Use boost beta, simplify overloads #3212

andrjohns · 2025-06-25T14:23:29Z

Summary

This PR replaces our manual implementation of the beta function with the one from Boost which is more accurate over a broader domain

I've also combined the multiple overloads into a single overload per prim, rev, fwd now that we have if constexpr.

Tests

N/A

Side Effects

N/A

Release notes

Use Boost's implementation of beta for improved stability

Checklist

Copyright holder: Andrew Johnson

The copyright holder is typically you or your assignee, such as a university or company. By submitting this pull request, the copyright holder is agreeing to the license the submitted work under the following licenses:
- Code: BSD 3-clause (https://opensource.org/licenses/BSD-3-Clause)
- Documentation: CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
the basic tests are passing
- unit tests pass (to run, use: ./runTests.py test/unit)
- header checks pass, (make test-headers)
- dependencies checks pass, (make test-math-dependencies)
- docs build, (make doxygen)
- code passes the built in C++ standards checks (make cpplint)
the code is written in idiomatic C++ and changes are documented in the doxygen
the new changes are tested

andrjohns · 2025-06-25T14:26:49Z

@SteveBronder what do you think of this structure for combining overloads with if constexpr? Just figuring out a good consistent structure to follow

SteveBronder · 2025-10-20T16:11:21Z

stan/math/fwd/fun/beta.hpp

+  const FvarInnerT beta_val = beta(a_val, b_val);
+  const FvarInnerT digamma_ab = digamma(a_val + b_val);
+  FvarInnerT beta_d(0);
+  if constexpr (!is_constant<Ta>::value) {


Suggested change

if constexpr (!is_constant<Ta>::value) {

if constexpr (is_autodiff_v<Ta>) {

SteveBronder · 2025-10-20T16:12:01Z

stan/math/fwd/fun/beta.hpp

+  if constexpr (!is_constant<Ta>::value) {
+    beta_d += (digamma(a_val) - digamma_ab) * beta_val * a.d_;
+  }
+  if constexpr (!is_constant<Tb>::value) {


Suggested change

if constexpr (!is_constant<Tb>::value) {

if constexpr (is_autodiff_v<Tb>) {

SteveBronder · 2025-10-20T16:36:50Z

stan/math/prim/fun/beta.hpp

+template <
+    typename T1, typename T2, require_any_container_t<T1, T2>* = nullptr,
+    require_t<math::disjunction<
+        is_arithmetic<return_type_t<T1, T2>>, is_fvar<return_type_t<T1, T2>>,
+        is_std_vector<T1>, is_std_vector<T2>>>* = nullptr>


Little confused. Wouldn't is_fvar<return_type> conflict with the fvar version of beta?

SteveBronder · 2025-10-20T16:38:56Z

stan/math/rev/fun/beta.hpp

+inline auto beta(const T1& a, const T2& b) {
+  arena_t<ref_type_t<T1>> arena_a = a;
+  arena_t<ref_type_t<T2>> arena_b = b;


Suggested change

inline auto beta(const T1& a, const T2& b) {

arena_t<ref_type_t<T1>> arena_a = a;

arena_t<ref_type_t<T2>> arena_b = b;

inline auto beta(T1&& a, T2&& b) {

arena_t<ref_type_t<T1>> arena_a = std::forward<T1>(a);

arena_t<ref_type_t<T2>> arena_b = std::forward<T2>(b);

SteveBronder · 2025-10-20T16:40:09Z

stan/math/rev/fun/beta.hpp

+  const auto& beta_val = beta(value_of(arena_a), value_of(arena_b));
+  using return_type_t = return_var_matrix_t<decltype(beta_val), T1, T2>;
+  arena_t<return_type_t> res(beta_val);


Suggested change

const auto& beta_val = beta(value_of(arena_a), value_of(arena_b));

using return_type_t = return_var_matrix_t<decltype(beta_val), T1, T2>;

arena_t<return_type_t> res(beta_val);

using inner_ret_t = decltype(beta(value_of(arena_a), value_of(arena_b)));

using return_type_t = return_var_matrix_t<inner_ret_t, T1, T2>;

arena_t<return_type_t> res(beta(value_of(arena_a), value_of(arena_b)));

SteveBronder · 2025-10-20T16:45:23Z

stan/math/rev/fun/beta.hpp

+    auto&& b_array = as_array_or_scalar(arena_b);
+    const auto& res_array = as_array_or_scalar(res);
+    const auto& digamma_ab = digamma(value_of(a_array) + value_of(b_array));
+    const auto& adj_val = res_array.adj() * res_array.val();


This produces a new expression objet so we don't need a const& of it

Suggested change

const auto& adj_val = res_array.adj() * res_array.val();

auto adj_val = res_array.adj() * res_array.val();

Anywhere that we will produce a new Eigen expression it should just be an object.

Same for several places here

SteveBronder · 2025-10-20T16:48:02Z

stan/math/rev/fun/beta.hpp

+  reverse_pass_callback([arena_a, arena_b, res]() mutable {
+    auto&& a_array = as_array_or_scalar(arena_a);
+    auto&& b_array = as_array_or_scalar(arena_b);
+    const auto& res_array = as_array_or_scalar(res);


You can use decltype(auto) here since as_array_or_scalar. decltype(auto) is allowed to be either a reference to an object or an object. The function as_array_or_scalar can either return a reference, for instance for a scalar or if an array is passed in as input and then given as output. It can also return a new object, like when we are return an array view of a matrix. That array view is an actual object.

SteveBronder · 2025-10-20T16:48:27Z

stan/math/rev/fun/beta.hpp

-  auto digamma_ab = (digamma(b.val()) - digamma(a + b.val())) * beta_val;
-  return make_callback_var(beta_val, [b, digamma_ab](auto& vi) mutable {
-    b.adj() += vi.adj() * digamma_ab;
+    if constexpr (!is_constant<T1>::value) {


It would be nice to use the new is_autodiff_v everywhere you use !is_constant

SteveBronder · 2025-10-20T16:49:05Z

test/unit/math/prim/fun/beta_test.cpp

+  Eigen::VectorXd in1 = Eigen::VectorXd::Random(6).cwiseAbs();
+  Eigen::VectorXd in2 = Eigen::VectorXd::Random(6).cwiseAbs();


Why did this have to change?

andrjohns and others added 2 commits June 25, 2025 22:14

Use boost beta, simplify overloads

e5e2f13

[Jenkins] auto-formatting by clang-format version 10.0.0-4ubuntu1

544a5e8

andrjohns added 4 commits June 25, 2025 22:35

Update doxygen

2c81206

Expression fixes

87f0309

arena for ret

f691622

Merge branch 'develop' into simplify-beta

0cbdf91

SteveBronder requested changes Oct 20, 2025

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Use boost beta, simplify overloads #3212

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andrjohns commented Jun 25, 2025

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	if constexpr (!is_constant<Ta>::value) {
	if constexpr (is_autodiff_v<Ta>) {

	if constexpr (!is_constant<Tb>::value) {
	if constexpr (is_autodiff_v<Tb>) {

	const auto& adj_val = res_array.adj() * res_array.val();
	auto adj_val = res_array.adj() * res_array.val();

		Eigen::VectorXd in1 = Eigen::VectorXd::Random(6).cwiseAbs();
		Eigen::VectorXd in2 = Eigen::VectorXd::Random(6).cwiseAbs();

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andrjohns commented Jun 25, 2025

Summary

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