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

 /*
  * Copyright (c) 2018-2020 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 "src/core/NEON/kernels/NEPriorBoxLayerKernel.h"

 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/Validate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"

 #include <arm_neon.h>

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const PriorBoxLayerInfo &info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input1, input2);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2);

     // Check variances
     const int var_size = info.variances().size();
     if(var_size > 1)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(var_size != 4, "Must provide 4 variance values");
         for(int i = 0; i < var_size; ++i)
         {
             ARM_COMPUTE_RETURN_ERROR_ON_MSG(var_size <= 0, "Must be greater than 0");
         }
     }
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.steps()[0] < 0.f, "Step x should be greater or equal to 0");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.steps()[1] < 0.f, "Step y should be greater or equal to 0");

     if(!info.max_sizes().empty())
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.max_sizes().size() != info.min_sizes().size(), "Max and min sizes dimensions should match");
     }

     for(unsigned int i = 0; i < info.max_sizes().size(); ++i)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.max_sizes()[i] < info.min_sizes()[i], "Max size should be greater than min size");
     }

     if(output != nullptr && output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != 2);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, output);
     }

     return Status{};
 }
 } // namespace

 NEPriorBoxLayerKernel::NEPriorBoxLayerKernel()
     : _input1(nullptr), _input2(nullptr), _output(nullptr), _info()
 {
 }

 void NEPriorBoxLayerKernel::store_coordinates(float *out, const int offset, const float center_x, const float center_y, const float box_width, const float box_height, const int width,
                                               const int height)
 {
     float xmin = (center_x - box_width / 2.f) / width;
     float ymin = (center_y - box_height / 2.f) / height;
     float xmax = (center_x + box_width / 2.f) / width;
     float ymax = (center_y + box_height / 2.f) / height;

     float32x4_t vec_elements = { xmin, ymin, xmax, ymax };
     if(_info.clip())
     {
         static const float32x4_t CONST_0 = vdupq_n_f32(0.f);
         static const float32x4_t CONST_1 = vdupq_n_f32(1.f);
         vec_elements                     = vmaxq_f32(vminq_f32(vec_elements, CONST_1), CONST_0);
     }
     vst1q_f32(out + offset, vec_elements);
 }

 void NEPriorBoxLayerKernel::calculate_prior_boxes(const Window &window)
 {
     const int num_priors = _info.aspect_ratios().size() * _info.min_sizes().size() + _info.max_sizes().size();

     const DataLayout data_layout = _input1->info()->data_layout();
     const int        width_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
     const int        height_idx  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);

     const int layer_width  = _input1->info()->dimension(width_idx);
     const int layer_height = _input1->info()->dimension(height_idx);

     int img_width  = _info.img_size().x;
     int img_height = _info.img_size().y;
     if(img_width == 0 || img_height == 0)
     {
         img_width  = _input2->info()->dimension(width_idx);
         img_height = _input2->info()->dimension(height_idx);
     }

     float step_x = _info.steps()[0];
     float step_y = _info.steps()[1];
     if(step_x == 0.f || step_y == 0.f)
     {
         step_x = static_cast<float>(img_width) / layer_width;
         step_y = static_cast<float>(img_height) / layer_height;
     }

     Window slice = window.first_slice_window_2D();
     slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 2));

     Iterator output(_output, slice);
     execute_window_loop(slice, [&](const Coordinates & id)
     {
         float center_x = 0;
         float center_y = 0;
         int   idx      = id.x() / (4 * num_priors);
         center_x       = (static_cast<float>(idx % layer_width) + _info.offset()) * step_x;
         center_y       = (static_cast<float>(idx / layer_width) + _info.offset()) * step_y;

         float box_width;
         float box_height;
         int   offset = 0;

         auto out = reinterpret_cast<float *>(output.ptr());
         for(unsigned int i = 0; i < _info.min_sizes().size(); ++i)
         {
             const float min_size = _info.min_sizes().at(i);
             box_width            = min_size;
             box_height           = min_size;
             store_coordinates(out, offset, center_x, center_y, box_width, box_height, img_width, img_height);
             offset += 4;

             if(!_info.max_sizes().empty())
             {
                 const float max_size = _info.max_sizes().at(i);
                 box_width            = std::sqrt(min_size * max_size);
                 box_height           = box_width;

                 store_coordinates(out, offset, center_x, center_y, box_width, box_height, img_width, img_height);
                 offset += 4;
             }

             // rest of priors
             for(auto ar : _info.aspect_ratios())
             {
                 if(fabs(ar - 1.) < 1e-6)
                 {
                     continue;
                 }

                 box_width  = min_size * sqrt(ar);
                 box_height = min_size / sqrt(ar);

                 store_coordinates(out, offset, center_x, center_y, box_width, box_height, img_width, img_height);
                 offset += 4;
             }
         }

         // set the variance
         out = reinterpret_cast<float *>(_output->ptr_to_element(Coordinates(id.x(), 1)));
         float32x4_t var;
         if(_info.variances().size() == 1)
         {
             var = vdupq_n_f32(_info.variances().at(0));
         }
         else
         {
             const float32x4_t vars = { _info.variances().at(0), _info.variances().at(1), _info.variances().at(2), _info.variances().at(3) };
             var                    = vars;
         }
         for(int i = 0; i < num_priors; ++i)
         {
             vst1q_f32(out + 4 * i, var);
         }
     },
     output);
 }

 void NEPriorBoxLayerKernel::configure(const ITensor *input1, const ITensor *input2, ITensor *output, const PriorBoxLayerInfo &info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);

     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(), info));

     _input1 = input1;
     _input2 = input2;
     _info   = info;
     _output = output;

     // Configure kernel window
     const int   num_priors = info.aspect_ratios().size() * info.min_sizes().size() + info.max_sizes().size();
     Window      win        = calculate_max_window(*output->info(), Steps(num_priors * 4));
     Coordinates coord;
     coord.set_num_dimensions(output->info()->num_dimensions());
     output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));

     INEKernel::configure(win);
 }

 Status NEPriorBoxLayerKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const PriorBoxLayerInfo &info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, info));

     return Status{};
 }
 void NEPriorBoxLayerKernel::run(const Window &window, const ThreadInfo &info)
 {
     ARM_COMPUTE_UNUSED(info);
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

     // Run function
     calculate_prior_boxes(window);
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2018-2020 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 "src/core/NEON/kernels/NEPriorBoxLayerKernel.h"

	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/ITensor.h"
	#include "arm_compute/core/Types.h"
	#include "arm_compute/core/Validate.h"
	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"

	#include <arm_neon.h>

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input1, const ITensorInfo input2, const ITensorInfo *output, const PriorBoxLayerInfo &info)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::F32);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input1, input2);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2);

	// Check variances
	const int var_size = info.variances().size();
	if(var_size > 1)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(var_size != 4, "Must provide 4 variance values");
	for(int i = 0; i < var_size; ++i)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(var_size <= 0, "Must be greater than 0");
	}
	}
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.steps()[0] < 0.f, "Step x should be greater or equal to 0");
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.steps()[1] < 0.f, "Step y should be greater or equal to 0");

	if(!info.max_sizes().empty())
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.max_sizes().size() != info.min_sizes().size(), "Max and min sizes dimensions should match");
	}

	for(unsigned int i = 0; i < info.max_sizes().size(); ++i)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.max_sizes()[i] < info.min_sizes()[i], "Max size should be greater than min size");
	}

	if(output != nullptr && output->total_size() != 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != 2);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, output);
	}

	return Status{};
	}
	} // namespace

	NEPriorBoxLayerKernel::NEPriorBoxLayerKernel()
	: _input1(nullptr), _input2(nullptr), _output(nullptr), _info()
	{
	}

	void NEPriorBoxLayerKernel::store_coordinates(float *out, const int offset, const float center_x, const float center_y, const float box_width, const float box_height, const int width,
	const int height)
	{
	float xmin = (center_x - box_width / 2.f) / width;
	float ymin = (center_y - box_height / 2.f) / height;
	float xmax = (center_x + box_width / 2.f) / width;
	float ymax = (center_y + box_height / 2.f) / height;

	float32x4_t vec_elements = { xmin, ymin, xmax, ymax };
	if(_info.clip())
	{
	static const float32x4_t CONST_0 = vdupq_n_f32(0.f);
	static const float32x4_t CONST_1 = vdupq_n_f32(1.f);
	vec_elements = vmaxq_f32(vminq_f32(vec_elements, CONST_1), CONST_0);
	}
	vst1q_f32(out + offset, vec_elements);
	}

	void NEPriorBoxLayerKernel::calculate_prior_boxes(const Window &window)
	{
	const int num_priors = _info.aspect_ratios().size() * _info.min_sizes().size() + _info.max_sizes().size();

	const DataLayout data_layout = _input1->info()->data_layout();
	const int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);

	const int layer_width = _input1->info()->dimension(width_idx);
	const int layer_height = _input1->info()->dimension(height_idx);

	int img_width = _info.img_size().x;
	int img_height = _info.img_size().y;
	if(img_width == 0 \|\| img_height == 0)
	{
	img_width = _input2->info()->dimension(width_idx);
	img_height = _input2->info()->dimension(height_idx);
	}

	float step_x = _info.steps()[0];
	float step_y = _info.steps()[1];
	if(step_x == 0.f \|\| step_y == 0.f)
	{
	step_x = static_cast<float>(img_width) / layer_width;
	step_y = static_cast<float>(img_height) / layer_height;
	}

	Window slice = window.first_slice_window_2D();
	slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 2));

	Iterator output(_output, slice);
	execute_window_loop(slice, [&](const Coordinates & id)
	{
	float center_x = 0;
	float center_y = 0;
	int idx = id.x() / (4 * num_priors);
	center_x = (static_cast<float>(idx % layer_width) + _info.offset()) * step_x;
	center_y = (static_cast<float>(idx / layer_width) + _info.offset()) * step_y;

	float box_width;
	float box_height;
	int offset = 0;

	auto out = reinterpret_cast<float *>(output.ptr());
	for(unsigned int i = 0; i < _info.min_sizes().size(); ++i)
	{
	const float min_size = _info.min_sizes().at(i);
	box_width = min_size;
	box_height = min_size;
	store_coordinates(out, offset, center_x, center_y, box_width, box_height, img_width, img_height);
	offset += 4;

	if(!_info.max_sizes().empty())
	{
	const float max_size = _info.max_sizes().at(i);
	box_width = std::sqrt(min_size * max_size);
	box_height = box_width;

	store_coordinates(out, offset, center_x, center_y, box_width, box_height, img_width, img_height);
	offset += 4;
	}

	// rest of priors
	for(auto ar : _info.aspect_ratios())
	{
	if(fabs(ar - 1.) < 1e-6)
	{
	continue;
	}

	box_width = min_size * sqrt(ar);
	box_height = min_size / sqrt(ar);

	store_coordinates(out, offset, center_x, center_y, box_width, box_height, img_width, img_height);
	offset += 4;
	}
	}

	// set the variance
	out = reinterpret_cast<float *>(_output->ptr_to_element(Coordinates(id.x(), 1)));
	float32x4_t var;
	if(_info.variances().size() == 1)
	{
	var = vdupq_n_f32(_info.variances().at(0));
	}
	else
	{
	const float32x4_t vars = { _info.variances().at(0), _info.variances().at(1), _info.variances().at(2), _info.variances().at(3) };
	var = vars;
	}
	for(int i = 0; i < num_priors; ++i)
	{
	vst1q_f32(out + 4 * i, var);
	}
	},
	output);
	}

	void NEPriorBoxLayerKernel::configure(const ITensor input1, const ITensor input2, ITensor *output, const PriorBoxLayerInfo &info)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);

	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(), info));

	_input1 = input1;
	_input2 = input2;
	_info = info;
	_output = output;

	// Configure kernel window
	const int num_priors = info.aspect_ratios().size() * info.min_sizes().size() + info.max_sizes().size();
	Window win = calculate_max_window(output->info(), Steps(num_priors 4));
	Coordinates coord;
	coord.set_num_dimensions(output->info()->num_dimensions());
	output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));

	INEKernel::configure(win);
	}

	Status NEPriorBoxLayerKernel::validate(const ITensorInfo input1, const ITensorInfo input2, const ITensorInfo *output, const PriorBoxLayerInfo &info)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, info));

	return Status{};
	}
	void NEPriorBoxLayerKernel::run(const Window &window, const ThreadInfo &info)
	{
	ARM_COMPUTE_UNUSED(info);
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

	// Run function
	calculate_prior_boxes(window);
	}
	} // namespace arm_compute