diff options
Diffstat (limited to 'src/runtime/NEON/functions/NEDetectionPostProcessLayer.cpp')
| -rw-r--r-- | src/runtime/NEON/functions/NEDetectionPostProcessLayer.cpp | 62 |
1 files changed, 44 insertions, 18 deletions
diff --git a/src/runtime/NEON/functions/NEDetectionPostProcessLayer.cpp b/src/runtime/NEON/functions/NEDetectionPostProcessLayer.cpp index 9e63800728..b347390162 100644 --- a/src/runtime/NEON/functions/NEDetectionPostProcessLayer.cpp +++ b/src/runtime/NEON/functions/NEDetectionPostProcessLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020 Arm Limited. + * Copyright (c) 2019-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -27,6 +27,8 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/core/Validate.h" +#include "src/common/utils/Log.h" + #include <cstddef> #include <ios> #include <list> @@ -34,23 +36,36 @@ namespace arm_compute { NEDetectionPostProcessLayer::NEDetectionPostProcessLayer(std::shared_ptr<IMemoryManager> memory_manager) - : _memory_group(std::move(memory_manager)), _dequantize(), _detection_post_process(), _decoded_scores(), _run_dequantize(false) + : _memory_group(std::move(memory_manager)), + _dequantize(), + _detection_post_process(), + _decoded_scores(), + _run_dequantize(false) { } -void NEDetectionPostProcessLayer::configure(const ITensor *input_box_encoding, const ITensor *input_scores, const ITensor *input_anchors, - ITensor *output_boxes, ITensor *output_classes, ITensor *output_scores, ITensor *num_detection, DetectionPostProcessLayerInfo info) +void NEDetectionPostProcessLayer::configure(const ITensor *input_box_encoding, + const ITensor *input_scores, + const ITensor *input_anchors, + ITensor *output_boxes, + ITensor *output_classes, + ITensor *output_scores, + ITensor *num_detection, + DetectionPostProcessLayerInfo info) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input_box_encoding, input_scores, input_anchors, output_boxes, output_classes, output_scores); - ARM_COMPUTE_ERROR_THROW_ON(NEDetectionPostProcessLayer::validate(input_box_encoding->info(), input_scores->info(), input_anchors->info(), output_boxes->info(), output_classes->info(), - output_scores->info(), - num_detection->info(), info)); + ARM_COMPUTE_ERROR_ON_NULLPTR(input_box_encoding, input_scores, input_anchors, output_boxes, output_classes, + output_scores); + ARM_COMPUTE_ERROR_THROW_ON(NEDetectionPostProcessLayer::validate( + input_box_encoding->info(), input_scores->info(), input_anchors->info(), output_boxes->info(), + output_classes->info(), output_scores->info(), num_detection->info(), info)); + ARM_COMPUTE_LOG_PARAMS(input_box_encoding, input_scores, input_anchors, output_boxes, output_classes, output_scores, + num_detection, info); const ITensor *input_scores_to_use = input_scores; DetectionPostProcessLayerInfo info_to_use = info; _run_dequantize = is_data_type_quantized(input_box_encoding->info()->data_type()); - if(_run_dequantize) + if (_run_dequantize) { _memory_group.manage(&_decoded_scores); @@ -59,26 +74,37 @@ void NEDetectionPostProcessLayer::configure(const ITensor *input_box_encoding, c input_scores_to_use = &_decoded_scores; // Create a new info struct to avoid dequantizing in the CPP layer - std::array<float, 4> scales_values{ info.scale_value_y(), info.scale_value_x(), info.scale_value_h(), info.scale_value_w() }; - DetectionPostProcessLayerInfo info_quantized(info.max_detections(), info.max_classes_per_detection(), info.nms_score_threshold(), info.iou_threshold(), info.num_classes(), - scales_values, info.use_regular_nms(), info.detection_per_class(), false); + std::array<float, 4> scales_values{info.scale_value_y(), info.scale_value_x(), info.scale_value_h(), + info.scale_value_w()}; + DetectionPostProcessLayerInfo info_quantized( + info.max_detections(), info.max_classes_per_detection(), info.nms_score_threshold(), info.iou_threshold(), + info.num_classes(), scales_values, info.use_regular_nms(), info.detection_per_class(), false); info_to_use = info_quantized; } - _detection_post_process.configure(input_box_encoding, input_scores_to_use, input_anchors, output_boxes, output_classes, output_scores, num_detection, info_to_use); + _detection_post_process.configure(input_box_encoding, input_scores_to_use, input_anchors, output_boxes, + output_classes, output_scores, num_detection, info_to_use); _decoded_scores.allocator()->allocate(); } -Status NEDetectionPostProcessLayer::validate(const ITensorInfo *input_box_encoding, const ITensorInfo *input_scores, const ITensorInfo *input_anchors, - ITensorInfo *output_boxes, ITensorInfo *output_classes, ITensorInfo *output_scores, ITensorInfo *num_detection, DetectionPostProcessLayerInfo info) +Status NEDetectionPostProcessLayer::validate(const ITensorInfo *input_box_encoding, + const ITensorInfo *input_scores, + const ITensorInfo *input_anchors, + ITensorInfo *output_boxes, + ITensorInfo *output_classes, + ITensorInfo *output_scores, + ITensorInfo *num_detection, + DetectionPostProcessLayerInfo info) { bool run_dequantize = is_data_type_quantized(input_box_encoding->data_type()); - if(run_dequantize) + if (run_dequantize) { TensorInfo decoded_classes_info = input_scores->clone()->set_is_resizable(true).set_data_type(DataType::F32); ARM_COMPUTE_RETURN_ON_ERROR(NEDequantizationLayer::validate(input_scores, &decoded_classes_info)); } - ARM_COMPUTE_RETURN_ON_ERROR(CPPDetectionPostProcessLayer::validate(input_box_encoding, input_scores, input_anchors, output_boxes, output_classes, output_scores, num_detection, info)); + ARM_COMPUTE_RETURN_ON_ERROR(CPPDetectionPostProcessLayer::validate(input_box_encoding, input_scores, input_anchors, + output_boxes, output_classes, output_scores, + num_detection, info)); return Status{}; } @@ -88,7 +114,7 @@ void NEDetectionPostProcessLayer::run() MemoryGroupResourceScope scope_mg(_memory_group); // Decode scores if necessary - if(_run_dequantize) + if (_run_dequantize) { _dequantize.run(); } |