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initial implementation of Tucker

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This commit is contained in:
Jiri Pittner 2025-10-21 17:40:48 +02:00
parent 6a3595f03e
commit ba58060c2d
2 changed files with 60 additions and 5 deletions
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48
tensor.cc
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@ -447,6 +447,7 @@ static void outputcallback(const SUPERINDEX &I, T *v)
//print indices flat
for(int i=0; i<I.size(); ++i)
for(int j=0; j<I[i].size(); ++j) *sout << I[i][j]<<" ";
//*sout<<" "<< " "<<(void *)v<<" "<< *v<<std::endl;
*sout<<" "<< *v<<std::endl;
}
@ -1075,6 +1076,53 @@ return r;
}
template<typename T>
NRVec<NRMat<T> > Tensor<T>::Tucker(typename LA_traits<T>::normtype thr)
{
int r=rank();
NRVec<NRMat<T> > ret(r);
if(r<2) return ret;
int rr=0;
for(int i=0; i<shape.size(); ++i)
for(int j=0; j<shape[i].number; ++j) //loop over all indices
{
NRMat<T> um;
NRVec<indexgroup> ushape;
{
Tensor<T> u=unwind_index(i,j);
ushape=u.shape;
um=u.matrix();
}
int mini=um.nrows(); if(um.ncols()<mini) mini=um.ncols(); //compact SVD, expect descendingly sorted values
NRMat<T> u(um.nrows(),mini),vt(mini,um.ncols());
NRVec<typename LA_traits<T>::normtype> w(mini);
singular_decomposition(um,&u,w,&vt,0);
um.resize(0,0); //deallocate
int preserve=mini;
for(int k=0; k<mini; ++k) if(w[k]<thr) {preserve=k; break;}
if(preserve==0) laerror("singular tensor in Tucker decomposition");
NRMat<T> umnew;
if(preserve<mini)
{
vt=vt.submatrix(0,preserve-1,0,um.ncols()-1);
w=w.subvector(0,preserve-1);
umnew=u.submatrix(0,um.nrows()-1,0,preserve-1);
}
else umnew=u;
ret[rr++]=vt.transpose(true);
umnew.diagmultr(w);
//rebuild tensor of the preserved shape from matrix
ushape[0].range=preserve;
NRVec<T> newdata(umnew);
*this = Tensor(ushape,newdata);
}
return ret;
}
template class Tensor<double>;

17
tensor.h
View File

@ -1,6 +1,6 @@
/*
LA: linear algebra C++ interface library
Copyright (C) 2024 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
Copyright (C) 2024-2025 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@ -21,6 +21,7 @@
//stored in an efficient way
//each index group has a specific symmetry (nosym,sym,antisym)
//additional symmetry between index groups (like in 2-electron integrals) is not supported directly, you would need to nest the class to Tensor<Tensor<T> >
//leftmost index is least significant (changing fastest) in the storage order
//presently only a rudimentary implementation
//presently limited to 2G data size due to NRVec - maybe use a typedef LA_index
//to uint64_t in the future in vector and matrix classes
@ -36,12 +37,16 @@
#include "smat.h"
#include "miscfunc.h"
//TODO:
//@@@!!!!!! - implement index names and contractions, unwinding etc. by named index list
//
//@@@contraction inside one tensor - compute resulting shape, loopover the shape, create index into the original tensor + loop over the contr. index, do the summation, store result
//@@@ will need to store vector of INDEX to the original tensor for the result's flatindex
//@@@ will not be particularly efficient
//
//@@@permutation of individual indices - chech the indices in sym groups remain adjacent, calculate result's shape, loopover the result and permute using unwind_callback
//@@@todo!!! - implement index names - flat vector of names, and contraction by named index list
//@@@?general permutation of individual indices - check the indices in sym groups remain adjacent, calculate result's shape, loopover the result and permute using unwind_callback
//
//
namespace LA {
@ -147,7 +152,9 @@ public:
explicit Tensor(const NRVec<T> &x);
explicit Tensor(const NRMat<T> &x);
explicit Tensor(const NRSMat<T> &x);
NRMat<T> matrix() const {return NRMat<T>(data,data.size()/groupsizes[0],groupsizes[0],0);}; //reinterpret as matrix with column index being the tensor's leftmost index group (typically the unwound single index)
bool is_flat() const {for(int i=0; i<shape.size(); ++i) if(shape[i].number>1) return false; return true;};
void clear() {data.clear();};
int rank() const {return myrank;};
int calcrank(); //is computed from shape
@ -207,7 +214,7 @@ public:
void grouploopover(void (*callback)(const GROUPINDEX &, T *)); //loop over all elements disregarding the internal structure of index groups
Tensor permute_index_groups(const NRPerm<int> &p) const; //rearrange the tensor storage permuting index groups as a whole
Tensor unwind_index(int group, int index) const; //separate an index from a group and expand it to full range as the least significant one
Tensor unwind_index(int group, int index) const; //separate an index from a group and expand it to full range as the least significant one (the leftmost one)
Tensor unwind_indices(const INDEXLIST &il) const; //the same for a list of indices
void addcontraction(const Tensor &rhs1, int group, int index, const Tensor &rhs2, int rhsgroup, int rhsindex, T alpha=1, T beta=1, bool doresize=false, bool conjugate1=false, bool conjugate=false); //rhs1 will have more significant non-contracted indices in the result than rhs2
inline Tensor contraction(int group, int index, const Tensor &rhs, int rhsgroup, int rhsindex, T alpha=1, bool conjugate1=false, bool conjugate=false) const {Tensor<T> r; r.addcontraction(*this,group,index,rhs,rhsgroup,rhsindex,alpha,0,true, conjugate1, conjugate); return r; };
@ -225,8 +232,8 @@ public:
void split_index_group(int group); //formal split of a non-symmetric index group WITHOUT the need for data reorganization
void merge_adjacent_index_groups(int groupfrom, int groupto); //formal merge of non-symmetric index groups WITHOUT the need for data reorganization
Tensor merge_index_groups(const NRVec<int> &groups) const;
NRVec<NRMat<T> > Tucker(typename LA_traits<T>::normtype thr=1e-12); //HOSVD-Tucker decomposition, return core tensor in *this, flattened
//TODO perhaps implement application of a permutation algebra to a product of several tensors
};