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update constraints to have checks for negative or zero sizes #3367

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9c649b1
update constraints to have checks for negative or zero sizes when not…
SteveBronder Oct 17, 2025
92002b5
clang format
SteveBronder Oct 17, 2025
ff489c7
Merge branch 'develop' into fix/constrain-size-checks
SteveBronder Oct 17, 2025
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31 changes: 22 additions & 9 deletions src/stan/io/deserializer.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -180,6 +180,7 @@ class deserializer {
return map_vector_t(nullptr, m);
} else {
check_r_capacity(m);
stan::math::check_nonnegative("read", "size", m);
return map_vector_t(&scalar_ptr_increment(m), m);
}
}
Expand All @@ -195,6 +196,7 @@ class deserializer {
if (unlikely(m == 0)) {
return Ret(map_vector_t(nullptr, m));
} else {
stan::math::check_nonnegative("read", "size", m);
check_r_capacity(2 * m);
Ret ret(m);
for (Eigen::Index i = 0; i < m; ++i) {
Expand All @@ -217,6 +219,7 @@ class deserializer {
if (unlikely(m == 0)) {
return map_row_vector_t(nullptr, m);
} else {
stan::math::check_nonnegative("read", "size", m);
check_r_capacity(m);
return map_row_vector_t(&scalar_ptr_increment(m), m);
}
Expand All @@ -233,6 +236,7 @@ class deserializer {
if (unlikely(m == 0)) {
return Ret(map_row_vector_t(nullptr, m));
} else {
stan::math::check_nonnegative("read", "size", m);
check_r_capacity(2 * m);
Ret ret(m);
for (Eigen::Index i = 0; i < m; ++i) {
Expand All @@ -256,6 +260,8 @@ class deserializer {
if (rows == 0 || cols == 0) {
return map_matrix_t(nullptr, rows, cols);
} else {
stan::math::check_nonnegative("read", "rows", rows);
stan::math::check_nonnegative("read", "cols", cols);
check_r_capacity(rows * cols);
return map_matrix_t(&scalar_ptr_increment(rows * cols), rows, cols);
}
Expand All @@ -273,6 +279,8 @@ class deserializer {
if (rows == 0 || cols == 0) {
return Ret(map_matrix_t(nullptr, rows, cols));
} else {
stan::math::check_nonnegative("read", "rows", rows);
stan::math::check_nonnegative("read", "cols", cols);
check_r_capacity(2 * rows * cols);
Ret ret(rows, cols);
for (Eigen::Index i = 0; i < rows * cols; ++i) {
Expand Down Expand Up @@ -798,10 +806,12 @@ class deserializer {
require_matrix_t<Ret>* = nullptr>
inline auto read_constrain_cholesky_factor_cov(LP& lp, Eigen::Index M,
Eigen::Index N) {
stan::math::check_greater_or_equal("read_constrain_cholesky_factor_cov",
"M", M, N);
const Eigen::Index size
= (M == 0 || N == 0) ? 0 : (N * (N + 1)) / 2 + (M - N) * N;
return stan::math::cholesky_factor_constrain<Jacobian>(
this->read<conditional_var_val_t<Ret, vector_t>>((N * (N + 1)) / 2
+ (M - N) * N),
M, N, lp);
this->read<conditional_var_val_t<Ret, vector_t>>(size), M, N, lp);
}

/**
Expand Down Expand Up @@ -857,9 +867,10 @@ class deserializer {
template <typename Ret, bool Jacobian, typename LP,
require_matrix_t<Ret>* = nullptr>
inline auto read_constrain_cholesky_factor_corr(LP& lp, Eigen::Index K) {
// If K is 0, we want to read 0 elements to form a 0x0 matrix
const Eigen::Index size = (K == 0) ? 0 : (K * (K - 1)) / 2;
return stan::math::cholesky_corr_constrain<Jacobian>(
this->read<conditional_var_val_t<Ret, vector_t>>((K * (K - 1)) / 2), K,
lp);
this->read<conditional_var_val_t<Ret, vector_t>>(size), K, lp);
}

/**
Expand Down Expand Up @@ -914,9 +925,9 @@ class deserializer {
template <typename Ret, bool Jacobian, typename LP,
require_matrix_t<Ret>* = nullptr>
inline auto read_constrain_cov_matrix(LP& lp, Eigen::Index k) {
const Eigen::Index size = (k == 0) ? 0 : (k * (k - 1)) / 2;
return stan::math::cov_matrix_constrain<Jacobian>(
this->read<conditional_var_val_t<Ret, vector_t>>(k + (k * (k - 1)) / 2),
k, lp);
this->read<conditional_var_val_t<Ret, vector_t>>(k + size), k, lp);
}

/**
Expand Down Expand Up @@ -969,9 +980,9 @@ class deserializer {
require_not_std_vector_t<Ret>* = nullptr,
require_matrix_t<Ret>* = nullptr>
inline auto read_constrain_corr_matrix(LP& lp, Eigen::Index k) {
const Eigen::Index size = (k == 0) ? 0 : (k * (k - 1)) / 2;
return stan::math::corr_matrix_constrain<Jacobian>(
this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2), k,
lp);
this->read<conditional_var_val_t<Ret, vector_t>>(size), k, lp);
}

/**
Expand Down Expand Up @@ -1024,6 +1035,7 @@ class deserializer {
require_matrix_t<Ret>* = nullptr>
inline auto read_constrain_stochastic_column(LP& lp, Eigen::Index rows,
Eigen::Index cols) {
stan::math::check_positive("read_stochastic_column", "rows", rows);
return stan::math::stochastic_column_constrain<Jacobian>(
this->read<conditional_var_val_t<Ret, matrix_t>>(rows - 1, cols), lp);
}
Expand Down Expand Up @@ -1080,6 +1092,7 @@ class deserializer {
require_matrix_t<Ret>* = nullptr>
inline auto read_constrain_stochastic_row(LP& lp, Eigen::Index rows,
Eigen::Index cols) {
stan::math::check_positive("read_stochastic_row", "cols", cols);
return stan::math::stochastic_row_constrain<Jacobian>(
this->read<conditional_var_val_t<Ret, matrix_t>>(rows, cols - 1), lp);
}
Expand Down
36 changes: 36 additions & 0 deletions src/test/unit/io/deserializer_test.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,7 @@ TEST(deserializer_vector, read) {

double z = deserializer.read<double>();
EXPECT_FLOAT_EQ(11.0, z);
EXPECT_THROW(deserializer.read<Eigen::VectorXd>(-1), std::domain_error);
}

TEST(deserializer_vector, complex_read) {
Expand Down Expand Up @@ -100,6 +101,7 @@ TEST(deserializer_vector, complex_read) {

double z = deserializer.read<double>();
EXPECT_FLOAT_EQ(15.0, z);
EXPECT_THROW(deserializer.read<complex_vec>(-1), std::domain_error);
}

// row vector
Expand All @@ -126,6 +128,7 @@ TEST(deserializer_row_vector, read) {

double z = deserializer.read<double>();
EXPECT_FLOAT_EQ(11.0, z);
EXPECT_THROW(deserializer.read<Eigen::RowVectorXd>(-1), std::domain_error);
}

TEST(deserializer_row_vector, complex_read) {
Expand Down Expand Up @@ -154,6 +157,7 @@ TEST(deserializer_row_vector, complex_read) {

double z = deserializer.read<double>();
EXPECT_FLOAT_EQ(15.0, z);
EXPECT_THROW(deserializer.read<complex_row_vec>(-1), std::domain_error);
}

// matrix
Expand Down Expand Up @@ -181,6 +185,8 @@ TEST(deserializer_matrix, read) {

double a = deserializer.read<double>();
EXPECT_FLOAT_EQ(13.0, a);
EXPECT_THROW(deserializer.read<eig_mat>(-1, 1), std::domain_error);
EXPECT_THROW(deserializer.read<eig_mat>(1, -1), std::domain_error);
}

TEST(deserializer_matrix, complex_read) {
Expand All @@ -205,6 +211,8 @@ TEST(deserializer_matrix, complex_read) {
EXPECT_FLOAT_EQ(sentinal, y(i).imag());
sentinal++;
}
EXPECT_THROW(deserializer.read<eig_mat>(-1, 1), std::domain_error);
EXPECT_THROW(deserializer.read<eig_mat>(1, -1), std::domain_error);
}

// array
Expand Down Expand Up @@ -643,6 +651,9 @@ TEST(deserializer_vector, simplex_constrain) {
double lp = 0;
Eigen::VectorXd reference
= stan::math::simplex_constrain(stan::math::to_vector(theta));
EXPECT_THROW(
(deserializer.read_constrain_simplex<Eigen::VectorXd, false>(lp, 0)),
std::domain_error);
Eigen::VectorXd phi(
deserializer.read_constrain_simplex<Eigen::VectorXd, false>(
lp, theta.size() + 1));
Expand Down Expand Up @@ -683,6 +694,9 @@ TEST(deserializer_vector, sum_to_zero_constrain) {
theta.push_back(0.0);
stan::io::deserializer<double> deserializer(theta, theta_i);
double lp = 0;
EXPECT_THROW(
(deserializer.read_constrain_sum_to_zero<Eigen::VectorXd, false>(lp, 0)),
std::domain_error);
Eigen::VectorXd reference
= stan::math::sum_to_zero_constrain(stan::math::to_vector(theta));
Eigen::VectorXd phi(
Expand Down Expand Up @@ -723,6 +737,12 @@ TEST(deserializer_matrix, sum_to_zero_constrain) {
theta.push_back(0.0);
stan::io::deserializer<double> deserializer(theta, theta_i);
double lp = 0.0;
EXPECT_THROW((deserializer.read_constrain_sum_to_zero<Eigen::MatrixXd, false>(
lp, 0, 1)),
std::domain_error);
EXPECT_THROW((deserializer.read_constrain_sum_to_zero<Eigen::MatrixXd, false>(
lp, 1, 0)),
std::domain_error);
Eigen::MatrixXd reference
= stan::math::sum_to_zero_constrain(stan::math::to_matrix(theta, 2, 2));
Eigen::MatrixXd phi(
Expand Down Expand Up @@ -874,6 +894,13 @@ TEST(deserializer_matrix, cholesky_factor_cov_constrain) {
theta.push_back(-static_cast<double>(i));
stan::io::deserializer<double> deserializer(theta, theta_i);
double lp = 0;
EXPECT_THROW(
(deserializer.read_constrain_cholesky_factor_cov<Eigen::MatrixXd, false>(
lp, 0, 1)),
std::domain_error);
EXPECT_NO_THROW(
(deserializer.read_constrain_cholesky_factor_cov<Eigen::MatrixXd, false>(
lp, 0, 0)));
Eigen::MatrixXd reference = stan::math::cholesky_factor_constrain(
stan::math::to_vector(theta).segment(0, 6), 3, 3);
Eigen::MatrixXd L(
Expand Down Expand Up @@ -956,6 +983,9 @@ TEST(deserializer_matrix, cholesky_factor_corr_constrain) {
theta.push_back(-static_cast<double>(i));
stan::io::deserializer<double> deserializer(theta, theta_i);
double lp = 0;
EXPECT_NO_THROW(
(deserializer.read_constrain_cholesky_factor_corr<Eigen::MatrixXd, false>(
lp, 0)));
Eigen::MatrixXd reference = stan::math::cholesky_corr_constrain(
stan::math::to_vector(theta).segment(0, 3), 3);
Eigen::MatrixXd L(
Expand Down Expand Up @@ -1002,6 +1032,8 @@ TEST(deserializer_matrix, cov_matrix_constrain) {
theta.push_back(-static_cast<double>(i));
stan::io::deserializer<double> deserializer(theta, theta_i);
double lp = 0;
EXPECT_NO_THROW(
(deserializer.read_constrain_cov_matrix<Eigen::MatrixXd, false>(lp, 0)));
Eigen::MatrixXd reference = stan::math::cov_matrix_constrain(
stan::math::to_vector(theta).segment(0, 6), 3);
Eigen::MatrixXd L(
Expand Down Expand Up @@ -1042,6 +1074,8 @@ TEST(deserializer_matrix, corr_matrix_constrain) {
theta.push_back(-static_cast<double>(i));
stan::io::deserializer<double> deserializer(theta, theta_i);
double lp = 0;
EXPECT_NO_THROW(
(deserializer.read_constrain_corr_matrix<Eigen::MatrixXd, false>(lp, 0)));
Eigen::MatrixXd reference = stan::math::corr_matrix_constrain(
stan::math::to_vector(theta).segment(0, 3), 3);
Eigen::MatrixXd L(
Expand All @@ -1061,6 +1095,8 @@ TEST(deserializer_matrix, corr_matrix_jacobian) {
stan::io::deserializer<double> deserializer(theta, theta_i);
double lp_ref = 0.0;
double lp = 0.0;
EXPECT_NO_THROW(
(deserializer.read_constrain_corr_matrix<Eigen::MatrixXd, true>(lp, 0)));
Eigen::MatrixXd reference = stan::math::corr_matrix_constrain(
stan::math::to_vector(theta).segment(0, 3), 3, lp_ref);
Eigen::MatrixXd L(
Expand Down