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Eliminate use of _res.

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This commit is contained in:
Antonio Sánchez
2023-10-16 19:56:53 +00:00
parent a96545777b
commit 5bdf58b8df
7 changed files with 99 additions and 95 deletions
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24
Eigen/src/SparseCore/SparseSparseProductWithPruning.h
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@@ -93,9 +93,9 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,C
static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
{
remove_all_t<ResultType> _res(res.rows(), res.cols());
internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,ResultType>(lhs, rhs, _res, tolerance);
res.swap(_res);
remove_all_t<ResultType> res_(res.rows(), res.cols());
internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,ResultType>(lhs, rhs, res_, tolerance);
res.swap(res_);
}
};
@@ -107,9 +107,9 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,C
{
// we need a col-major matrix to hold the result
typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> SparseTemporaryType;
SparseTemporaryType _res(res.rows(), res.cols());
internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, _res, tolerance);
res = _res;
SparseTemporaryType res_(res.rows(), res.cols());
internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, res_, tolerance);
res = res_;
}
};
@@ -120,9 +120,9 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,R
static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
{
// let's transpose the product to get a column x column product
remove_all_t<ResultType> _res(res.rows(), res.cols());
internal::sparse_sparse_product_with_pruning_impl<Rhs,Lhs,ResultType>(rhs, lhs, _res, tolerance);
res.swap(_res);
remove_all_t<ResultType> res_(res.rows(), res.cols());
internal::sparse_sparse_product_with_pruning_impl<Rhs,Lhs,ResultType>(rhs, lhs, res_, tolerance);
res.swap(res_);
}
};
@@ -140,9 +140,9 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,R
// let's transpose the product to get a column x column product
// typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType;
// SparseTemporaryType _res(res.cols(), res.rows());
// sparse_sparse_product_with_pruning_impl<Rhs,Lhs,SparseTemporaryType>(rhs, lhs, _res);
// res = _res.transpose();
// SparseTemporaryType res_(res.cols(), res.rows());
// sparse_sparse_product_with_pruning_impl<Rhs,Lhs,SparseTemporaryType>(rhs, lhs, res_);
// res = res_.transpose();
}
};