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
@@ -0,0 +1,47 @@
+//
+//  ShapeROIPooling.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 {
+
+// Size Computer
+class ROIPoolingComputer : public SizeComputer {
+    virtual bool onComputeSize(const MNN::Op *op, const std::vector<Tensor *> &inputs,
+                               const std::vector<Tensor *> &outputs) const override {
+        MNN_ASSERT(2 == inputs.size() || 3 == inputs.size());
+        MNN_ASSERT(1 == outputs.size());
+
+        if (inputs.size() == 2) {
+            // copy dims
+            auto &input  = inputs[0]->buffer();
+            auto &output = outputs[0]->buffer();
+            memcpy(output.dim, input.dim, sizeof(halide_dimension_t) * input.dimensions);
+            output.type = halide_type_of<float>();
+
+            // width & height
+            auto roi             = op->main_as_RoiParameters();
+            output.dim[3].extent = roi->pooledWidth();
+            output.dim[2].extent = roi->pooledHeight();
+            output.dim[0].extent = inputs[1]->batch();
+            TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+        }
+
+        // backward mode, third input is backward diff, output is the grad of inputs[0]
+        if (inputs.size() == 3) {
+            TensorUtils::copyShape(inputs[0], outputs[0], true);
+            outputs[0]->buffer().type = inputs[0]->getType();
+        }
+
+        return true;
+    }
+};
+
+REGISTER_SHAPE(ROIPoolingComputer, OpType_ROIPooling);
+} // namespace MNN