mirror of https://github.com/alibaba/MNN.git
57 lines
1.6 KiB
C++
57 lines
1.6 KiB
C++
//
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// ShapeMatMul.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 "core/Macro.h"
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#include "core/SizeComputer.hpp"
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#include "core/TensorUtils.hpp"
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namespace MNN {
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class MatMulSizeComputer : 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());
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MNN_ASSERT(1 == outputs.size());
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MNN_ASSERT(2 == inputs[0]->buffer().dimensions);
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MNN_ASSERT(2 == inputs[1]->buffer().dimensions);
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MNN_ASSERT(op->main_type() == OpParameter_MatMul);
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auto matMul = op->main_as_MatMul();
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auto output = outputs[0];
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TensorUtils::copyShape(inputs[0], output, true);
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auto w0 = inputs[0]->length(1);
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auto h0 = inputs[0]->length(0);
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if (matMul->transposeA()) {
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auto t = w0;
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w0 = h0;
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h0 = t;
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}
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auto w1 = inputs[1]->length(1);
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auto h1 = inputs[1]->length(0);
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if (matMul->transposeB()) {
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auto t = w1;
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w1 = h1;
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h1 = t;
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}
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if (w0 != h1) {
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return false;
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}
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output->buffer().type = inputs[0]->buffer().type;
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output->setLength(0, h0);
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output->setLength(1, w1);
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TensorUtils::getDescribe(output)->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(MatMulSizeComputer, OpType_MatMul);
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} // namespace MNN
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