mirror of https://github.com/alibaba/MNN.git
77 lines
2.7 KiB
C++
77 lines
2.7 KiB
C++
//
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// ShapeReduction.cpp
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// MNN
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//
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// Created by MNN on 2019/01/10.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "shape/SizeComputer.hpp"
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#include "core/Macro.h"
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#include "core/TensorUtils.hpp"
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namespace MNN {
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static int _getRealAxis(int axis, int n) {
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if (axis < 0) {
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return axis + n;
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}
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return axis;
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}
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class ReductionComputer : public SizeComputer {
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public:
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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(1 == inputs.size() || 2 == inputs.size());
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MNN_ASSERT(1 == outputs.size());
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auto output = outputs[0];
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TensorUtils::getDescribe(output)->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
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auto reduce = op->main_as_ReductionParam();
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output->buffer().type = inputs[0]->buffer().type;
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if (nullptr == reduce->dim() && inputs.size() == 1) {
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output->buffer().dimensions = 0;
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return true;
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}
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std::set<int> reduceDimSet;
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if (nullptr != reduce->dim()) {
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for (int i = 0; i < reduce->dim()->size(); ++i) {
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reduceDimSet.insert(_getRealAxis(reduce->dim()->data()[i], inputs[0]->dimensions()));
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}
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} else {
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auto input1 = inputs[1];
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auto size = input1->elementSize();
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auto dims = input1->host<int32_t>();
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for (int i = 0; i < size; ++i) {
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reduceDimSet.insert(_getRealAxis(dims[i], inputs[0]->dimensions()));
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}
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}
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auto input = inputs[0];
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const int inputDimensions = input->dimensions();
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if (reduceDimSet.find(-1) != reduceDimSet.end()) {
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// dim set have -1 which mean applying reduction on last dimension
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reduceDimSet.erase(-1);
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reduceDimSet.insert(inputDimensions - 1);
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}
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std::vector<int> newDims;
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for (int i = 0; i < inputDimensions; ++i) {
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if (reduceDimSet.find(i) == reduceDimSet.end()) {
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newDims.push_back(input->length(i));
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} else if (reduce->keepDims()) {
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newDims.push_back(1);
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}
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}
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output->buffer().dimensions = (int)newDims.size();
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for (int i = 0; i < newDims.size(); ++i) {
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output->buffer().dim[i].extent = newDims[i];
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}
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TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
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return true;
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}
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};
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REGISTER_SHAPE_INPUTS(ReductionComputer, OpType_Reduction, {1});
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} // namespace MNN
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