mirror of https://github.com/alibaba/MNN.git
47 lines
1.7 KiB
C++
47 lines
1.7 KiB
C++
//
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// ShapeROIAlign.cpp
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// MNN
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//
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// Created by MNN on 2021/11/02.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "core/Macro.h"
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#include "shape/SizeComputer.hpp"
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namespace MNN {
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class ROIAlignComputer : public SizeComputer {
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virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
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const std::vector<Tensor*>& outputs) const override {
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MNN_ASSERT(2 == inputs.size() || 3 == inputs.size() || 4 == inputs.size());
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MNN_ASSERT(1 == outputs.size());
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if (inputs.size() == 2 || inputs.size() == 3) {
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// copy dims
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auto& input = inputs[0]->buffer();
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auto& output = outputs[0]->buffer();
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memcpy(output.dim, input.dim, sizeof(halide_dimension_t) * input.dimensions);
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output.type = halide_type_of<float>();
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// width & height
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auto roi = op->main_as_RoiParameters();
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output.dim[3].extent = roi->pooledWidth();
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output.dim[2].extent = roi->pooledHeight();
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output.dim[0].extent = inputs[1]->batch();
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TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
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}
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// backward mode, fourth input is backward diff, output is the grad of inputs[0]
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if (inputs.size() == 4) {
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TensorUtils::copyShape(inputs[0], outputs[0], true);
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outputs[0]->buffer().type = inputs[0]->getType();
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}
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return true;
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}
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};
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REGISTER_SHAPE(ROIAlignComputer, OpType_ROIAlign);
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} // namespace MNN
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