mirror of https://github.com/alibaba/MNN.git
50 lines
1.6 KiB
C++
50 lines
1.6 KiB
C++
//
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// ShapeSpaceToDepth.cpp
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// MNN
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//
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// Created by MNN on 2019/07/16.
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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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class SpaceToDepthSizeComputer : 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(inputs.size() == 1);
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MNN_ASSERT(outputs.size() == 1);
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MNN_ASSERT(inputs[0]->buffer().dimensions == 4);
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const int blockSize = op->main_as_DepthSpaceParam()->blockSize();
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MNN_ASSERT(blockSize >= 1);
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auto& ib = inputs[0]->buffer();
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auto& ob = outputs[0]->buffer();
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ob.dimensions = ib.dimensions;
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ob.type = ib.type;
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auto format = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
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ob.dim[0].extent = ib.dim[0].extent;
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if (MNN_DATA_FORMAT_NHWC == format) {
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ob.dim[1].extent = ib.dim[1].extent / blockSize;
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ob.dim[2].extent = ib.dim[2].extent / blockSize;
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ob.dim[3].extent = ib.dim[3].extent * (blockSize * blockSize);
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} else {
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ob.dim[3].extent = ib.dim[3].extent / blockSize;
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ob.dim[2].extent = ib.dim[2].extent / blockSize;
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ob.dim[1].extent = ib.dim[1].extent * (blockSize * blockSize);
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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(SpaceToDepthSizeComputer, OpType_SpaceToDepth);
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} // namespace MNN
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