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

 /*
  * Copyright (c) 2019-2023 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/NEGatherKernel.h"

 #include "arm_compute/core/Coordinates.h"
 #include "arm_compute/core/Error.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/Window.h"

 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *indices, const ITensorInfo *output, int axis)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, indices, output);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);

     if (axis < 0)
     {
         axis += input->num_dimensions();
     }

     ARM_COMPUTE_RETURN_ERROR_ON(0 > axis || axis >= static_cast<int32_t>(input->num_dimensions()));
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() + indices->num_dimensions() - 1 >
                                 Coordinates::num_max_dimensions);
     ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);

     if (output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
         TensorShape output_shape = arm_compute::misc::shape_calculator::compute_gather_shape(
             input->tensor_shape(), indices->tensor_shape(), axis);
         ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() != output->tensor_shape().total_size());
     }

     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::U32, DataType::S32);

     return Status{};
 }
 } // namespace

 NEGatherKernel::NEGatherKernel()
     : _input{}, _indices{}, _axis{}, _output{}, _func{}, _src_it_strides{}, _idx_it_strides{}
 {
 }

 template <typename TIndex>
 void NEGatherKernel::gather_common(const Window &window, const ThreadInfo &info)
 {
     ARM_COMPUTE_UNUSED(info);

     auto dst_win = window;

     const auto src_info = _input->info();
     const auto idx_info = _indices->info();
     const auto dst_info = _output->info();

     const auto num_dims     = dst_info->num_dimensions();
     const auto chunk_stride = src_info->strides_in_bytes()[_axis];

     const auto window_start_x = window.x().start();
     const auto window_end_x   = window.x().end();
     auto       window_size_x  = src_info->element_size();

     const auto idx_limit = static_cast<TIndex>(src_info->tensor_shape()[_axis]);

     if (_axis != 0)
     {
         dst_win.set(0, Window::Dimension(window_start_x, window_start_x + 1, 1));
         window_size_x *= window_end_x - window_start_x;
     }

     // Compute source and index tensors window based on the output window.
     auto   src_win = dst_win;
     Window idx_win;

     for (size_t i = 0; i < idx_info->num_dimensions(); ++i)
     {
         src_win.set(_axis + i, Window::Dimension(0, 1, 1));
         idx_win.set(_axis + i, window[_axis + i]);
     }

     // Use the custom strides to access all three tensors using the same loop.
     Iterator src_it(num_dims, _src_it_strides, _input->buffer(), src_info->offset_first_element_in_bytes(), src_win);
     Iterator idx_it(num_dims, _idx_it_strides, _indices->buffer(), idx_info->offset_first_element_in_bytes(), idx_win);
     Iterator dst_it(num_dims, dst_info->strides_in_bytes(), _output->buffer(),
                     dst_info->offset_first_element_in_bytes(), dst_win);

     execute_window_loop(
         dst_win,
         [&](const Coordinates &)
         {
             const auto idx = *reinterpret_cast<const TIndex *>(idx_it.ptr());

             if (idx >= 0 && idx < idx_limit)
             {
                 const auto src_ptr = src_it.ptr() + idx * chunk_stride;

                 std::copy_n(src_ptr, window_size_x, dst_it.ptr());
             }
             else
             {
                 std::fill_n(dst_it.ptr(), window_size_x, 0);
             }
         },
         src_it, idx_it, dst_it);
 }

 void NEGatherKernel::configure(const ITensor *input, const ITensor *indices, ITensor *output, int axis)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, indices);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), indices->info(), output->info(), axis));

     _input   = input;
     _indices = indices;
     _output  = output;
     _axis    = axis;

     if (_axis < 0)
     {
         _axis += input->info()->num_dimensions();
     }
     ARM_COMPUTE_ERROR_ON(0 > _axis || _axis >= static_cast<int32_t>(input->info()->num_dimensions()));

     switch (_indices->info()->data_type())
     {
         case DataType::U32:
             _func = &NEGatherKernel::gather_common<uint32_t>;
             break;
         case DataType::S32:
             _func = &NEGatherKernel::gather_common<int32_t>;
             break;
         default:
             ARM_COMPUTE_ERROR("Not supported");
             break;
     }

     // Output auto initialization if not yet initialized
     const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_gather_shape(
         input->info()->tensor_shape(), indices->info()->tensor_shape(), _axis);
     auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));

     // Create window
     Window win = calculate_max_window(*output->info(), Steps());

     INEKernel::configure(win);

     // Create input and indices strides that have the same number of dimensions as the output tensor.
     // These will be used to iterate lock-step through all tensors (input, indices and output).
     size_t dim_no = 0;

     const auto  input_info    = input->info();
     const auto &input_strides = input_info->strides_in_bytes();

     const auto  indices_info     = indices->info();
     const auto &indices_strides  = indices_info->strides_in_bytes();
     const auto  indices_num_dims = indices_info->num_dimensions();

     for (; dim_no < static_cast<size_t>(_axis); ++dim_no)
     {
         _src_it_strides[dim_no] = input_strides[dim_no];
     }

     for (; dim_no < static_cast<size_t>(_axis) + indices_num_dims; ++dim_no)
     {
         _idx_it_strides[dim_no] = indices_strides[dim_no - _axis];
     }

     for (; dim_no < Coordinates::num_max_dimensions; ++dim_no)
     {
         _src_it_strides[dim_no] = input_strides[dim_no - indices_num_dims + 1];
     }
 }

 Status
 NEGatherKernel::validate(const ITensorInfo *input, const ITensorInfo *indices, const ITensorInfo *output, int axis)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, indices, output, axis));
     return Status{};
 }

 void NEGatherKernel::run(const Window &window, const ThreadInfo &info)
 {
     ARM_COMPUTE_UNUSED(info);
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON(_func == nullptr);

     (this->*_func)(window, info);
 }

 } // namespace arm_compute
	/*
	* Copyright (c) 2019-2023 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/NEGatherKernel.h"

	#include "arm_compute/core/Coordinates.h"
	#include "arm_compute/core/Error.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/utils/misc/ShapeCalculator.h"
	#include "arm_compute/core/Validate.h"
	#include "arm_compute/core/Window.h"

	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo indices, const ITensorInfo *output, int axis)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, indices, output);
	ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);

	if (axis < 0)
	{
	axis += input->num_dimensions();
	}

	ARM_COMPUTE_RETURN_ERROR_ON(0 > axis \|\| axis >= static_cast<int32_t>(input->num_dimensions()));
	ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() + indices->num_dimensions() - 1 >
	Coordinates::num_max_dimensions);
	ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);

	if (output->total_size() != 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
	TensorShape output_shape = arm_compute::misc::shape_calculator::compute_gather_shape(
	input->tensor_shape(), indices->tensor_shape(), axis);
	ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() != output->tensor_shape().total_size());
	}

	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::U32, DataType::S32);

	return Status{};
	}
	} // namespace

	NEGatherKernel::NEGatherKernel()
	: _input{}, _indices{}, _axis{}, _output{}, _func{}, _src_it_strides{}, _idx_it_strides{}
	{
	}

	template <typename TIndex>
	void NEGatherKernel::gather_common(const Window &window, const ThreadInfo &info)
	{
	ARM_COMPUTE_UNUSED(info);

	auto dst_win = window;

	const auto src_info = _input->info();
	const auto idx_info = _indices->info();
	const auto dst_info = _output->info();

	const auto num_dims = dst_info->num_dimensions();
	const auto chunk_stride = src_info->strides_in_bytes()[_axis];

	const auto window_start_x = window.x().start();
	const auto window_end_x = window.x().end();
	auto window_size_x = src_info->element_size();

	const auto idx_limit = static_cast<TIndex>(src_info->tensor_shape()[_axis]);

	if (_axis != 0)
	{
	dst_win.set(0, Window::Dimension(window_start_x, window_start_x + 1, 1));
	window_size_x *= window_end_x - window_start_x;
	}

	// Compute source and index tensors window based on the output window.
	auto src_win = dst_win;
	Window idx_win;

	for (size_t i = 0; i < idx_info->num_dimensions(); ++i)
	{
	src_win.set(_axis + i, Window::Dimension(0, 1, 1));
	idx_win.set(_axis + i, window[_axis + i]);
	}

	// Use the custom strides to access all three tensors using the same loop.
	Iterator src_it(num_dims, _src_it_strides, _input->buffer(), src_info->offset_first_element_in_bytes(), src_win);
	Iterator idx_it(num_dims, _idx_it_strides, _indices->buffer(), idx_info->offset_first_element_in_bytes(), idx_win);
	Iterator dst_it(num_dims, dst_info->strides_in_bytes(), _output->buffer(),
	dst_info->offset_first_element_in_bytes(), dst_win);

	execute_window_loop(
	dst_win,
	[&](const Coordinates &)
	{
	const auto idx = reinterpret_cast<const TIndex >(idx_it.ptr());

	if (idx >= 0 && idx < idx_limit)
	{
	const auto src_ptr = src_it.ptr() + idx * chunk_stride;

	std::copy_n(src_ptr, window_size_x, dst_it.ptr());
	}
	else
	{
	std::fill_n(dst_it.ptr(), window_size_x, 0);
	}
	},
	src_it, idx_it, dst_it);
	}

	void NEGatherKernel::configure(const ITensor input, const ITensor indices, ITensor *output, int axis)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, indices);
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), indices->info(), output->info(), axis));

	_input = input;
	_indices = indices;
	_output = output;
	_axis = axis;

	if (_axis < 0)
	{
	_axis += input->info()->num_dimensions();
	}
	ARM_COMPUTE_ERROR_ON(0 > _axis \|\| _axis >= static_cast<int32_t>(input->info()->num_dimensions()));

	switch (_indices->info()->data_type())
	{
	case DataType::U32:
	_func = &NEGatherKernel::gather_common<uint32_t>;
	break;
	case DataType::S32:
	_func = &NEGatherKernel::gather_common<int32_t>;
	break;
	default:
	ARM_COMPUTE_ERROR("Not supported");
	break;
	}

	// Output auto initialization if not yet initialized
	const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_gather_shape(
	input->info()->tensor_shape(), indices->info()->tensor_shape(), _axis);
	auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));

	// Create window
	Window win = calculate_max_window(*output->info(), Steps());

	INEKernel::configure(win);

	// Create input and indices strides that have the same number of dimensions as the output tensor.
	// These will be used to iterate lock-step through all tensors (input, indices and output).
	size_t dim_no = 0;

	const auto input_info = input->info();
	const auto &input_strides = input_info->strides_in_bytes();

	const auto indices_info = indices->info();
	const auto &indices_strides = indices_info->strides_in_bytes();
	const auto indices_num_dims = indices_info->num_dimensions();

	for (; dim_no < static_cast<size_t>(_axis); ++dim_no)
	{
	_src_it_strides[dim_no] = input_strides[dim_no];
	}

	for (; dim_no < static_cast<size_t>(_axis) + indices_num_dims; ++dim_no)
	{
	_idx_it_strides[dim_no] = indices_strides[dim_no - _axis];
	}

	for (; dim_no < Coordinates::num_max_dimensions; ++dim_no)
	{
	_src_it_strides[dim_no] = input_strides[dim_no - indices_num_dims + 1];
	}
	}

	Status
	NEGatherKernel::validate(const ITensorInfo input, const ITensorInfo indices, const ITensorInfo *output, int axis)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, indices, output, axis));
	return Status{};
	}

	void NEGatherKernel::run(const Window &window, const ThreadInfo &info)
	{
	ARM_COMPUTE_UNUSED(info);
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON(_func == nullptr);

	(this->*_func)(window, info);
	}

	} // namespace arm_compute