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gumbel_cdf.hpp
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1#ifndef STAN_MATH_OPENCL_PRIM_GUMBEL_CDF_HPP
2#define STAN_MATH_OPENCL_PRIM_GUMBEL_CDF_HPP
3#ifdef STAN_OPENCL
4
12
13namespace stan {
14namespace math {
15
29template <
30 typename T_y_cl, typename T_loc_cl, typename T_scale_cl,
32 T_scale_cl>* = nullptr,
33 require_any_not_stan_scalar_t<T_y_cl, T_loc_cl, T_scale_cl>* = nullptr>
35 const T_loc_cl& mu,
36 const T_scale_cl& beta) {
37 static constexpr const char* function = "gumbel_cdf(OpenCL)";
39 using std::isfinite;
40 using std::isnan;
41
42 check_consistent_sizes(function, "Random variable", y, "Location parameter",
43 mu, "Scale parameter", beta);
44 const size_t N = max_size(y, mu, beta);
45 if (N == 0) {
46 return 1.0;
47 }
48
49 const auto& y_col = as_column_vector_or_scalar(y);
50 const auto& mu_col = as_column_vector_or_scalar(mu);
51 const auto& beta_col = as_column_vector_or_scalar(beta);
52
53 const auto& y_val = value_of(y_col);
54 const auto& mu_val = value_of(mu_col);
55 const auto& beta_val = value_of(beta_col);
56
57 auto check_y_not_nan
58 = check_cl(function, "Random variable", y_val, "not NaN");
59 auto y_not_nan_expr = !isnan(y_val);
60 auto check_mu_finite
61 = check_cl(function, "Location parameter", mu_val, "finite");
62 auto mu_finite_expr = isfinite(mu_val);
63 auto check_beta_positive
64 = check_cl(function, "Scale parameter", beta_val, "positive");
65 auto beta_positive_expr = 0.0 < beta_val;
66
67 auto scaled_diff = elt_divide(y_val - mu_val, beta_val);
68 auto exp_m_scaled_diff = exp(-scaled_diff);
69 auto cdf_n = exp(-exp_m_scaled_diff);
70 auto cdf_expr = colwise_prod(cdf_n);
71 auto rep_deriv = elt_divide(exp(-scaled_diff - exp_m_scaled_diff),
72 elt_multiply(beta_val, cdf_n));
73
74 matrix_cl<double> cdf_cl;
75 matrix_cl<double> y_deriv_cl;
76 matrix_cl<double> mu_deriv_cl;
77 matrix_cl<double> beta_deriv_cl;
78
79 results(check_y_not_nan, check_mu_finite, check_beta_positive, cdf_cl,
80 mu_deriv_cl, beta_deriv_cl)
82 y_not_nan_expr, mu_finite_expr, beta_positive_expr, cdf_expr,
84 rep_deriv),
86
87 T_partials_return cdf = (from_matrix_cl(cdf_cl)).prod();
88
89 auto y_deriv = elt_multiply(cdf, mu_deriv_cl);
90 auto mu_deriv = -y_deriv;
91 auto beta_deriv
93 beta_deriv_cl);
94
95 results(y_deriv_cl, mu_deriv_cl, beta_deriv_cl)
99
100 auto ops_partials = make_partials_propagator(y_col, mu_col, beta_col);
101
103 partials<0>(ops_partials) = std::move(y_deriv_cl);
104 }
106 partials<1>(ops_partials) = std::move(mu_deriv_cl);
107 }
109 partials<2>(ops_partials) = std::move(beta_deriv_cl);
110 }
111 return ops_partials.build(cdf);
112}
113
114} // namespace math
115} // namespace stan
116#endif
117#endif
Represents an arithmetic matrix on the OpenCL device.
Definition matrix_cl.hpp:47
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.
Definition check_cl.hpp:219
results_cl< T_results... > results(T_results &&... results)
Deduces types for constructing results_cl object.
auto as_column_vector_or_scalar(T &&a)
as_column_vector_or_scalar of a kernel generator expression.
auto colwise_prod(T &&a)
Column wise product - reduction 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)
Definition calc_if.hpp:121
expressions_cl< T_expressions... > expressions(T_expressions &&... expressions)
Deduces types for constructing expressions_cl object.
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)
Returns the gumbel cumulative distribution function for the given location, and scale.
auto from_matrix_cl(const T &src)
Copies the source matrix that is stored on the OpenCL device to the destination Eigen matrix.
Definition copy.hpp:61
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.
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
value_type_t< T > prod(const T &m)
Calculates product of given kernel generator expression elements.
Definition prod.hpp:21
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition value_of.hpp:18
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.
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
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.
Definition beta.hpp:51
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
fvar< T > exp(const fvar< T > &x)
Definition exp.hpp:15
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.
Definition std_isnan.hpp:18
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Extends std::true_type when instantiated with zero or more template parameters, all of which extend t...