mirror of https://github.com/alibaba/MNN.git
46 lines
1.4 KiB
C++
46 lines
1.4 KiB
C++
//
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// ShapeLinSpace.cpp
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// MNN
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//
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// Created by MNN on 2019/12/11.
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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 LinSpaceSizeComputer : 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() == 3);
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MNN_ASSERT(outputs.size() == 1);
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auto& ib1 = inputs[0]->buffer();
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auto& ib2 = inputs[1]->buffer();
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auto& ib3 = inputs[2]->buffer();
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auto& ob = outputs[0]->buffer();
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MNN_ASSERT(ib1.dimensions == 0);
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MNN_ASSERT(ib2.dimensions == 0);
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MNN_ASSERT(ib3.dimensions == 0);
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MNN_ASSERT(inputs[0]->getType() == halide_type_of<float>());
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MNN_ASSERT(inputs[1]->getType() == halide_type_of<float>());
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MNN_ASSERT(inputs[2]->getType() == halide_type_of<int32_t>());
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int num = inputs[2]->host<int32_t>()[0];
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MNN_ASSERT(num > 0);
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ob.dimensions = 1;
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ob.dim[0].extent = num;
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outputs[0]->setType(DataType_DT_FLOAT);
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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(LinSpaceSizeComputer, OpType_LinSpace, {2});
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} // namespace MNN
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