chore: import upstream snapshot with attribution

2026-07-13 13:33:03 +08:00
commit 5b57521aa1
8226 changed files with 3425766 additions and 0 deletions
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+//
+//  ShapeNonMaxSuppressionV2.cpp
+//  MNN
+//
+//  Created by MNN on 2019/01/10.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "shape/SizeComputer.hpp"
+#include "core/Macro.h"
+
+namespace MNN {
+
+class NonMaxSuppressionV2Computer : public SizeComputer {
+    virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
+                               const std::vector<Tensor*>& outputs) const override {
+        // boxes: [num_boxes, 4]
+        const Tensor* boxes = inputs[0];
+        // scores: [num_boxes]
+        const Tensor* scores = inputs[1];
+        // iou_threshold: scalar
+        if (inputs.size() > 3 && inputs[3]->host<float>() != nullptr) {
+            auto iou_threshold_val = inputs[3]->host<float>()[0];
+            MNN_ASSERT(iou_threshold_val >= 0 && iou_threshold_val <= 1);
+        }
+        
+        int num_boxes = 0;
+        MNN_ASSERT(boxes->buffer().dimensions == 2);
+        num_boxes = boxes->buffer().dim[0].extent;
+
+        MNN_ASSERT(boxes->buffer().dimensions == 2 && scores->buffer().dim[0].extent == num_boxes &&
+                   boxes->buffer().dim[1].extent == 4 && scores->buffer().dimensions == 1);
+
+        int output_size = num_boxes;
+        if (inputs.size() > 2 && inputs[2]->host<int32_t>() != nullptr) {
+            output_size = std::min(inputs[2]->host<int32_t>()[0], num_boxes);
+        }
+
+        // TODO ramdom output shape only for fast rcnn
+        outputs[0]->buffer().dimensions = 1;
+        outputs[0]->setType(MNN::DataType_DT_INT32);
+        outputs[0]->buffer().dim[0].extent = output_size;
+        TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+
+        return true;
+    }
+};
+
+REGISTER_SHAPE_INPUTS(NonMaxSuppressionV2Computer, OpType_NonMaxSuppressionV2, (std::vector<int>{2, 3}));
+} // namespace MNN