forked from jiuyuan/InfiniTensor
59 lines
1.8 KiB
C++
59 lines
1.8 KiB
C++
#pragma once
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#include "core/operator.h"
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#include <assert.h>
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namespace infini {
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/**
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* @brief General to band matrix multiplication, which is used for Longformer
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* model. See https://arxiv.org/pdf/2004.05150.pdf for detail.
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*
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*/
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class G2BMMObj : public OperatorObj {
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private:
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// to be implemented
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int width, dilation;
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ActType act;
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int b, m, k;
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public:
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/**
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* @brief Construct a new G2BMM object.
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*
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* @param graph The computation graph that this operator belongs to.
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* @param A The input tensor.
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* @param B The input tensor.
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* @param C C is the output of G2BMM. If outputs are going to be created in
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* the constructor, C should be an empty Ref.
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* @param width The width of the attention window.
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* @param dilation The dilation of the attention window.
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* @param bias The bias tensor.
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* @param act The activation.
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*/
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G2BMMObj(GraphObj *graph, Tensor A, Tensor B, Tensor C, const int width,
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const int dilation, Tensor bias = nullptr,
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ActType act = ActType::None);
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OP_CLONE(G2BMMObj);
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std::string toString() const override;
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optional<vector<Shape>> inferShape(const TensorVec &inputs) const override;
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int numInputs() const override { return 2; }
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int numOutputs() const override { return 1; }
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int getWidth() const { return width; }
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int getDilation() const { return dilation; }
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Tensor getBias() const { return inputs[2]; }
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ActType getAct() const { return act; }
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int getB() const { return b; }
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int getM() const { return m; }
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int getK() const { return k; }
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auto getBMKWD() const { return tuple{b, m, k, width, dilation}; }
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private:
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vector<int> getWorkloadVector() const override;
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vector<int> getOpAttrVector() const override;
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};
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} // namespace infini
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