src/core/GLES_COMPUTE/kernels/GCIm2ColKernel.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/GCIm2ColKernel.h"

 #include "arm_compute/core/Error.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/Size2D.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/Validate.h"
 #include "src/core/AccessWindowStatic.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "support/StringSupport.h"

 #include <cmath>
 #include <tuple>

 using namespace arm_compute;

 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);

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

     return Status{};
 }
 } // namespace

 GCIm2ColKernel::GCIm2ColKernel()
     : _input(nullptr), _output(nullptr), _convolved_dims(), _kernel_dims(), _num_elems_processed_per_iteration(1), _run_func(nullptr)
 {
 }

 void GCIm2ColKernel::configure(const IGCTensor *input, IGCTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

     // Perform validation step
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));

     _input  = input;
     _output = output;

     // Create kernel
     std::set<std::string> build_opts;
     std::string           dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
     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 " + dt_name);

     if(has_bias)
     {
         build_opts.emplace("#define HAS_BIAS");
     }

     int stride_x = 0;
     int stride_y = 0;

     std::tie(stride_x, stride_y) = conv_info.stride();
     _kernel_dims = std::make_pair(kernel_dims.width, kernel_dims.height);

     const bool run_img2col_reduced = (output->info()->dimension(0) == (input->info()->dimension(0) * input->info()->dimension(1) * input->info()->dimension(2))) && (TensorShape::num_max_dimensions >= 4)
                                      && (std::equal(input->info()->tensor_shape().cbegin() + 3,
                                                     input->info()->tensor_shape().cend(),
                                                     output->info()->tensor_shape().cbegin() + 1))
                                      && ((stride_x == 1) && (stride_y == 1) && !conv_info.has_padding())
                                      && (dilation == Size2D(1U, 1U));

     std::string kernel_name = "im2col_generic";
     if(!run_img2col_reduced)
     {
         if(input->info()->data_type() == DataType::F16 && _kernel_dims == std::pair<unsigned int, unsigned int>(1, 1))
         {
             build_opts.emplace("#define KERNEL_1x1");
         }

         build_opts.emplace("#define IM2COL_GENERIC");
         _convolved_dims = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1),
                                             kernel_dims.width, kernel_dims.height,
                                             conv_info, dilation);
         _num_elems_processed_per_iteration = (input->info()->data_type() == DataType::F32) ? 1 : 2;

         build_opts.emplace("#define KERNEL_WIDTH " + support::cpp11::to_string(kernel_dims.width));
         build_opts.emplace("#define KERNEL_HEIGHT " + support::cpp11::to_string(kernel_dims.height));
         build_opts.emplace("#define KERNEL_DEPTH " + support::cpp11::to_string(input->info()->dimension(2)));
         build_opts.emplace("#define CONVOLVED_WIDTH " + support::cpp11::to_string(_convolved_dims.first));
         build_opts.emplace("#define CONVOLVED_HEIGHT " + support::cpp11::to_string(_convolved_dims.second));
         build_opts.emplace("#define STRIDE_X " + support::cpp11::to_string(conv_info.stride().first));
         build_opts.emplace("#define STRIDE_Y " + support::cpp11::to_string(conv_info.stride().second));
         build_opts.emplace("#define PAD_LEFT " + support::cpp11::to_string(conv_info.pad_left()));
         build_opts.emplace("#define PAD_TOP " + support::cpp11::to_string(conv_info.pad_top()));
         build_opts.emplace("#define PAD_RIGHT " + support::cpp11::to_string(conv_info.pad_right()));
         build_opts.emplace("#define PAD_BOTTOM " + support::cpp11::to_string(conv_info.pad_bottom()));
         build_opts.emplace("#define SRC_WIDTH " + support::cpp11::to_string(input->info()->dimension(0)));
         build_opts.emplace("#define SRC_HEIGHT " + support::cpp11::to_string(input->info()->dimension(1)));
         build_opts.emplace("#define DILATION_X " + support::cpp11::to_string(dilation.x()));
         build_opts.emplace("#define DILATION_Y " + support::cpp11::to_string(dilation.y()));

         _run_func = &GCIm2ColKernel::run_generic;
     }
     else
     {
         build_opts.emplace("#define IM2COL_REDUCED");
         kernel_name = "im2col_reduced";

         if(input->info()->data_type() == DataType::F32)
         {
             _num_elems_processed_per_iteration = 4 / input->info()->element_size();
         }
         else if(input->info()->data_type() == DataType::F16)
         {
             int input_width  = input->info()->dimension(0);
             int input_height = input->info()->dimension(1);

             build_opts.emplace("#define IMAGE_SIZE " + support::cpp11::to_string(input_width * input_height));
             if(input_width % 8 == 0)
             {
                 _num_elems_processed_per_iteration = 8;
                 build_opts.emplace("#define IM2COL_REDUCED_8X");
             }
             else if(input_width % 4 == 0)
             {
                 _num_elems_processed_per_iteration = 4;
                 build_opts.emplace("#define IM2COL_REDUCED_4X");
             }
             else if(input_width % 2 == 0)
             {
                 _num_elems_processed_per_iteration = 2;
                 build_opts.emplace("#define IM2COL_REDUCED_2X");
             }
             else
             {
                 _num_elems_processed_per_iteration = 2;
                 build_opts.emplace("#define IM2COL_REDUCED_GENERIC");
             }
         }

         _run_func = &GCIm2ColKernel::run_reduced;
     }

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

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

     if(input->info()->data_type() == DataType::F16)
     {
         // Calculate input right and bottom border
         const int input_width         = input->info()->dimension(0);
         const int input_height        = input->info()->dimension(1);
         int       input_total_width   = input->info()->padding().left + input_width + input->info()->padding().right;
         int       input_padding_right = ceil_to_multiple(input_total_width, _num_elems_processed_per_iteration) - input_total_width;
         input_total_width             = input_width + input_padding_right + input->info()->padding().right;
         AccessWindowStatic input_access(input->info(), 0, 0, input_total_width, input_height);

         // Calculate output right and bottom border
         const int          output_width         = output->info()->dimension(0);
         const int          output_height        = output->info()->dimension(1);
         const int          output_padding_right = ceil_to_multiple(output_width, _num_elems_processed_per_iteration) - output_width;
         AccessWindowStatic output_access(output->info(), 0, 0, output_width + output_padding_right, output_height);

         update_window_and_padding(win, input_access, output_access);
     }

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

     if(!run_img2col_reduced)
     {
         // set the Z dimension's step same size as the whole dimension so that one can't split across the Z dimension
         win.set_dimension_step(Window::DimZ, win[Window::DimZ].end() - win[Window::DimZ].start());
     }

     IGCKernel::configure(win);
 }

 Status GCIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation)
 {
     ARM_COMPUTE_UNUSED(kernel_dims);
     ARM_COMPUTE_UNUSED(conv_info);
     ARM_COMPUTE_UNUSED(has_bias);
     ARM_COMPUTE_UNUSED(dilation);
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
     return Status{};
 }

 void GCIm2ColKernel::run(const Window &window)
 {
     ARM_COMPUTE_ERROR_ON(_run_func == nullptr);
     (this->*_run_func)(window);
 }

 void GCIm2ColKernel::run_generic(const Window &window)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);

     // Get initial windows
     Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);

     // Change the Z dimension's step back to 1
     window_collapsed.set_dimension_step(Window::DimZ, 1);

     Window slice     = window_collapsed.first_slice_window_3D();
     Window slice_in  = window_collapsed.first_slice_window_3D();
     Window slice_out = window_collapsed.first_slice_window_3D();

     // Setup slice
     slice.set(Window::DimX, Window::Dimension(0, static_cast<int>(_convolved_dims.first), 1));
     slice.set(Window::DimY, Window::Dimension(0, static_cast<int>(_convolved_dims.second), 1));

     // Setup output slice
     slice_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _num_elems_processed_per_iteration));
     slice_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 1));
     slice_out.set(Window::DimZ, Window::Dimension(0, 1, 1));

     // we need top/left pad to be included in valid region
     if(_input->info()->data_type() == DataType::F16)
     {
         (dynamic_cast<TensorInfo *>(_input->info()))->init(_input->info()->tensor_shape(), _input->info()->num_channels(), _input->info()->data_type(), _input->info()->strides_in_bytes(), 0,
                                                            _input->info()->total_size());
     }

     _kernel.use();

     do
     {
         unsigned int idx = 0;
         add_3D_tensor_argument(idx, _input, 1, slice_in);
         add_2D_tensor_argument(idx, _output, 2, slice_out);
         _kernel.set_argument(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
         _kernel.set_argument(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));
         _kernel.update_shader_params();

         enqueue(*this, slice);
     }
     while(window_collapsed.slide_window_slice_3D(slice) && window_collapsed.slide_window_slice_3D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
 }

 void GCIm2ColKernel::run_reduced(const Window &window)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);

     Window out_window;
     out_window.use_tensor_dimensions(_output->info()->tensor_shape());

     Window out_slice = out_window.first_slice_window_1D();
     Window in_slice  = window.first_slice_window_3D();

     _kernel.use();

     // Run kernel
     do
     {
         // Set arguments
         unsigned int idx = 0;

         add_3D_tensor_argument(idx, _input, 1, in_slice);
         add_1D_tensor_argument(idx, _output, 2, out_slice);
         _kernel.set_argument(idx++, _input->info()->dimension(0));
         _kernel.set_argument(idx++, _input->info()->dimension(1));
         _kernel.update_shader_params();

         enqueue(*this, in_slice);
     }
     while(window.slide_window_slice_3D(in_slice) && out_window.slide_window_slice_1D(out_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/GCIm2ColKernel.h"

	#include "arm_compute/core/Error.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/Size2D.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/Types.h"
	#include "arm_compute/core/Validate.h"
	#include "src/core/AccessWindowStatic.h"
	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"
	#include "support/StringSupport.h"

	#include <cmath>
	#include <tuple>

	using namespace arm_compute;

	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo output)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);

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

	return Status{};
	}
	} // namespace

	GCIm2ColKernel::GCIm2ColKernel()
	: _input(nullptr), _output(nullptr), _convolved_dims(), _kernel_dims(), _num_elems_processed_per_iteration(1), _run_func(nullptr)
	{
	}

	void GCIm2ColKernel::configure(const IGCTensor input, IGCTensor output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

	// Perform validation step
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));

	_input = input;
	_output = output;

	// Create kernel
	std::set<std::string> build_opts;
	std::string dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
	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 " + dt_name);

	if(has_bias)
	{
	build_opts.emplace("#define HAS_BIAS");
	}

	int stride_x = 0;
	int stride_y = 0;

	std::tie(stride_x, stride_y) = conv_info.stride();
	_kernel_dims = std::make_pair(kernel_dims.width, kernel_dims.height);

	const bool run_img2col_reduced = (output->info()->dimension(0) == (input->info()->dimension(0) * input->info()->dimension(1) * input->info()->dimension(2))) && (TensorShape::num_max_dimensions >= 4)
	&& (std::equal(input->info()->tensor_shape().cbegin() + 3,
	input->info()->tensor_shape().cend(),
	output->info()->tensor_shape().cbegin() + 1))
	&& ((stride_x == 1) && (stride_y == 1) && !conv_info.has_padding())
	&& (dilation == Size2D(1U, 1U));

	std::string kernel_name = "im2col_generic";
	if(!run_img2col_reduced)
	{
	if(input->info()->data_type() == DataType::F16 && _kernel_dims == std::pair<unsigned int, unsigned int>(1, 1))
	{
	build_opts.emplace("#define KERNEL_1x1");
	}

	build_opts.emplace("#define IM2COL_GENERIC");
	_convolved_dims = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1),
	kernel_dims.width, kernel_dims.height,
	conv_info, dilation);
	_num_elems_processed_per_iteration = (input->info()->data_type() == DataType::F32) ? 1 : 2;

	build_opts.emplace("#define KERNEL_WIDTH " + support::cpp11::to_string(kernel_dims.width));
	build_opts.emplace("#define KERNEL_HEIGHT " + support::cpp11::to_string(kernel_dims.height));
	build_opts.emplace("#define KERNEL_DEPTH " + support::cpp11::to_string(input->info()->dimension(2)));
	build_opts.emplace("#define CONVOLVED_WIDTH " + support::cpp11::to_string(_convolved_dims.first));
	build_opts.emplace("#define CONVOLVED_HEIGHT " + support::cpp11::to_string(_convolved_dims.second));
	build_opts.emplace("#define STRIDE_X " + support::cpp11::to_string(conv_info.stride().first));
	build_opts.emplace("#define STRIDE_Y " + support::cpp11::to_string(conv_info.stride().second));
	build_opts.emplace("#define PAD_LEFT " + support::cpp11::to_string(conv_info.pad_left()));
	build_opts.emplace("#define PAD_TOP " + support::cpp11::to_string(conv_info.pad_top()));
	build_opts.emplace("#define PAD_RIGHT " + support::cpp11::to_string(conv_info.pad_right()));
	build_opts.emplace("#define PAD_BOTTOM " + support::cpp11::to_string(conv_info.pad_bottom()));
	build_opts.emplace("#define SRC_WIDTH " + support::cpp11::to_string(input->info()->dimension(0)));
	build_opts.emplace("#define SRC_HEIGHT " + support::cpp11::to_string(input->info()->dimension(1)));
	build_opts.emplace("#define DILATION_X " + support::cpp11::to_string(dilation.x()));
	build_opts.emplace("#define DILATION_Y " + support::cpp11::to_string(dilation.y()));

	_run_func = &GCIm2ColKernel::run_generic;
	}
	else
	{
	build_opts.emplace("#define IM2COL_REDUCED");
	kernel_name = "im2col_reduced";

	if(input->info()->data_type() == DataType::F32)
	{
	_num_elems_processed_per_iteration = 4 / input->info()->element_size();
	}
	else if(input->info()->data_type() == DataType::F16)
	{
	int input_width = input->info()->dimension(0);
	int input_height = input->info()->dimension(1);

	build_opts.emplace("#define IMAGE_SIZE " + support::cpp11::to_string(input_width * input_height));
	if(input_width % 8 == 0)
	{
	_num_elems_processed_per_iteration = 8;
	build_opts.emplace("#define IM2COL_REDUCED_8X");
	}
	else if(input_width % 4 == 0)
	{
	_num_elems_processed_per_iteration = 4;
	build_opts.emplace("#define IM2COL_REDUCED_4X");
	}
	else if(input_width % 2 == 0)
	{
	_num_elems_processed_per_iteration = 2;
	build_opts.emplace("#define IM2COL_REDUCED_2X");
	}
	else
	{
	_num_elems_processed_per_iteration = 2;
	build_opts.emplace("#define IM2COL_REDUCED_GENERIC");
	}
	}

	_run_func = &GCIm2ColKernel::run_reduced;
	}

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

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

	if(input->info()->data_type() == DataType::F16)
	{
	// Calculate input right and bottom border
	const int input_width = input->info()->dimension(0);
	const int input_height = input->info()->dimension(1);
	int input_total_width = input->info()->padding().left + input_width + input->info()->padding().right;
	int input_padding_right = ceil_to_multiple(input_total_width, _num_elems_processed_per_iteration) - input_total_width;
	input_total_width = input_width + input_padding_right + input->info()->padding().right;
	AccessWindowStatic input_access(input->info(), 0, 0, input_total_width, input_height);

	// Calculate output right and bottom border
	const int output_width = output->info()->dimension(0);
	const int output_height = output->info()->dimension(1);
	const int output_padding_right = ceil_to_multiple(output_width, _num_elems_processed_per_iteration) - output_width;
	AccessWindowStatic output_access(output->info(), 0, 0, output_width + output_padding_right, output_height);

	update_window_and_padding(win, input_access, output_access);
	}

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

	if(!run_img2col_reduced)
	{
	// set the Z dimension's step same size as the whole dimension so that one can't split across the Z dimension
	win.set_dimension_step(Window::DimZ, win[Window::DimZ].end() - win[Window::DimZ].start());
	}

	IGCKernel::configure(win);
	}

	Status GCIm2ColKernel::validate(const ITensorInfo input, const ITensorInfo output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation)
	{
	ARM_COMPUTE_UNUSED(kernel_dims);
	ARM_COMPUTE_UNUSED(conv_info);
	ARM_COMPUTE_UNUSED(has_bias);
	ARM_COMPUTE_UNUSED(dilation);
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
	return Status{};
	}

	void GCIm2ColKernel::run(const Window &window)
	{
	ARM_COMPUTE_ERROR_ON(_run_func == nullptr);
	(this->*_run_func)(window);
	}

	void GCIm2ColKernel::run_generic(const Window &window)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);

	// Get initial windows
	Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);

	// Change the Z dimension's step back to 1
	window_collapsed.set_dimension_step(Window::DimZ, 1);

	Window slice = window_collapsed.first_slice_window_3D();
	Window slice_in = window_collapsed.first_slice_window_3D();
	Window slice_out = window_collapsed.first_slice_window_3D();

	// Setup slice
	slice.set(Window::DimX, Window::Dimension(0, static_cast<int>(_convolved_dims.first), 1));
	slice.set(Window::DimY, Window::Dimension(0, static_cast<int>(_convolved_dims.second), 1));

	// Setup output slice
	slice_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _num_elems_processed_per_iteration));
	slice_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 1));
	slice_out.set(Window::DimZ, Window::Dimension(0, 1, 1));

	// we need top/left pad to be included in valid region
	if(_input->info()->data_type() == DataType::F16)
	{
	(dynamic_cast<TensorInfo *>(_input->info()))->init(_input->info()->tensor_shape(), _input->info()->num_channels(), _input->info()->data_type(), _input->info()->strides_in_bytes(), 0,
	_input->info()->total_size());
	}

	_kernel.use();

	do
	{
	unsigned int idx = 0;
	add_3D_tensor_argument(idx, _input, 1, slice_in);
	add_2D_tensor_argument(idx, _output, 2, slice_out);
	_kernel.set_argument(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
	_kernel.set_argument(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));
	_kernel.update_shader_params();

	enqueue(*this, slice);
	}
	while(window_collapsed.slide_window_slice_3D(slice) && window_collapsed.slide_window_slice_3D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
	}

	void GCIm2ColKernel::run_reduced(const Window &window)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);

	Window out_window;
	out_window.use_tensor_dimensions(_output->info()->tensor_shape());

	Window out_slice = out_window.first_slice_window_1D();
	Window in_slice = window.first_slice_window_3D();

	_kernel.use();

	// Run kernel
	do
	{
	// Set arguments
	unsigned int idx = 0;

	add_3D_tensor_argument(idx, _input, 1, in_slice);
	add_1D_tensor_argument(idx, _output, 2, out_slice);
	_kernel.set_argument(idx++, _input->info()->dimension(0));
	_kernel.set_argument(idx++, _input->info()->dimension(1));
	_kernel.update_shader_params();

	enqueue(*this, in_slice);
	}
	while(window.slide_window_slice_3D(in_slice) && out_window.slide_window_slice_1D(out_slice));
	}