const uint16x8_t data_low_b1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low_ptr + in.offset())));
	const uint16x8_t data_low_b2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low2_ptr + in.offset())));

	uint16x8_t out_low = vaddq_u16(data_low_t2, data_low_b2);
	out_low = vmlaq_u16(out_low, data_low_t1, four);
	out_low = vmlaq_u16(out_low, data_low_m, six);
	out_low = vmlaq_u16(out_low, data_low_b1, four);

	in.increment(Window::DimX);

	// High data
	const uint16x8_t data_high_t2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top2_ptr + in.offset())));
	const uint16x8_t data_high_t1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_top_ptr + in.offset())));
	const uint16x8_t data_high_m = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_mid_ptr + in.offset())));
	const uint16x8_t data_high_b1 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low_ptr + in.offset())));
	const uint16x8_t data_high_b2 = vreinterpretq_u16_s16(vld1q_s16(reinterpret_cast<const int16_t *>(input_low2_ptr + in.offset())));

	uint16x8_t out_high = vaddq_u16(data_high_t2, data_high_b2);
	out_high = vmlaq_u16(out_high, data_high_t1, four);
	out_high = vmlaq_u16(out_high, data_high_m, six);
	out_high = vmlaq_u16(out_high, data_high_b1, four);

	vst1q_u8(out.ptr(), vcombine_u8(vqshrn_n_u16(out_low, 8), vqshrn_n_u16(out_high, 8)));
	},
	in, out);
	}