//update all rows of Z^t
void M3LLinear::update_all_rows( SparseVector& x, const M3LFloat* Rrow, const M3LFloat& scale)
{
M3LFloat* Zk=Z;
M3LFloat mk;
int nnz=x.get_nnz();
for(int k=0;k<L;k++)
{
if(Rrow[k]==0)
{
Zk+=d;
continue;
}
mk=Rrow[k]*scale;
for(int i=0;i<nnz;i++)
{
Zk[x.get_ith_index(i)]+=mk*(x.get_ith_value(i));
}
b[k]+=Rrow[k]*scale*bias;
Zk+=d;
}
}
//helper functions
void add(M3LFloat* s, SparseVector a, M3LFloat scale)
{
int nnz=a.get_nnz();
for(int i=0;i<nnz;i++)
{
s[a.get_ith_index(i)]+=scale*(a.get_ith_value(i));
}
}
//update only current row of Z^t
void M3LLinear::update_current_row(const int& l, SparseVector& x, const M3LFloat& scale)
{
M3LFloat* Zl=getZrow(l);
int nnz=x.get_nnz();
for(int i=0;i<nnz;i++)
{
Zl[x.get_ith_index(i)]+=scale*(x.get_ith_value(i));
}
b[l]+=scale*bias;
}
M3LFloat M3LLinear::score(const int& l, SparseVector& x)
{
M3LFloat* Zl=getZrow(l);
int nnz=x.get_nnz();
M3LFloat sum=0;
for(int i=0;i<nnz;i++)
{
sum+=Zl[x.get_ith_index(i)]*x.get_ith_value(i);
}
sum+=bias*b[l];
return sum;
}
