src/core/CL/kernels/CLNormalizationLayerKernel.cpp - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2017-2021 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 "src/core/CL/kernels/CLNormalizationLayerKernel.h"

 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/CL/CLKernelLibrary.h"
 #include "arm_compute/core/CL/ICLTensor.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Window.h"
 #include "src/core/AccessWindowStatic.h"
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/NormalizationHelpers.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "support/StringSupport.h"

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, NormalizationLayerInfo norm_info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NCHW, DataLayout::NHWC);
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);

     ARM_COMPUTE_RETURN_ERROR_ON_MSG(!(norm_info.norm_size() % 2), "Normalization size should be odd");

     // Checks performed when output is configured
     if(output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
     }

     return Status{};
 }

 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, NormalizationLayerInfo norm_info)
 {
     // Output tensor auto initialization if not yet initialized
     auto_init_if_empty(*output, *input->clone());

     bool             window_changed = false;
     Window           win;
     const DataLayout data_layout = input->data_layout();
     if(data_layout == DataLayout::NCHW)
     {
         const unsigned int vec_size_x           = adjust_vec_size(max_cl_vector_width / input->element_size(), input->dimension(0));
         const unsigned int norm_idx             = get_normalization_dimension_index(input->data_layout(), norm_info);
         const bool         is_norm_across_width = norm_idx == 0;

         const unsigned int norm_radius = norm_info.norm_size() / 2;
         // Border / padding calculation:
         // For NCHW no border handling is impelmeneted in the kernel in the x axis.
         // This means the x axis is fully-padded depending on vec_size_x and norm_size
         // E.G. for input x dimension = 3, norm_size = 3 (radius = 1), vec_size_x = 2 ('#' is element 'p' is padding):
         // In : |p|#|#|#|p|p|
         // Out:   |#|#|#|p|
         // The output has 1 right padding because of the vec_size_x.
         // The input has 1 left padding because radius = 1.
         // The input has 2 right padding because of radius = 1 AND because of the extra output padding
         const unsigned int border_width_left  = is_norm_across_width ? norm_radius : 0;
         const unsigned int border_width_right = is_norm_across_width ? norm_radius + (vec_size_x - input->dimension(0) % vec_size_x) : 0;
         const BorderSize   border_size        = BorderSize(0, border_width_right, 0, border_width_left);

         win = calculate_max_window(*input, Steps(vec_size_x));

         // We do not use a Rectangle window for IN_MAP_2D as we clamp the top and bottom accesses inside the kernel, avoiding padding
         // Reads can occur within the valid region of the input
         if(is_norm_across_width)
         {
             AccessWindowStatic input_access(input, -border_size.left, 0, input->dimension(0) + border_size.right, 0);
             window_changed = window_changed || update_window_and_padding(win, input_access);
         }
         else
         {
             AccessWindowHorizontal input_access(input, -border_size.left, vec_size_x);
             window_changed = window_changed || update_window_and_padding(win, input_access);
         }

         AccessWindowHorizontal output_access(output, 0, vec_size_x);
         window_changed = window_changed || update_window_and_padding(win, output_access);
     }
     else
     {
         unsigned int vec_size_x = adjust_vec_size(max_cl_vector_width / input->element_size(), input->dimension(0));
         if(norm_info.is_cross_map())
         {
             vec_size_x = 1;
         }
         win = calculate_max_window(*input, Steps(vec_size_x));
     }
     Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
     return std::make_pair(err, win);
 }
 } // namespace

 CLNormalizationLayerKernel::CLNormalizationLayerKernel()
     : _input(nullptr), _output(nullptr), _border_size(0), _is_norm_across_width(false)
 {
     _type = CLKernelType::ELEMENTWISE;
 }

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

 void CLNormalizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info)
 {
     configure(CLKernelLibrary::get().get_compile_context(), input, output, norm_info);
 }

 void CLNormalizationLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     auto padding_info = get_padding_info({ input, output });

     // Perform validation step
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), norm_info));
     auto win_config = validate_and_configure_window(input->info(), output->info(), norm_info);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);

     _input  = input;
     _output = output;

     const DataLayout data_layout          = input->info()->data_layout();
     unsigned int     vec_size_x           = adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0));
     int              vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x;
     if(norm_info.is_cross_map() && data_layout == DataLayout::NHWC)
     {
         vec_size_x           = 1;
         vec_size_x_leftovers = 0;
     }

     if(data_layout == DataLayout::NCHW)
     {
         const unsigned int norm_idx    = get_normalization_dimension_index(data_layout, norm_info);
         _is_norm_across_width          = norm_idx == 0;
         const unsigned int norm_radius = norm_info.norm_size() / 2;
         // Border / padding calculation:
         // For NCHW no border handling is impelmeneted in the kernel in the x axis.
         // This means the x axis is fully-padded depending on vec_size_x and norm_size
         // E.G. for input x dimension = 3, norm_size = 3 (radius = 1), vec_size_x = 2 ('#' is element 'p' is padding):
         // In : |p|#|#|#|p|p|
         // Out:   |#|#|#|p|
         // The output has 1 right padding because of the vec_size_x.
         // The input has 1 left padding because radius = 1.
         // The input has 2 right padding because of radius = 1 AND the extra output padding
         const unsigned int border_width_left  = _is_norm_across_width ? norm_radius : 0;
         const unsigned int border_width_right = _is_norm_across_width ? norm_radius + (vec_size_x - input->info()->dimension(0) % vec_size_x) : 0;
         _border_size                          = BorderSize(0, border_width_right, 0, border_width_left);
     }

     const bool is_in_map_2D = (norm_info.type() == NormType::IN_MAP_2D);

     // Set build options
     CLBuildOptions build_opts;
     build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
     build_opts.add_option(("-DCOEFF=" + float_to_string_with_full_precision(norm_info.scale_coeff())));
     build_opts.add_option(("-DBETA=" + float_to_string_with_full_precision(norm_info.beta())));
     build_opts.add_option(("-DKAPPA=" + float_to_string_with_full_precision(norm_info.kappa())));
     build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x)));
     build_opts.add_option(("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_x_leftovers)));
     build_opts.add_option(("-DRADIUS=" + support::cpp11::to_string(norm_info.norm_size() / 2)));
     build_opts.add_option(("-DNUM_SLICES=" + support::cpp11::to_string(input->info()->dimension(2))));
     build_opts.add_option_if(is_in_map_2D, "-DIN_MAP_2D");
     build_opts.add_option_if(norm_info.is_in_map() || (data_layout == DataLayout::NHWC && norm_info.is_cross_map()), "-DWIDTH_SIZE=" + support::cpp11::to_string(input->info()->dimension(0)));
     build_opts.add_option_if(norm_info.is_in_map() && data_layout == DataLayout::NHWC, "-DDIM1_SIZE=" + support::cpp11::to_string(input->info()->dimension(1)));

     // Create kernel
     std::string kernel_name;
     if(norm_info.is_in_map())
     {
         kernel_name = "normalization_layer_in_map_" + lower_string(string_from_data_layout(data_layout));
     }
     else
     {
         kernel_name = "normalization_layer_cross_map_" + lower_string(string_from_data_layout(data_layout));
     }
     _kernel = create_kernel(compile_context, kernel_name, build_opts.options());

     // Configure kernel window
     ICLKernel::configure_internal(win_config.second);

     // Set config_id for enabling LWS tuning
     _config_id = "normalization_layer_";
     _config_id += lower_string(string_from_data_type(input->info()->data_type()));
     _config_id += "_";
     _config_id += support::cpp11::to_string(static_cast<std::underlying_type<NormType>::type>(norm_info.type()));
     _config_id += "_";
     _config_id += support::cpp11::to_string(norm_info.norm_size());
     _config_id += "_";
     _config_id += support::cpp11::to_string(input->info()->dimension(0));
     _config_id += "_";
     _config_id += support::cpp11::to_string(input->info()->dimension(1));
     if(data_layout == DataLayout::NHWC)
     {
         ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
     }
 }

 Status CLNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, NormalizationLayerInfo norm_info)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, norm_info));
     ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), norm_info).first);

     return Status{};
 }

 void CLNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     const int collapsed_dimension = _is_norm_across_width ? Window::DimZ : 4;
     Window    window_collapsed    = window.collapse_if_possible(ICLKernel::window(), collapsed_dimension);
     Window    slice               = window_collapsed.first_slice_window_3D();

     do
     {
         unsigned int idx = 0;
         add_3D_tensor_argument(idx, _input, slice);
         add_3D_tensor_argument(idx, _output, slice);
         enqueue(queue, *this, slice, lws_hint());
     }
     while(window_collapsed.slide_window_slice_3D(slice));
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2017-2021 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 "src/core/CL/kernels/CLNormalizationLayerKernel.h"

	#include "arm_compute/core/CL/CLHelpers.h"
	#include "arm_compute/core/CL/CLKernelLibrary.h"
	#include "arm_compute/core/CL/ICLTensor.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/Utils.h"
	#include "arm_compute/core/Window.h"
	#include "src/core/AccessWindowStatic.h"
	#include "src/core/CL/CLValidate.h"
	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/NormalizationHelpers.h"
	#include "src/core/helpers/WindowHelpers.h"
	#include "support/StringSupport.h"

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo output, NormalizationLayerInfo norm_info)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NCHW, DataLayout::NHWC);
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);

	ARM_COMPUTE_RETURN_ERROR_ON_MSG(!(norm_info.norm_size() % 2), "Normalization size should be odd");

	// Checks performed when output is configured
	if(output->total_size() != 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
	}

	return Status{};
	}

	std::pair<Status, Window> validate_and_configure_window(ITensorInfo input, ITensorInfo output, NormalizationLayerInfo norm_info)
	{
	// Output tensor auto initialization if not yet initialized
	auto_init_if_empty(output, input->clone());

	bool window_changed = false;
	Window win;
	const DataLayout data_layout = input->data_layout();
	if(data_layout == DataLayout::NCHW)
	{
	const unsigned int vec_size_x = adjust_vec_size(max_cl_vector_width / input->element_size(), input->dimension(0));
	const unsigned int norm_idx = get_normalization_dimension_index(input->data_layout(), norm_info);
	const bool is_norm_across_width = norm_idx == 0;

	const unsigned int norm_radius = norm_info.norm_size() / 2;
	// Border / padding calculation:
	// For NCHW no border handling is impelmeneted in the kernel in the x axis.
	// This means the x axis is fully-padded depending on vec_size_x and norm_size
	// E.G. for input x dimension = 3, norm_size = 3 (radius = 1), vec_size_x = 2 ('#' is element 'p' is padding):
	// In : \|p\|#\|#\|#\|p\|p\|
	// Out: \|#\|#\|#\|p\|
	// The output has 1 right padding because of the vec_size_x.
	// The input has 1 left padding because radius = 1.
	// The input has 2 right padding because of radius = 1 AND because of the extra output padding
	const unsigned int border_width_left = is_norm_across_width ? norm_radius : 0;
	const unsigned int border_width_right = is_norm_across_width ? norm_radius + (vec_size_x - input->dimension(0) % vec_size_x) : 0;
	const BorderSize border_size = BorderSize(0, border_width_right, 0, border_width_left);

	win = calculate_max_window(*input, Steps(vec_size_x));

	// We do not use a Rectangle window for IN_MAP_2D as we clamp the top and bottom accesses inside the kernel, avoiding padding
	// Reads can occur within the valid region of the input
	if(is_norm_across_width)
	{
	AccessWindowStatic input_access(input, -border_size.left, 0, input->dimension(0) + border_size.right, 0);
	window_changed = window_changed \|\| update_window_and_padding(win, input_access);
	}
	else
	{
	AccessWindowHorizontal input_access(input, -border_size.left, vec_size_x);
	window_changed = window_changed \|\| update_window_and_padding(win, input_access);
	}

	AccessWindowHorizontal output_access(output, 0, vec_size_x);
	window_changed = window_changed \|\| update_window_and_padding(win, output_access);
	}
	else
	{
	unsigned int vec_size_x = adjust_vec_size(max_cl_vector_width / input->element_size(), input->dimension(0));
	if(norm_info.is_cross_map())
	{
	vec_size_x = 1;
	}
	win = calculate_max_window(*input, Steps(vec_size_x));
	}
	Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
	return std::make_pair(err, win);
	}
	} // namespace

	CLNormalizationLayerKernel::CLNormalizationLayerKernel()
	: _input(nullptr), _output(nullptr), _border_size(0), _is_norm_across_width(false)
	{
	_type = CLKernelType::ELEMENTWISE;
	}

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

	void CLNormalizationLayerKernel::configure(const ICLTensor input, ICLTensor output, NormalizationLayerInfo norm_info)
	{
	configure(CLKernelLibrary::get().get_compile_context(), input, output, norm_info);
	}

	void CLNormalizationLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor input, ICLTensor output, NormalizationLayerInfo norm_info)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
	auto padding_info = get_padding_info({ input, output });

	// Perform validation step
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), norm_info));
	auto win_config = validate_and_configure_window(input->info(), output->info(), norm_info);
	ARM_COMPUTE_ERROR_THROW_ON(win_config.first);

	_input = input;
	_output = output;

	const DataLayout data_layout = input->info()->data_layout();
	unsigned int vec_size_x = adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0));
	int vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x;
	if(norm_info.is_cross_map() && data_layout == DataLayout::NHWC)
	{
	vec_size_x = 1;
	vec_size_x_leftovers = 0;
	}

	if(data_layout == DataLayout::NCHW)
	{
	const unsigned int norm_idx = get_normalization_dimension_index(data_layout, norm_info);
	_is_norm_across_width = norm_idx == 0;
	const unsigned int norm_radius = norm_info.norm_size() / 2;
	// Border / padding calculation:
	// For NCHW no border handling is impelmeneted in the kernel in the x axis.
	// This means the x axis is fully-padded depending on vec_size_x and norm_size
	// E.G. for input x dimension = 3, norm_size = 3 (radius = 1), vec_size_x = 2 ('#' is element 'p' is padding):
	// In : \|p\|#\|#\|#\|p\|p\|
	// Out: \|#\|#\|#\|p\|
	// The output has 1 right padding because of the vec_size_x.
	// The input has 1 left padding because radius = 1.
	// The input has 2 right padding because of radius = 1 AND the extra output padding
	const unsigned int border_width_left = _is_norm_across_width ? norm_radius : 0;
	const unsigned int border_width_right = _is_norm_across_width ? norm_radius + (vec_size_x - input->info()->dimension(0) % vec_size_x) : 0;
	_border_size = BorderSize(0, border_width_right, 0, border_width_left);
	}

	const bool is_in_map_2D = (norm_info.type() == NormType::IN_MAP_2D);

	// Set build options
	CLBuildOptions build_opts;
	build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
	build_opts.add_option(("-DCOEFF=" + float_to_string_with_full_precision(norm_info.scale_coeff())));
	build_opts.add_option(("-DBETA=" + float_to_string_with_full_precision(norm_info.beta())));
	build_opts.add_option(("-DKAPPA=" + float_to_string_with_full_precision(norm_info.kappa())));
	build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x)));
	build_opts.add_option(("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_x_leftovers)));
	build_opts.add_option(("-DRADIUS=" + support::cpp11::to_string(norm_info.norm_size() / 2)));
	build_opts.add_option(("-DNUM_SLICES=" + support::cpp11::to_string(input->info()->dimension(2))));
	build_opts.add_option_if(is_in_map_2D, "-DIN_MAP_2D");
	build_opts.add_option_if(norm_info.is_in_map() \|\| (data_layout == DataLayout::NHWC && norm_info.is_cross_map()), "-DWIDTH_SIZE=" + support::cpp11::to_string(input->info()->dimension(0)));
	build_opts.add_option_if(norm_info.is_in_map() && data_layout == DataLayout::NHWC, "-DDIM1_SIZE=" + support::cpp11::to_string(input->info()->dimension(1)));

	// Create kernel
	std::string kernel_name;
	if(norm_info.is_in_map())
	{
	kernel_name = "normalization_layer_in_map_" + lower_string(string_from_data_layout(data_layout));
	}
	else
	{
	kernel_name = "normalization_layer_cross_map_" + lower_string(string_from_data_layout(data_layout));
	}
	_kernel = create_kernel(compile_context, kernel_name, build_opts.options());

	// Configure kernel window
	ICLKernel::configure_internal(win_config.second);

	// Set config_id for enabling LWS tuning
	_config_id = "normalization_layer_";
	_config_id += lower_string(string_from_data_type(input->info()->data_type()));
	_config_id += "_";
	_config_id += support::cpp11::to_string(static_cast<std::underlying_type<NormType>::type>(norm_info.type()));
	_config_id += "_";
	_config_id += support::cpp11::to_string(norm_info.norm_size());
	_config_id += "_";
	_config_id += support::cpp11::to_string(input->info()->dimension(0));
	_config_id += "_";
	_config_id += support::cpp11::to_string(input->info()->dimension(1));
	if(data_layout == DataLayout::NHWC)
	{
	ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
	}
	}

	Status CLNormalizationLayerKernel::validate(const ITensorInfo input, const ITensorInfo output, NormalizationLayerInfo norm_info)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, norm_info));
	ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), norm_info).first);

	return Status{};
	}

	void CLNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	const int collapsed_dimension = _is_norm_across_width ? Window::DimZ : 4;
	Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), collapsed_dimension);
	Window slice = window_collapsed.first_slice_window_3D();

	do
	{
	unsigned int idx = 0;
	add_3D_tensor_argument(idx, _input, slice);
	add_3D_tensor_argument(idx, _output, slice);
	enqueue(queue, *this, slice, lws_hint());
	}
	while(window_collapsed.slide_window_slice_3D(slice));
	}
	} // namespace arm_compute