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

 /*
  * Copyright (c) 2019-2020, 2023 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/NEON/kernels/NEDepthToSpaceLayerKernel.h"

 #include "arm_compute/core/CoreTypes.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "arm_compute/core/Validate.h"

 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "src/cpu/kernels/depth_to_space/list.h"

 #include <cstdint>

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
     ARM_COMPUTE_RETURN_ERROR_ON(block_shape < 2);

     const DataLayout data_layout = input->data_layout();
     const int        idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
     ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] % (block_shape * block_shape) != 0);
     // Validate output if initialized
     if (output->total_size() != 0)
     {
         const int idx_width  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
         const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
         ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] !=
                                     (block_shape * input->tensor_shape()[idx_width]));
         ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_height] !=
                                     (block_shape * input->tensor_shape()[idx_height]));
         ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
     }

     return Status{};
 }
 } // namespace

 NEDepthToSpaceLayerKernel::NEDepthToSpaceLayerKernel()
     : _input(nullptr),
       _output(nullptr),
       _block_shape(),
       _data_layout(DataLayout::UNKNOWN),
       _split_dimension(Window::DimY)
 {
 }

 void NEDepthToSpaceLayerKernel::configure(const ITensor *input, ITensor *output, int32_t block_shape)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     TensorShape output_shape = misc::shape_calculator::compute_depth_to_space_shape(
         input->info()->tensor_shape(), input->info()->data_layout(), block_shape);
     // Output auto inizialitation if not yet initialized
     auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));

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

     _input       = input;
     _output      = output;
     _block_shape = block_shape;
     _data_layout = input->info()->data_layout();

     constexpr size_t dim_b = 3;
     const auto       dim_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
     const auto       dim_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
     const auto       dim_c = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);

     ARM_COMPUTE_ERROR_ON(get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES) != dim_b);

     // Configure kernel window
     Steps steps;
     steps.set(dim_h, block_shape);
     steps.set(dim_w, block_shape);
     steps.set(dim_c, output->info()->dimension(dim_c));

     Window win = calculate_max_window(*output->info(), steps);
     ICPPKernel::configure(win);

     const auto num_batches = input->info()->tensor_shape().total_size_upper(dim_b);
     if (num_batches > 1)
     {
         _split_dimension = dim_b;
     }
     else
     {
         _split_dimension = dim_h;
     }
 }

 Status NEDepthToSpaceLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, block_shape));
     return Status{};
 }

 size_t NEDepthToSpaceLayerKernel::get_split_dimension() const
 {
     return _split_dimension;
 }

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

     const auto *input_info  = _input->info();
     const auto *output_info = _output->info();

     const auto  element_size   = input_info->element_size();
     const auto &input_strides  = input_info->strides_in_bytes();
     const auto &output_strides = output_info->strides_in_bytes();

     const auto &input_shape = input_info->tensor_shape();

     const uintptr_t k_input_strides[]  = {input_strides[0], input_strides[1], input_strides[2], input_strides[3]};
     const uintptr_t k_output_strides[] = {output_strides[0], output_strides[1], output_strides[2], output_strides[3]};

     const uint8_t *k_input_ptr  = _input->buffer();
     uint8_t       *k_output_ptr =               //
         _output->buffer() +                     //
         window[3].start() * output_strides[3] + //
         window[2].start() * output_strides[2] + //
         window[1].start() * output_strides[1] + //
         window[0].start() * output_strides[0];

     if (_data_layout == DataLayout::NCHW)
     {
         ARM_COMPUTE_ERROR_ON_MSG(window[2].start() != 0 || window[2].end() != window[2].step(),
                                  "The window cannot be splitted in channel dimension");

         const uintptr_t k_input_shape[] = {
             window.num_iterations(0), //
             window.num_iterations(1), //
             input_shape[2],           // The window cannot be splitted in channel dimension.
             window.num_iterations(3)  //
         };

         k_input_ptr += window[3].start() * input_strides[3] +                               //
                        window[2].start() * _block_shape * _block_shape * input_strides[2] + //
                        (window[1].start() / _block_shape) * input_strides[1] +              //
                        (window[0].start() / _block_shape) * input_strides[0];

         cpu::depth_to_space_nchw_any(                         //
             k_input_ptr, k_output_ptr,                        //
             k_input_shape, k_input_strides, k_output_strides, //
             element_size, _block_shape);
     }
     else
     {
         ARM_COMPUTE_ERROR_ON_MSG(window[0].start() != 0 || window[0].end() != window[0].step(),
                                  "The window cannot be splitted in channel dimension");

         const uintptr_t k_input_shape[] = {
             input_shape[0],           // The window cannot be splitted in channel dimension.
             window.num_iterations(1), //
             window.num_iterations(2), //
             window.num_iterations(3)  //
         };

         k_input_ptr += window[3].start() * input_strides[3] +                  //
                        (window[2].start() / _block_shape) * input_strides[2] + //
                        (window[1].start() / _block_shape) * input_strides[1] + //
                        window[0].start() * _block_shape * _block_shape * input_strides[0];

         cpu::depth_to_space_nhwc_any(                         //
             k_input_ptr, k_output_ptr,                        //
             k_input_shape, k_input_strides, k_output_strides, //
             element_size, _block_shape);
     }
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2019-2020, 2023 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/NEON/kernels/NEDepthToSpaceLayerKernel.h"

	#include "arm_compute/core/CoreTypes.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/ITensor.h"
	#include "arm_compute/core/Types.h"
	#include "arm_compute/core/utils/misc/ShapeCalculator.h"
	#include "arm_compute/core/Validate.h"

	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"
	#include "src/cpu/kernels/depth_to_space/list.h"

	#include <cstdint>

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo output, int32_t block_shape)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
	ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON(block_shape < 2);

	const DataLayout data_layout = input->data_layout();
	const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
	ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] % (block_shape * block_shape) != 0);
	// Validate output if initialized
	if (output->total_size() != 0)
	{
	const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
	ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] !=
	(block_shape * input->tensor_shape()[idx_width]));
	ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_height] !=
	(block_shape * input->tensor_shape()[idx_height]));
	ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	}

	return Status{};
	}
	} // namespace

	NEDepthToSpaceLayerKernel::NEDepthToSpaceLayerKernel()
	: _input(nullptr),
	_output(nullptr),
	_block_shape(),
	_data_layout(DataLayout::UNKNOWN),
	_split_dimension(Window::DimY)
	{
	}

	void NEDepthToSpaceLayerKernel::configure(const ITensor input, ITensor output, int32_t block_shape)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
	TensorShape output_shape = misc::shape_calculator::compute_depth_to_space_shape(
	input->info()->tensor_shape(), input->info()->data_layout(), block_shape);
	// Output auto inizialitation if not yet initialized
	auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));

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

	_input = input;
	_output = output;
	_block_shape = block_shape;
	_data_layout = input->info()->data_layout();

	constexpr size_t dim_b = 3;
	const auto dim_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
	const auto dim_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
	const auto dim_c = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);

	ARM_COMPUTE_ERROR_ON(get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES) != dim_b);

	// Configure kernel window
	Steps steps;
	steps.set(dim_h, block_shape);
	steps.set(dim_w, block_shape);
	steps.set(dim_c, output->info()->dimension(dim_c));

	Window win = calculate_max_window(*output->info(), steps);
	ICPPKernel::configure(win);

	const auto num_batches = input->info()->tensor_shape().total_size_upper(dim_b);
	if (num_batches > 1)
	{
	_split_dimension = dim_b;
	}
	else
	{
	_split_dimension = dim_h;
	}
	}

	Status NEDepthToSpaceLayerKernel::validate(const ITensorInfo input, const ITensorInfo output, int32_t block_shape)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, block_shape));
	return Status{};
	}

	size_t NEDepthToSpaceLayerKernel::get_split_dimension() const
	{
	return _split_dimension;
	}

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

	const auto *input_info = _input->info();
	const auto *output_info = _output->info();

	const auto element_size = input_info->element_size();
	const auto &input_strides = input_info->strides_in_bytes();
	const auto &output_strides = output_info->strides_in_bytes();

	const auto &input_shape = input_info->tensor_shape();

	const uintptr_t k_input_strides[] = {input_strides[0], input_strides[1], input_strides[2], input_strides[3]};
	const uintptr_t k_output_strides[] = {output_strides[0], output_strides[1], output_strides[2], output_strides[3]};

	const uint8_t *k_input_ptr = _input->buffer();
	uint8_t *k_output_ptr = //
	_output->buffer() + //
	window[3].start() * output_strides[3] + //
	window[2].start() * output_strides[2] + //
	window[1].start() * output_strides[1] + //
	window[0].start() * output_strides[0];

	if (_data_layout == DataLayout::NCHW)
	{
	ARM_COMPUTE_ERROR_ON_MSG(window[2].start() != 0 \|\| window[2].end() != window[2].step(),
	"The window cannot be splitted in channel dimension");

	const uintptr_t k_input_shape[] = {
	window.num_iterations(0), //
	window.num_iterations(1), //
	input_shape[2], // The window cannot be splitted in channel dimension.
	window.num_iterations(3) //
	};

	k_input_ptr += window[3].start() * input_strides[3] + //
	window[2].start() * _block_shape * _block_shape * input_strides[2] + //
	(window[1].start() / _block_shape) * input_strides[1] + //
	(window[0].start() / _block_shape) * input_strides[0];

	cpu::depth_to_space_nchw_any( //
	k_input_ptr, k_output_ptr, //
	k_input_shape, k_input_strides, k_output_strides, //
	element_size, _block_shape);
	}
	else
	{
	ARM_COMPUTE_ERROR_ON_MSG(window[0].start() != 0 \|\| window[0].end() != window[0].step(),
	"The window cannot be splitted in channel dimension");

	const uintptr_t k_input_shape[] = {
	input_shape[0], // The window cannot be splitted in channel dimension.
	window.num_iterations(1), //
	window.num_iterations(2), //
	window.num_iterations(3) //
	};

	k_input_ptr += window[3].start() * input_strides[3] + //
	(window[2].start() / _block_shape) * input_strides[2] + //
	(window[1].start() / _block_shape) * input_strides[1] + //
	window[0].start() * _block_shape * _block_shape * input_strides[0];

	cpu::depth_to_space_nhwc_any( //
	k_input_ptr, k_output_ptr, //
	k_input_shape, k_input_strides, k_output_strides, //
	element_size, _block_shape);
	}
	}
	} // namespace arm_compute