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 +1,48 @@
+//
+//  ShapeTopKV2.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 TopKV2SizeComputer : 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(2 == outputs.size());
+        auto input   = inputs[0];
+        auto kTensor = inputs[1];
+        MNN_ASSERT(kTensor->elementSize() == 1); // Scalar
+        MNN_ASSERT(kTensor->getType().code == halide_type_int);
+        const int k              = kTensor->host<int32_t>()[0];
+        const int inputDimension = input->buffer().dimensions;
+        int axis = (inputs.size() == 3 ? inputs[2]->host<int32_t>()[0] : inputDimension - 1);
+        if (axis < 0) axis += input->dimensions();
+        // outputs: 0 --> data, 1 --> index
+
+        auto outputData                 = outputs[0];
+        outputData->buffer().dimensions = inputDimension;
+        memcpy(outputData->buffer().dim, input->buffer().dim, inputDimension * sizeof(halide_dimension_t));
+        outputData->buffer().dim[axis].extent = k;
+        outputData->buffer().type                           = input->buffer().type;
+
+        auto outputIndices                 = outputs[1];
+        outputIndices->buffer().dimensions = inputDimension;
+        memcpy(outputIndices->buffer().dim, input->buffer().dim, inputDimension * sizeof(halide_dimension_t));
+        outputIndices->buffer().dim[axis].extent = k;
+        outputIndices->setType(MNN::DataType_DT_INT32);
+        TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+        TensorUtils::getDescribe(outputs[1])->dimensionFormat = TensorUtils::getDescribe(inputs[1])->dimensionFormat;
+
+        return true;
+    }
+};
+
+REGISTER_SHAPE_INPUTS(TopKV2SizeComputer, OpType_TopKV2, (std::vector<int>{1,2}));
+} // namespace MNN