src/core/GLES_COMPUTE/kernels/GCSoftmaxLayerKernel.cpp - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2017-2020 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/GLES_COMPUTE/kernels/GCSoftmaxLayerKernel.h"

 #include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
 #include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
 #include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
 #include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/Window.h"
 #include "src/core/AccessWindowStatic.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "support/StringSupport.h"

 #include <set>
 #include <string>

 using namespace arm_compute;

 void GCLogits1DMaxKernel::configure(const IGCTensor *input, IGCTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_NULLPTR(output);

     // Softmax across the x dimension
     TensorShape output_shape{ input->info()->tensor_shape() };
     output_shape.set(0, 1);

     // Output auto initialization if not yet initialized
     auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type());

     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);

     _input  = input;
     _output = output;

     // Set build options
     std::set<std::string> build_opts;
     std::string           dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
     build_opts.insert("#define " + dt_name);
     build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
     build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
     build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
     build_opts.insert("#define SOFTMAX_LAYER_MAX");

     // Tell the kernel that the width is not a multiple of 8
     if((input->info()->dimension(0) % 8) != 0)
     {
         build_opts.insert("#define NON_MULTIPLE_OF_8");
     }

     // Create kernel
     _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("softmax_layer_max", build_opts));

     // Set fixed arguments
     unsigned int idx = 2 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
     _kernel.set_argument(idx++, input->info()->dimension(0));

     // Configure kernel window
     // The kernel loops over all elements in steps of 8
     const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 8);
     unsigned int       num_elems_written_per_iteration   = 1;
     if(input->info()->data_type() == DataType::F16)
     {
         num_elems_written_per_iteration = 2;
     }

     Window                 win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
     AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration);

     update_window_and_padding(win, input_access, output_access);

     output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));

     IGCKernel::configure(win);
 }

 GCLogits1DShiftExpSumKernel::GCLogits1DShiftExpSumKernel()
     : _input(nullptr), _max(nullptr), _output(nullptr), _sum(nullptr)
 {
 }

 void GCLogits1DShiftExpSumKernel::configure(const IGCTensor *input, const IGCTensor *max, IGCTensor *output, IGCTensor *sum)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_NULLPTR(max, sum, output);

     // Output auto initialization if not yet initialized
     auto_init_if_empty(*sum->info(), max->info()->tensor_shape(), 1, input->info()->data_type());
     auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());

     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, max, sum);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(max, sum);

     _input  = input;
     _max    = max;
     _output = output;
     _sum    = sum;

     // Set build options
     std::set<std::string> build_opts;
     std::string           dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
     build_opts.insert("#define " + dt_name);
     build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
     build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
     build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
     build_opts.insert("#define SOFTMAX_LAYER_SHIFT_EXP_SUM");

     // Tell the kernel that the width is not a multiple of 8
     if((input->info()->dimension(0) % 8) != 0)
     {
         build_opts.insert("#define NON_MULTIPLE_OF_8");
     }

     // Create kernel
     _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("softmax_layer_shift_exp_sum", build_opts));

     // Set fixed arguments
     unsigned int idx = 4 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
     _kernel.set_argument(idx++, input->info()->dimension(0));

     // Configure window
     // The kernel loops over all elements in steps of 8
     const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 8);
     unsigned int       num_elems_written_per_iteration   = 1;
     if(input->info()->data_type() == DataType::F16)
     {
         num_elems_written_per_iteration = 2;
     }

     Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

     AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal max_access(max->info(), 0, num_elems_written_per_iteration);
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal sum_access(sum->info(), 0, num_elems_written_per_iteration);

     update_window_and_padding(win, input_access, max_access, output_access, sum_access);

     output_access.set_valid_region(win, input->info()->valid_region());
     sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->info()->tensor_shape()));

     IGCKernel::configure(win);
 }

 void GCLogits1DShiftExpSumKernel::run(const Window &window)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);
     Window slice            = window_collapsed.first_slice_window_3D();

     _kernel.use();

     do
     {
         unsigned int idx     = 0;
         unsigned int binding = 1; // SSBO binding starts from 1.
         // Set inputs
         add_3D_tensor_argument(idx, _input, binding++, slice);
         add_3D_tensor_argument(idx, _max, binding++, slice);
         add_3D_tensor_argument(idx, _output, binding++, slice);
         add_3D_tensor_argument(idx, _sum, binding++, slice);
         _kernel.update_shader_params();
         enqueue(*this, slice);
     }
     while(window_collapsed.slide_window_slice_3D(slice));
 }

 GCLogits1DNormKernel::GCLogits1DNormKernel()
     : _input(nullptr), _sum(nullptr), _output(nullptr)
 {
 }

 void GCLogits1DNormKernel::configure(const IGCTensor *input, const IGCTensor *sum, IGCTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_NULLPTR(sum, output);

     // Output auto initialization if not yet initialized
     auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());

     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum, output);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);

     _input  = input;
     _sum    = sum;
     _output = output;

     // Set build options
     std::set<std::string> build_opts;
     std::string           dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
     build_opts.insert("#define " + dt_name);
     build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
     build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
     build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
     build_opts.insert("#define SOFTMAX_LAYER_NORM");

     // Create kernel
     _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("softmax_layer_norm", build_opts));

     // Configure window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
     unsigned int           num_elems_written_per_iteration   = 1;
     if(input->info()->data_type() == DataType::F16)
     {
         num_elems_written_per_iteration = 2;
     }

     Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

     AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
     AccessWindowStatic     sum_access(sum->info(), 0, 0, num_elems_written_per_iteration, sum->info()->dimension(1));
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);

     update_window_and_padding(win, input_access, sum_access, output_access);

     output_access.set_valid_region(win, input->info()->valid_region());

     IGCKernel::configure(win);
 }

 void GCLogits1DNormKernel::run(const Window &window)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);
     Window slice            = window_collapsed.first_slice_window_3D();

     _kernel.use();

     do
     {
         Window sum_slice = slice;
         sum_slice.set(Window::DimX, Window::Dimension(0, 1, 1));

         unsigned int idx     = 0;
         unsigned int binding = 1; // SSBO binding starts from 1.
         // Set inputs
         add_3D_tensor_argument(idx, _input, binding++, slice);
         add_3D_tensor_argument(idx, _sum, binding++, slice);
         add_3D_tensor_argument(idx, _output, binding++, slice);

         _kernel.update_shader_params();
         enqueue(*this, slice);
     }
     while(window_collapsed.slide_window_slice_3D(slice));
 }
	/*
	* Copyright (c) 2017-2020 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/GLES_COMPUTE/kernels/GCSoftmaxLayerKernel.h"

	#include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
	#include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
	#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
	#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/Utils.h"
	#include "arm_compute/core/Validate.h"
	#include "arm_compute/core/Window.h"
	#include "src/core/AccessWindowStatic.h"
	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"
	#include "support/StringSupport.h"

	#include <set>
	#include <string>

	using namespace arm_compute;

	void GCLogits1DMaxKernel::configure(const IGCTensor input, IGCTensor output)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_NULLPTR(output);

	// Softmax across the x dimension
	TensorShape output_shape{ input->info()->tensor_shape() };
	output_shape.set(0, 1);

	// Output auto initialization if not yet initialized
	auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type());

	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);

	_input = input;
	_output = output;

	// Set build options
	std::set<std::string> build_opts;
	std::string dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
	build_opts.insert("#define " + dt_name);
	build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
	build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
	build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
	build_opts.insert("#define SOFTMAX_LAYER_MAX");

	// Tell the kernel that the width is not a multiple of 8
	if((input->info()->dimension(0) % 8) != 0)
	{
	build_opts.insert("#define NON_MULTIPLE_OF_8");
	}

	// Create kernel
	_kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("softmax_layer_max", build_opts));

	// Set fixed arguments
	unsigned int idx = 2 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
	_kernel.set_argument(idx++, input->info()->dimension(0));

	// Configure kernel window
	// The kernel loops over all elements in steps of 8
	const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 8);
	unsigned int num_elems_written_per_iteration = 1;
	if(input->info()->data_type() == DataType::F16)
	{
	num_elems_written_per_iteration = 2;
	}

	Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
	AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
	AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration);

	update_window_and_padding(win, input_access, output_access);

	output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));

	IGCKernel::configure(win);
	}

	GCLogits1DShiftExpSumKernel::GCLogits1DShiftExpSumKernel()
	: _input(nullptr), _max(nullptr), _output(nullptr), _sum(nullptr)
	{
	}

	void GCLogits1DShiftExpSumKernel::configure(const IGCTensor input, const IGCTensor max, IGCTensor output, IGCTensor sum)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_NULLPTR(max, sum, output);

	// Output auto initialization if not yet initialized
	auto_init_if_empty(*sum->info(), max->info()->tensor_shape(), 1, input->info()->data_type());
	auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());

	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, max, sum);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(max, sum);

	_input = input;
	_max = max;
	_output = output;
	_sum = sum;

	// Set build options
	std::set<std::string> build_opts;
	std::string dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
	build_opts.insert("#define " + dt_name);
	build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
	build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
	build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
	build_opts.insert("#define SOFTMAX_LAYER_SHIFT_EXP_SUM");

	// Tell the kernel that the width is not a multiple of 8
	if((input->info()->dimension(0) % 8) != 0)
	{
	build_opts.insert("#define NON_MULTIPLE_OF_8");
	}

	// Create kernel
	_kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("softmax_layer_shift_exp_sum", build_opts));

	// Set fixed arguments
	unsigned int idx = 4 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
	_kernel.set_argument(idx++, input->info()->dimension(0));

	// Configure window
	// The kernel loops over all elements in steps of 8
	const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 8);
	unsigned int num_elems_written_per_iteration = 1;
	if(input->info()->data_type() == DataType::F16)
	{
	num_elems_written_per_iteration = 2;
	}

	Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

	AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
	AccessWindowHorizontal max_access(max->info(), 0, num_elems_written_per_iteration);
	AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
	AccessWindowHorizontal sum_access(sum->info(), 0, num_elems_written_per_iteration);

	update_window_and_padding(win, input_access, max_access, output_access, sum_access);

	output_access.set_valid_region(win, input->info()->valid_region());
	sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->info()->tensor_shape()));

	IGCKernel::configure(win);
	}

	void GCLogits1DShiftExpSumKernel::run(const Window &window)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);
	Window slice = window_collapsed.first_slice_window_3D();

	_kernel.use();

	do
	{
	unsigned int idx = 0;
	unsigned int binding = 1; // SSBO binding starts from 1.
	// Set inputs
	add_3D_tensor_argument(idx, _input, binding++, slice);
	add_3D_tensor_argument(idx, _max, binding++, slice);
	add_3D_tensor_argument(idx, _output, binding++, slice);
	add_3D_tensor_argument(idx, _sum, binding++, slice);
	_kernel.update_shader_params();
	enqueue(*this, slice);
	}
	while(window_collapsed.slide_window_slice_3D(slice));
	}

	GCLogits1DNormKernel::GCLogits1DNormKernel()
	: _input(nullptr), _sum(nullptr), _output(nullptr)
	{
	}

	void GCLogits1DNormKernel::configure(const IGCTensor input, const IGCTensor sum, IGCTensor *output)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_NULLPTR(sum, output);

	// Output auto initialization if not yet initialized
	auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());

	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum, output);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);

	_input = input;
	_sum = sum;
	_output = output;

	// Set build options
	std::set<std::string> build_opts;
	std::string dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
	build_opts.insert("#define " + dt_name);
	build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
	build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
	build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
	build_opts.insert("#define SOFTMAX_LAYER_NORM");

	// Create kernel
	_kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("softmax_layer_norm", build_opts));

	// Configure window
	constexpr unsigned int num_elems_processed_per_iteration = 8;
	unsigned int num_elems_written_per_iteration = 1;
	if(input->info()->data_type() == DataType::F16)
	{
	num_elems_written_per_iteration = 2;
	}

	Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

	AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
	AccessWindowStatic sum_access(sum->info(), 0, 0, num_elems_written_per_iteration, sum->info()->dimension(1));
	AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);

	update_window_and_padding(win, input_access, sum_access, output_access);

	output_access.set_valid_region(win, input->info()->valid_region());

	IGCKernel::configure(win);
	}

	void GCLogits1DNormKernel::run(const Window &window)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);
	Window slice = window_collapsed.first_slice_window_3D();

	_kernel.use();

	do
	{
	Window sum_slice = slice;
	sum_slice.set(Window::DimX, Window::Dimension(0, 1, 1));

	unsigned int idx = 0;
	unsigned int binding = 1; // SSBO binding starts from 1.
	// Set inputs
	add_3D_tensor_argument(idx, _input, binding++, slice);
	add_3D_tensor_argument(idx, _sum, binding++, slice);
	add_3D_tensor_argument(idx, _output, binding++, slice);

	_kernel.update_shader_params();
	enqueue(*this, slice);
	}
	while(window_collapsed.slide_window_slice_3D(slice));
	}