| /* |
| * Copyright (c) 2021 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 "ROIPoolingLayer.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "tests/validation/Helpers.h" |
| #include <algorithm> |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| template <> |
| SimpleTensor<float> roi_pool_layer(const SimpleTensor<float> &src, const SimpleTensor<uint16_t> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo) |
| { |
| ARM_COMPUTE_UNUSED(output_qinfo); |
| |
| const size_t num_rois = rois.shape()[1]; |
| const size_t values_per_roi = rois.shape()[0]; |
| DataType output_data_type = src.data_type(); |
| |
| TensorShape input_shape = src.shape(); |
| TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), src.shape()[2], num_rois); |
| SimpleTensor<float> output(output_shape, output_data_type); |
| |
| const int pooled_w = pool_info.pooled_width(); |
| const int pooled_h = pool_info.pooled_height(); |
| const float spatial_scale = pool_info.spatial_scale(); |
| |
| // get sizes of x and y dimensions in src tensor |
| const int width = src.shape()[0]; |
| const int height = src.shape()[1]; |
| |
| // Move pointer across the fourth dimension |
| const size_t input_stride_w = input_shape[0] * input_shape[1] * input_shape[2]; |
| const size_t output_stride_w = output_shape[0] * output_shape[1] * output_shape[2]; |
| |
| const auto *rois_ptr = reinterpret_cast<const uint16_t *>(rois.data()); |
| |
| // Iterate through pixel width (X-Axis) |
| for(size_t pw = 0; pw < num_rois; ++pw) |
| { |
| const unsigned int roi_batch = rois_ptr[values_per_roi * pw]; |
| const auto x1 = rois_ptr[values_per_roi * pw + 1]; |
| const auto y1 = rois_ptr[values_per_roi * pw + 2]; |
| const auto x2 = rois_ptr[values_per_roi * pw + 3]; |
| const auto y2 = rois_ptr[values_per_roi * pw + 4]; |
| |
| //Iterate through pixel height (Y-Axis) |
| for(size_t fm = 0; fm < input_shape[2]; ++fm) |
| { |
| // Iterate through regions of interest index |
| for(size_t py = 0; py < pool_info.pooled_height(); ++py) |
| { |
| // 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 over feature map (Z axis) |
| for(size_t px = 0; px < pool_info.pooled_width(); ++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)) |
| { |
| /* Assign element in tensor 'output' at coordinates px, py, fm, roi_indx, to 0 */ |
| auto out_ptr = output.data() + px + py * output_shape[0] + fm * output_shape[0] * output_shape[1] + pw * output_stride_w; |
| *out_ptr = 0; |
| } |
| else |
| { |
| float curr_max = -std::numeric_limits<float>::max(); |
| for(int j = region_start_y; j < region_end_y; ++j) |
| { |
| for(int i = region_start_x; i < region_end_x; ++i) |
| { |
| /* Retrieve element from input tensor at coordinates(i, j, fm, roi_batch) */ |
| float in_element = *(src.data() + i + j * input_shape[0] + fm * input_shape[0] * input_shape[1] + roi_batch * input_stride_w); |
| curr_max = std::max(in_element, curr_max); |
| } |
| } |
| |
| /* Assign element in tensor 'output' at coordinates px, py, fm, roi_indx, to curr_max */ |
| auto out_ptr = output.data() + px + py * output_shape[0] + fm * output_shape[0] * output_shape[1] + pw * output_stride_w; |
| *out_ptr = curr_max; |
| } |
| } |
| } |
| } |
| } |
| |
| return output; |
| } |
| |
| /* |
| Template genericised method to allow calling of roi_pooling_layer with quantized 8 bit datatype |
| */ |
| template <> |
| SimpleTensor<uint8_t> roi_pool_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint16_t> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo) |
| { |
| const SimpleTensor<float> src_tmp = convert_from_asymmetric(src); |
| SimpleTensor<float> dst_tmp = roi_pool_layer<float>(src_tmp, rois, pool_info, output_qinfo); |
| SimpleTensor<uint8_t> dst = convert_to_asymmetric<uint8_t>(dst_tmp, output_qinfo); |
| return dst; |
| } |
| |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |