| /* |
| * Copyright (c) 2017-2019 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/NEON/kernels/NEROIPoolingLayerKernel.h" |
| |
| #include "arm_compute/core/AccessWindowStatic.h" |
| #include "arm_compute/core/CPP/Validate.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| #include "support/ToolchainSupport.h" |
| |
| #include <cfloat> |
| #include <cmath> |
| |
| namespace arm_compute |
| { |
| NEROIPoolingLayerKernel::NEROIPoolingLayerKernel() |
| : _input(nullptr), _rois(nullptr), _output(nullptr), _pool_info(0, 0, 0.f) |
| { |
| } |
| |
| void NEROIPoolingLayerKernel::configure(const ITensor *input, const ITensor *rois, ITensor *output, const ROIPoolingLayerInfo &pool_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, rois); |
| |
| //Validate arguments |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), rois->info(), output->info()); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(rois, 1, DataType::U16); |
| ARM_COMPUTE_ERROR_ON(rois->info()->dimension(0) != 5); |
| ARM_COMPUTE_ERROR_ON(rois->info()->num_dimensions() > 2); |
| ARM_COMPUTE_ERROR_ON_CPU_F16_UNSUPPORTED(input); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16); |
| ARM_COMPUTE_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0)); |
| |
| if(output->info()->total_size() != 0) |
| { |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pool_info.pooled_width()) || (output->info()->dimension(1) != pool_info.pooled_height())); |
| ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != output->info()->dimension(2)); |
| ARM_COMPUTE_ERROR_ON(rois->info()->dimension(1) != output->info()->dimension(3)); |
| } |
| |
| // Output auto initialization if not yet initialized |
| TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), rois->info()->dimension(1)); |
| auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type()); |
| |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pool_info.pooled_width()) || (output->info()->dimension(1) != pool_info.pooled_height())); |
| |
| // Set instance variables |
| _input = input; |
| _rois = rois; |
| _output = output; |
| _pool_info = pool_info; |
| |
| // Configure kernel window |
| Window window; |
| window.set(Window::DimX, Window::Dimension(0, rois->info()->dimension(1))); |
| window.set(Window::DimY, Window::Dimension(0, 1)); |
| |
| AccessWindowStatic input_access(input->info(), |
| input->info()->valid_region().start(0), |
| input->info()->valid_region().start(1), |
| input->info()->valid_region().end(0), |
| input->info()->valid_region().end(1)); |
| AccessWindowStatic output_access(output->info(), 0, 0, pool_info.pooled_width(), pool_info.pooled_height()); |
| |
| ARM_COMPUTE_UNUSED(update_window_and_padding(window, input_access, output_access)); |
| output_access.set_valid_region(window, ValidRegion(Coordinates(), output->info()->tensor_shape())); |
| INEKernel::configure(window); |
| } |
| |
| void NEROIPoolingLayerKernel::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); |
| |
| const size_t values_per_roi = _rois->info()->dimension(0); |
| |
| const int roi_list_start = window.x().start(); |
| const int roi_list_end = window.x().end(); |
| const int width = _input->info()->dimension(Window::DimX); |
| const int height = _input->info()->dimension(Window::DimY); |
| const int fms = _input->info()->dimension(Window::DimZ); |
| const int pooled_w = _pool_info.pooled_width(); |
| const int pooled_h = _pool_info.pooled_height(); |
| const float spatial_scale = _pool_info.spatial_scale(); |
| |
| const auto *rois_ptr = reinterpret_cast<const uint16_t *>(_rois->buffer()); |
| |
| for(int roi_indx = roi_list_start; roi_indx < roi_list_end; ++roi_indx) |
| { |
| const unsigned int roi_batch = rois_ptr[values_per_roi * roi_indx]; |
| const auto x1 = rois_ptr[values_per_roi * roi_indx + 1]; |
| const auto y1 = rois_ptr[values_per_roi * roi_indx + 2]; |
| const auto x2 = rois_ptr[values_per_roi * roi_indx + 3]; |
| const auto y2 = rois_ptr[values_per_roi * roi_indx + 4]; |
| |
| // Scale ROI |
| const int roi_anchor_x = support::cpp11::round(x1 * spatial_scale); |
| const int roi_anchor_y = support::cpp11::round(y1 * spatial_scale); |
| const int roi_width = std::max(support::cpp11::round((x2 - x1) * spatial_scale), 1.f); |
| const int roi_height = std::max(support::cpp11::round((y2 - y1) * spatial_scale), 1.f); |
| |
| // Iterate through all feature maps |
| for(int fm = 0; fm < fms; ++fm) |
| { |
| // Iterate through all output pixels |
| for(int py = 0; py < pooled_h; ++py) |
| { |
| for(int px = 0; px < pooled_w; ++px) |
| { |
| auto region_start_x = static_cast<int>(std::floor((static_cast<float>(px) / pooled_w) * roi_width)); |
| auto region_end_x = static_cast<int>(std::floor((static_cast<float>(px + 1) / pooled_w) * roi_width)); |
| auto region_start_y = static_cast<int>(std::floor((static_cast<float>(py) / pooled_h) * roi_height)); |
| auto region_end_y = static_cast<int>(std::floor((static_cast<float>(py + 1) / pooled_h) * roi_height)); |
| |
| region_start_x = std::min(std::max(region_start_x + roi_anchor_x, 0), width); |
| region_end_x = std::min(std::max(region_end_x + roi_anchor_x, 0), width); |
| region_start_y = std::min(std::max(region_start_y + roi_anchor_y, 0), height); |
| region_end_y = std::min(std::max(region_end_y + roi_anchor_y, 0), height); |
| |
| // Iterate through the pooling region |
| if((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) |
| { |
| *reinterpret_cast<float *>(_output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = 0; |
| } |
| else |
| { |
| float curr_max = -FLT_MAX; |
| for(int j = region_start_y; j < region_end_y; ++j) |
| { |
| for(int i = region_start_x; i < region_end_x; ++i) |
| { |
| const auto val = *reinterpret_cast<const float *>(_input->ptr_to_element(Coordinates(i, j, fm, roi_batch))); |
| curr_max = std::max(val, curr_max); |
| } |
| } |
| *reinterpret_cast<float *>(_output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = curr_max; |
| } |
| } |
| } |
| } |
| } |
| } |
| } // namespace arm_compute |
