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Replace norm() with squaredNorm() to address integer overflows

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For random matrices with integer coefficients, many of the tests here lead to
integer overflows. When taking the norm() of a row/column, the squaredNorm()
often overflows to a negative value, leading to domain errors when taking the
sqrt(). This leads to a crash on some systems. By replacing the norm() call by
a squaredNorm(), the values still overflow, but at least there is no domain
error.

Addresses https://gitlab.com/libeigen/eigen/-/issues/1856
This commit is contained in:
Antonio Sanchez 2020-04-07 09:30:16 -07:00 committed by Antonio Sánchez
parent 9dda5eb7d2
commit 8e875719b3
1 changed files with 5 additions and 5 deletions
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10
test/stl_iterators.cpp
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@ -431,22 +431,22 @@ void test_stl_iterators(int rows=Rows, int cols=Cols)
{ {
RowVectorType row = RowVectorType::Random(cols); RowVectorType row = RowVectorType::Random(cols);
A.rowwise() = row; A.rowwise() = row;
VERIFY( std::all_of(A.rowwise().begin(), A.rowwise().end(), [&row](typename ColMatrixType::RowXpr x) { return internal::isApprox(x.norm(),row.norm()); }) ); VERIFY( std::all_of(A.rowwise().begin(), A.rowwise().end(), [&row](typename ColMatrixType::RowXpr x) { return internal::isApprox(x.squaredNorm(),row.squaredNorm()); }) );
VectorType col = VectorType::Random(rows); VectorType col = VectorType::Random(rows);
A.colwise() = col; A.colwise() = col;
VERIFY( std::all_of(A.colwise().begin(), A.colwise().end(), [&col](typename ColMatrixType::ColXpr x) { return internal::isApprox(x.norm(),col.norm()); }) ); VERIFY( std::all_of(A.colwise().begin(), A.colwise().end(), [&col](typename ColMatrixType::ColXpr x) { return internal::isApprox(x.squaredNorm(),col.squaredNorm()); }) );
VERIFY( std::all_of(A.colwise().cbegin(), A.colwise().cend(), [&col](typename ColMatrixType::ConstColXpr x) { return internal::isApprox(x.norm(),col.norm()); }) ); VERIFY( std::all_of(A.colwise().cbegin(), A.colwise().cend(), [&col](typename ColMatrixType::ConstColXpr x) { return internal::isApprox(x.squaredNorm(),col.squaredNorm()); }) );
i = internal::random<Index>(0,A.rows()-1); i = internal::random<Index>(0,A.rows()-1);
A.setRandom(); A.setRandom();
A.row(i).setZero(); A.row(i).setZero();
VERIFY_IS_EQUAL( std::find_if(A.rowwise().begin(), A.rowwise().end(), [](typename ColMatrixType::RowXpr x) { return x.norm() == Scalar(0); })-A.rowwise().begin(), i ); VERIFY_IS_EQUAL( std::find_if(A.rowwise().begin(), A.rowwise().end(), [](typename ColMatrixType::RowXpr x) { return x.squaredNorm() == Scalar(0); })-A.rowwise().begin(), i );
j = internal::random<Index>(0,A.cols()-1); j = internal::random<Index>(0,A.cols()-1);
A.setRandom(); A.setRandom();
A.col(j).setZero(); A.col(j).setZero();
VERIFY_IS_EQUAL( std::find_if(A.colwise().begin(), A.colwise().end(), [](typename ColMatrixType::ColXpr x) { return x.norm() == Scalar(0); })-A.colwise().begin(), j ); VERIFY_IS_EQUAL( std::find_if(A.colwise().begin(), A.colwise().end(), [](typename ColMatrixType::ColXpr x) { return x.squaredNorm() == Scalar(0); })-A.colwise().begin(), j );
} }
{ {