1#ifndef STAN_MATH_OPENCL_PRIM_NEG_BINOMIAL_LPMF_HPP 
    2#define STAN_MATH_OPENCL_PRIM_NEG_BINOMIAL_LPMF_HPP 
   34template <
bool propto, 
typename T_n_cl, 
typename T_shape_cl,
 
   35          typename T_inv_scale_cl,
 
   37              T_n_cl, T_shape_cl, T_inv_scale_cl>* = 
nullptr,
 
   39                                        T_inv_scale_cl>* = 
nullptr>
 
   41    const T_n_cl& n, 
const T_shape_cl& alpha, 
const T_inv_scale_cl& 
beta) {
 
   42  static constexpr const char* function = 
"neg_binomial_lpmf(OpenCL)";
 
   43  using T_partials_return
 
   49                         alpha, 
"Inverse scale parameter", 
beta);
 
   55                                 T_inv_scale_cl>::value) {
 
   62  const auto& alpha_val = 
value_of(alpha_col);
 
   63  const auto& beta_val = 
value_of(beta_col);
 
   65  auto check_n_nonnegative
 
   66      = 
check_cl(function, 
"Failures variable", n, 
"nonnegative");
 
   67  auto n_nonnegative = n >= 0;
 
   68  auto check_alpha_positive_finite
 
   69      = 
check_cl(function, 
"Shape parameter", alpha_val, 
"positive finite");
 
   70  auto alpha_positive_finite = 0 < alpha_val && 
isfinite(alpha_val);
 
   71  auto check_beta_positive_finite = 
check_cl(
 
   72      function, 
"Inverse scale parameter", beta_val, 
"positive finite");
 
   73  auto beta_positive_finite = 0 < beta_val && 
isfinite(beta_val);
 
   75  auto digamma_alpha = 
digamma(alpha_val);
 
   77  auto log1p_beta = 
log1p(beta_val);
 
   78  auto lambda_m_alpha_over_1p_beta
 
   89  auto alpha_deriv = 
digamma(alpha_val + n) - digamma_alpha - log1p_inv_beta;
 
   90  auto beta_deriv = lambda_m_alpha_over_1p_beta - 
elt_divide(n, beta_val + 1.0);
 
   96  results(check_n_nonnegative, check_alpha_positive_finite,
 
   97          check_beta_positive_finite, logp_cl, alpha_deriv_cl, beta_deriv_cl)
 
   98      = 
expressions(n_nonnegative, alpha_positive_finite, beta_positive_finite,
 
   99                    logp_expr, 
calc_if<is_autodiff_v<T_shape_cl>>(alpha_deriv),
 
  100                    calc_if<is_autodiff_v<T_inv_scale_cl>>(beta_deriv));
 
  106  if constexpr (is_autodiff_v<T_shape_cl>) {
 
  107    partials<0>(ops_partials) = std::move(alpha_deriv_cl);
 
  109  if constexpr (is_autodiff_v<T_inv_scale_cl>) {
 
  110    partials<1>(ops_partials) = std::move(beta_deriv_cl);
 
  112  return ops_partials.build(logp);
 
Represents an arithmetic matrix on the OpenCL device.
 
elt_multiply_< as_operation_cl_t< T_a >, as_operation_cl_t< T_b > > elt_multiply(T_a &&a, T_b &&b)
 
isfinite_< as_operation_cl_t< T > > isfinite(T &&a)
 
auto check_cl(const char *function, const char *var_name, T &&y, const char *must_be)
Constructs a check on opencl matrix or expression.
 
results_cl< T_results... > results(T_results &&... results)
Deduces types for constructing results_cl object.
 
binomial_coefficient_log_< as_operation_cl_t< T1 >, as_operation_cl_t< T2 > > binomial_coefficient_log(T1 &&a, T2 &&b)
 
auto as_column_vector_or_scalar(T &&a)
as_column_vector_or_scalar of a kernel generator expression.
 
elt_divide_< as_operation_cl_t< T_a >, as_operation_cl_t< T_b > > elt_divide(T_a &&a, T_b &&b)
 
calc_if_< true, as_operation_cl_t< T > > calc_if(T &&a)
 
auto colwise_sum(T &&a)
Column wise sum - reduction of a kernel generator expression.
 
expressions_cl< T_expressions... > expressions(T_expressions &&... expressions)
Deduces types for constructing expressions_cl object.
 
return_type_t< T_n_cl, T_shape_cl, T_inv_scale_cl > neg_binomial_lpmf(const T_n_cl &n, const T_shape_cl &alpha, const T_inv_scale_cl &beta)
The log of the negative binomial density for the specified scalars given the specified mean(s) and de...
 
auto from_matrix_cl(const T &src)
Copies the source matrix that is stored on the OpenCL device to the destination Eigen matrix.
 
require_all_t< is_prim_or_rev_kernel_expression< std::decay_t< Types > >... > require_all_prim_or_rev_kernel_expression_t
Require type satisfies is_prim_or_rev_kernel_expression.
 
require_any_not_t< is_stan_scalar< std::decay_t< Types > >... > require_any_not_stan_scalar_t
Require at least one of the types do not satisfy is_stan_scalar.
 
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
 
T value_of(const fvar< T > &v)
Return the value of the specified variable.
 
T1 static_select(T1 &&a, T2 &&b)
Returns one of the arguments that can be of different type, depending on the compile time condition.
 
void check_consistent_sizes(const char *)
Trivial no input case, this function is a no-op.
 
fvar< T > log1p(const fvar< T > &x)
 
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
 
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
 
fvar< T > beta(const fvar< T > &x1, const fvar< T > &x2)
Return fvar with the beta function applied to the specified arguments and its gradient.
 
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
 
fvar< T > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.
 
typename partials_return_type< Args... >::type partials_return_t
 
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
 
bool isnan(const stan::math::var &a)
Checks if the given number is NaN.
 
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...