src/core/NEON/kernels/NEBatchToSpaceLayerKernel.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/NEBatchToSpaceLayerKernel.h"

 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/TensorInfo.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"

 using namespace arm_compute::misc::shape_calculator;

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, output);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
     ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);

     // Validate output if initialized
     if (output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
     }

     return Status{};
 }
 Status validate_arguments_static(const ITensorInfo *input,
                                  int                block_shape_x,
                                  int                block_shape_y,
                                  const ITensorInfo *output,
                                  const CropInfo    &crop_info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
     ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x <= 0);
     ARM_COMPUTE_RETURN_ERROR_ON(block_shape_y <= 0);

     const DataLayout data_layout = input->data_layout();
     const int        idx_batch   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
     ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0);
     // Validate output if initialized
     if (output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);

         const TensorShape expected_output_shape = compute_batch_to_space_shape(
             input->data_layout(), input->tensor_shape(), block_shape_x, block_shape_y, crop_info);
         const TensorInfo expected_output = output->clone()->set_tensor_shape(expected_output_shape);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &expected_output);
     }

     return Status{};
 }
 } // namespace

 NEBatchToSpaceLayerKernel::NEBatchToSpaceLayerKernel()
     : _input(nullptr),
       _block_shape(nullptr),
       _output(nullptr),
       _data_layout(DataLayout::UNKNOWN),
       _block_shape_x(),
       _block_shape_y(),
       _crop_info()
 {
 }

 void NEBatchToSpaceLayerKernel::configure(const ITensor *input, const ITensor *block_shape, ITensor *output)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), output->info()));

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

     // Configure kernel window
     Window win = calculate_max_window(*output->info(), Steps());
     ICPPKernel::configure(win);
 }

 void NEBatchToSpaceLayerKernel::configure(
     const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output, const CropInfo &crop_info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     const TensorShape output_shape = compute_batch_to_space_shape(
         input->info()->data_layout(), input->info()->tensor_shape(), block_shape_x, block_shape_y);
     // Output auto initialization 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_static(input->info(), block_shape_x, block_shape_y, output->info(), crop_info));

     _input         = input;
     _output        = output;
     _block_shape_x = block_shape_x;
     _block_shape_y = block_shape_y;
     _data_layout   = input->info()->data_layout();
     _crop_info     = crop_info;

     // Configure kernel window
     Window win = calculate_max_window(*output->info(), Steps());
     ICPPKernel::configure(win);
 }

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

 Status NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input,
                                            int32_t            block_shape_x,
                                            int32_t            block_shape_y,
                                            const ITensorInfo *output,
                                            const CropInfo    &crop_info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output, crop_info));
     return Status{};
 }

 void NEBatchToSpaceLayerKernel::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);

     if (_block_shape != nullptr)
     {
         // Retrieve the block shapes dynamically
         _block_shape_x = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(0)));
         _block_shape_y = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(1)));
     }

     const int batch_size   = _output->info()->dimension(3);
     const int element_size = _output->info()->element_size();

     Window slice_out = window.first_slice_window_3D();

     int batch_id = 0;
     // Main loop for NCHW and NHWC
     if (_data_layout == DataLayout::NCHW)
     {
         do
         {
             Iterator out(_output, slice_out);
             execute_window_loop(
                 slice_out,
                 [&](const Coordinates &id)
                 {
                     const int x = id.x();
                     const int y = id.y();
                     const int z = id.z();
                     // Translate x, y to uncropped version
                     const int x_c = x + _crop_info.left;
                     const int y_c = y + _crop_info.top;

                     const int in_batch =
                         batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size;
                     const int   in_x = x_c / _block_shape_x;
                     const int   in_y = y_c / _block_shape_y;
                     Coordinates input_coords{in_x, in_y, z, in_batch};
                     memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
                 },
                 out);
             ++batch_id;
         } while (window.slide_window_slice_3D(slice_out));
     }
     else
     {
         // For NHWC we can perform a block copy on the Channel (first) dimension. Thus we do not need to iterate over this dimension
         slice_out.set(0U, Window::Dimension(0U, 1U, 1U));
         do
         {
             Iterator out(_output, slice_out);
             execute_window_loop(
                 slice_out,
                 [&](const Coordinates &id)
                 {
                     const int x = id.y();
                     const int y = id.z();

                     // Translate x, y to uncropped version
                     const int x_c = x + _crop_info.left;
                     const int y_c = y + _crop_info.top;

                     const int in_batch =
                         batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size;
                     const int   in_x = x_c / _block_shape_x;
                     const int   in_y = y_c / _block_shape_y;
                     Coordinates input_coords{0, in_x, in_y, in_batch};
                     memcpy(out.ptr(), _input->ptr_to_element(input_coords),
                            element_size * _input->info()->dimension(0));
                 },
                 out);
             ++batch_id;
         } while (window.slide_window_slice_3D(slice_out));
     }
 }
 } // 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/NEBatchToSpaceLayerKernel.h"

	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/ITensor.h"
	#include "arm_compute/core/TensorInfo.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"

	using namespace arm_compute::misc::shape_calculator;

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo block_info, const ITensorInfo *output)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, output);
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32);
	ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);

	// Validate output if initialized
	if (output->total_size() != 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	}

	return Status{};
	}
	Status validate_arguments_static(const ITensorInfo *input,
	int block_shape_x,
	int block_shape_y,
	const ITensorInfo *output,
	const CropInfo &crop_info)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x <= 0);
	ARM_COMPUTE_RETURN_ERROR_ON(block_shape_y <= 0);

	const DataLayout data_layout = input->data_layout();
	const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
	ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0);
	// Validate output if initialized
	if (output->total_size() != 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);

	const TensorShape expected_output_shape = compute_batch_to_space_shape(
	input->data_layout(), input->tensor_shape(), block_shape_x, block_shape_y, crop_info);
	const TensorInfo expected_output = output->clone()->set_tensor_shape(expected_output_shape);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &expected_output);
	}

	return Status{};
	}
	} // namespace

	NEBatchToSpaceLayerKernel::NEBatchToSpaceLayerKernel()
	: _input(nullptr),
	_block_shape(nullptr),
	_output(nullptr),
	_data_layout(DataLayout::UNKNOWN),
	_block_shape_x(),
	_block_shape_y(),
	_crop_info()
	{
	}

	void NEBatchToSpaceLayerKernel::configure(const ITensor input, const ITensor block_shape, ITensor *output)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), output->info()));

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

	// Configure kernel window
	Window win = calculate_max_window(*output->info(), Steps());
	ICPPKernel::configure(win);
	}

	void NEBatchToSpaceLayerKernel::configure(
	const ITensor input, int32_t block_shape_x, int32_t block_shape_y, ITensor output, const CropInfo &crop_info)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
	const TensorShape output_shape = compute_batch_to_space_shape(
	input->info()->data_layout(), input->info()->tensor_shape(), block_shape_x, block_shape_y);
	// Output auto initialization 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_static(input->info(), block_shape_x, block_shape_y, output->info(), crop_info));

	_input = input;
	_output = output;
	_block_shape_x = block_shape_x;
	_block_shape_y = block_shape_y;
	_data_layout = input->info()->data_layout();
	_crop_info = crop_info;

	// Configure kernel window
	Window win = calculate_max_window(*output->info(), Steps());
	ICPPKernel::configure(win);
	}

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

	Status NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input,
	int32_t block_shape_x,
	int32_t block_shape_y,
	const ITensorInfo *output,
	const CropInfo &crop_info)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output, crop_info));
	return Status{};
	}

	void NEBatchToSpaceLayerKernel::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);

	if (_block_shape != nullptr)
	{
	// Retrieve the block shapes dynamically
	_block_shape_x = (reinterpret_cast<const int >(_block_shape->ptr_to_element(0)));
	_block_shape_y = (reinterpret_cast<const int >(_block_shape->ptr_to_element(1)));
	}

	const int batch_size = _output->info()->dimension(3);
	const int element_size = _output->info()->element_size();

	Window slice_out = window.first_slice_window_3D();

	int batch_id = 0;
	// Main loop for NCHW and NHWC
	if (_data_layout == DataLayout::NCHW)
	{
	do
	{
	Iterator out(_output, slice_out);
	execute_window_loop(
	slice_out,
	[&](const Coordinates &id)
	{
	const int x = id.x();
	const int y = id.y();
	const int z = id.z();
	// Translate x, y to uncropped version
	const int x_c = x + _crop_info.left;
	const int y_c = y + _crop_info.top;

	const int in_batch =
	batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size;
	const int in_x = x_c / _block_shape_x;
	const int in_y = y_c / _block_shape_y;
	Coordinates input_coords{in_x, in_y, z, in_batch};
	memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
	},
	out);
	++batch_id;
	} while (window.slide_window_slice_3D(slice_out));
	}
	else
	{
	// For NHWC we can perform a block copy on the Channel (first) dimension. Thus we do not need to iterate over this dimension
	slice_out.set(0U, Window::Dimension(0U, 1U, 1U));
	do
	{
	Iterator out(_output, slice_out);
	execute_window_loop(
	slice_out,
	[&](const Coordinates &id)
	{
	const int x = id.y();
	const int y = id.z();

	// Translate x, y to uncropped version
	const int x_c = x + _crop_info.left;
	const int y_c = y + _crop_info.top;

	const int in_batch =
	batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size;
	const int in_x = x_c / _block_shape_x;
	const int in_y = y_c / _block_shape_y;
	Coordinates input_coords{0, in_x, in_y, in_batch};
	memcpy(out.ptr(), _input->ptr_to_element(input_coords),
	element_size * _input->info()->dimension(0));
	},
	out);
	++batch_id;
	} while (window.slide_window_slice_3D(slice_out));
	}
	}
	} // namespace arm_compute