bernoulli_lcdf.hpp

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#ifndef STAN_MATH_OPENCL_PRIM_BERNOULLI_LCDF_HPP
#define STAN_MATH_OPENCL_PRIM_BERNOULLI_LCDF_HPP
#ifdef STAN_OPENCL
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/opencl/kernel_generator.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/elt_divide.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
 
namespace stan {
namespace math {
 
template <
    typename T_n_cl, typename T_prob_cl,
    require_all_prim_or_rev_kernel_expression_t<T_n_cl, T_prob_cl>* = nullptr,
    require_any_not_stan_scalar_t<T_n_cl, T_prob_cl>* = nullptr>
return_type_t<T_prob_cl> bernoulli_lcdf(const T_n_cl& n,
                                        const T_prob_cl& theta) {
  static constexpr const char* function = "bernoulli_lcdf(OpenCL)";
  using T_partials_return = partials_return_t<T_prob_cl>;
  using std::isnan;
  constexpr bool is_n_vector = !is_stan_scalar<T_n_cl>::value;
 
  check_consistent_sizes(function, "Random variable", n,
                         "Probability parameter", theta);
  const size_t N = is_n_vector ? math::size(n) : math::size(theta);
  if (N == 0) {
    return 0.0;
  }
 
  const auto& theta_col = as_column_vector_or_scalar(theta);
  const auto& theta_val = value_of(theta_col);
 
  auto check_theta_bounded = check_cl(function, "Probability parameter",
                                      theta_val, "in the interval [0, 1]");
  auto theta_bounded_expr = 0.0 <= theta_val && theta_val <= 1.0;
 
  auto any_n_negative = colwise_max(cast<char>(n < 0));
  auto Pi = 1.0 - theta_val;
  auto cond = n >= 1;
  auto P_expr = colwise_sum(select(cond, 0.0, log(Pi)));
  auto deriv = select(cond, 0.0, elt_divide(-1.0, Pi));
 
  matrix_cl<char> any_n_negative_cl;
  matrix_cl<double> P_cl;
  matrix_cl<double> deriv_cl;
 
  results(check_theta_bounded, any_n_negative_cl, P_cl, deriv_cl)
      = expressions(theta_bounded_expr, any_n_negative, P_expr,
                    calc_if<(!is_constant_all<T_prob_cl>::value)>(deriv));
 
  if (from_matrix_cl(any_n_negative_cl).maxCoeff()) {
    return NEGATIVE_INFTY;
  }
 
  T_partials_return P = from_matrix_cl(P_cl).sum();
  auto ops_partials = make_partials_propagator(theta_col);
 
  if (!is_constant_all<T_prob_cl>::value) {
    partials<0>(ops_partials) = std::move(deriv_cl);
  }
 
  return ops_partials.build(P);
}
 
}  // namespace math
}  // namespace stan
#endif
#endif