gumbel_cdf.hpp

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#ifndef STAN_MATH_OPENCL_PRIM_GUMBEL_CDF_HPP
#define STAN_MATH_OPENCL_PRIM_GUMBEL_CDF_HPP
#ifdef STAN_OPENCL
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/elt_divide.hpp>
#include <stan/math/prim/fun/elt_multiply.hpp>
#include <stan/math/opencl/kernel_generator.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
 
namespace stan {
namespace math {
 
template <
    typename T_y_cl, typename T_loc_cl, typename T_scale_cl,
    require_all_prim_or_rev_kernel_expression_t<T_y_cl, T_loc_cl,
                                                T_scale_cl>* = nullptr,
    require_any_not_stan_scalar_t<T_y_cl, T_loc_cl, T_scale_cl>* = nullptr>
inline return_type_t<T_y_cl, T_loc_cl, T_scale_cl> gumbel_cdf(
    const T_y_cl& y, const T_loc_cl& mu, const T_scale_cl& beta) {
  static constexpr const char* function = "gumbel_cdf(OpenCL)";
  using T_partials_return = partials_return_t<T_y_cl, T_loc_cl, T_scale_cl>;
  using std::isfinite;
  using std::isnan;
 
  check_consistent_sizes(function, "Random variable", y, "Location parameter",
                         mu, "Scale parameter", beta);
  const size_t N = max_size(y, mu, beta);
  if (N == 0) {
    return 1.0;
  }
 
  const auto& y_col = as_column_vector_or_scalar(y);
  const auto& mu_col = as_column_vector_or_scalar(mu);
  const auto& beta_col = as_column_vector_or_scalar(beta);
 
  const auto& y_val = value_of(y_col);
  const auto& mu_val = value_of(mu_col);
  const auto& beta_val = value_of(beta_col);
 
  auto check_y_not_nan
      = check_cl(function, "Random variable", y_val, "not NaN");
  auto y_not_nan_expr = !isnan(y_val);
  auto check_mu_finite
      = check_cl(function, "Location parameter", mu_val, "finite");
  auto mu_finite_expr = isfinite(mu_val);
  auto check_beta_positive
      = check_cl(function, "Scale parameter", beta_val, "positive");
  auto beta_positive_expr = 0.0 < beta_val;
 
  auto scaled_diff = elt_divide(y_val - mu_val, beta_val);
  auto exp_m_scaled_diff = exp(-scaled_diff);
  auto cdf_n = exp(-exp_m_scaled_diff);
  auto cdf_expr = colwise_prod(cdf_n);
  auto rep_deriv = elt_divide(exp(-scaled_diff - exp_m_scaled_diff),
                              elt_multiply(beta_val, cdf_n));
 
  matrix_cl<double> cdf_cl;
  matrix_cl<double> y_deriv_cl;
  matrix_cl<double> mu_deriv_cl;
  matrix_cl<double> beta_deriv_cl;
 
  results(check_y_not_nan, check_mu_finite, check_beta_positive, cdf_cl,
          mu_deriv_cl, beta_deriv_cl)
      = expressions(
          y_not_nan_expr, mu_finite_expr, beta_positive_expr, cdf_expr,
          calc_if<is_any_autodiff_v<T_y_cl, T_loc_cl, T_scale_cl>>(rep_deriv),
          calc_if<is_autodiff_v<T_scale_cl>>(scaled_diff));
 
  T_partials_return cdf = (from_matrix_cl(cdf_cl)).prod();
 
  auto y_deriv = elt_multiply(cdf, mu_deriv_cl);
  auto mu_deriv = -y_deriv;
  auto beta_deriv = elt_multiply(
      static_select<is_constant_v<T_scale_cl>>(0, mu_deriv), beta_deriv_cl);
 
  results(y_deriv_cl, mu_deriv_cl, beta_deriv_cl)
      = expressions(calc_if<is_autodiff_v<T_y_cl>>(y_deriv),
                    calc_if<is_autodiff_v<T_loc_cl>>(mu_deriv),
                    calc_if<is_autodiff_v<T_scale_cl>>(beta_deriv));
 
  auto ops_partials = make_partials_propagator(y_col, mu_col, beta_col);
 
  if constexpr (is_autodiff_v<T_y_cl>) {
    partials<0>(ops_partials) = std::move(y_deriv_cl);
  }
  if constexpr (is_autodiff_v<T_loc_cl>) {
    partials<1>(ops_partials) = std::move(mu_deriv_cl);
  }
  if constexpr (is_autodiff_v<T_scale_cl>) {
    partials<2>(ops_partials) = std::move(beta_deriv_cl);
  }
  return ops_partials.build(cdf);
}
 
}  // namespace math
}  // namespace stan
#endif
#endif