forked from jiuyuan/InfiniTensor
75 lines
2.8 KiB
C++
75 lines
2.8 KiB
C++
#pragma once
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#include "core/operator.h"
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namespace infini {
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/**
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* @brief Matrix multiplication.
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*
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*/
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class MatmulObj : public OperatorObj {
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private:
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// InfiniTensor assumes a row-major tensor layout. `transA`=false means
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// default dims, true means A should be transposed before matmul. This is in
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// oppsite to the column-major BLAS.
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bool transA, transB;
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ActType act;
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// Auxiliary attributes which are not a part of operator attributes.
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int b, m, n, k;
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// Specifies the data precision for the matrix multiply.
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std::string computeType = "default";
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public:
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/**
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* @brief Matmul operator with batch broadcast and tensor transpose
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* supports. Only one tensor with singe batch can be broadcasted due to the
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* BLAS interface restriction. Tranpose indicates whether the last two
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* dimensions should be transposed before Matmul and does not affect other
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* leading dimensions.
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*
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* Matmul show how operators are defined in InfiniTensor. The constructor of
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* an operator can create output tensors for the operator or not, which
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* depends on `graph`.
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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 Matmul. 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 transA If matrix A should be transposed when computing.
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* @param transB If matrix B should be transposed when computing.
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* @param bias The bias tensor.
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* @param act The activation function.
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* @param computeType Specifies the data precision for the matrix multiply.
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*/
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MatmulObj(GraphObj *graph, Tensor A, Tensor B, Tensor C,
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bool transA = false, bool transB = false, Tensor bias = nullptr,
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ActType act = ActType::None, std::string computeType = "default");
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OP_CLONE(MatmulObj);
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std::string toString() const override;
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optional<vector<Shape>> inferShape(const TensorVec &inputs) override;
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int numInputs() const override { return inputs.size(); }
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int numOutputs() const override { return 1; }
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Tensor getBias() const { return inputs.size() > 2 ? inputs[2] : nullptr; }
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ActType getAct() const { return act; }
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auto getBMNKTransAB() const { return tuple(b, m, n, k, transA, transB); }
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bool getTransA() const { return transA; }
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bool getTransB() const { return transB; }
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int getB() const { return b; }
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int getM() const { return m; }
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int getN() const { return n; }
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int getK() const { return k; }
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auto getBMNK() const { return tuple{b, m, n, k}; }
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std::string getComputeType() const { return computeType; }
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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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