2019-04-17 10:49:11 +08:00
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//
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// ShapeUnpack.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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2019-12-27 22:16:57 +08:00
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#include "core/Macro.h"
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#include "core/SizeComputer.hpp"
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2019-04-17 10:49:11 +08:00
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namespace MNN {
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class UnpackComputer : 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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2020-04-11 20:37:20 +08:00
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if (nullptr == op || inputs.empty()) {
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// Avoid crash for special model
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return false;
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}
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2019-04-17 10:49:11 +08:00
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auto unpack = op->main_as_Axis();
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const int axis = unpack->axis();
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auto &input = inputs[0]->buffer();
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const int inputDimensions = input.dimensions;
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MNN_ASSERT(1 <= inputDimensions);
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std::vector<int> outDims;
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for (int i = 0; i < inputDimensions; i++) {
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if (axis == i) {
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continue;
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}
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outDims.push_back(input.dim[i].extent);
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}
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const int outputDimensions = inputDimensions - 1;
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MNN_ASSERT(outDims.size() == outputDimensions);
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for (int i = 0; i < outputs.size(); i++) {
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auto &output = outputs[i]->buffer();
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output.dimensions = outputDimensions;
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output.type = input.type;
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for (int j = 0; j < outputDimensions; j++) {
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output.dim[j].extent = outDims[j];
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}
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2019-08-22 20:13:46 +08:00
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TensorUtils::getDescribe(outputs[i])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
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2019-04-17 10:49:11 +08:00
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}
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return true;
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}
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};
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REGISTER_SHAPE(UnpackComputer, OpType_Unpack);
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} // namespace MNN
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