Automatic Differentiation
 
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rayleigh_lpdf.hpp
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1#ifndef STAN_MATH_OPENCL_PRIM_RAYLEIGH_LPDF_HPP
2#define STAN_MATH_OPENCL_PRIM_RAYLEIGH_LPDF_HPP
3#ifdef STAN_OPENCL
4
11
12namespace stan {
13namespace math {
14
27template <
28 bool propto, typename T_y_cl, typename T_scale_cl,
29 require_all_prim_or_rev_kernel_expression_t<T_y_cl, T_scale_cl>* = nullptr,
30 require_any_not_stan_scalar_t<T_y_cl, T_scale_cl>* = nullptr>
32 const T_scale_cl& sigma) {
33 static constexpr const char* function = "rayleigh_lpdf(OpenCL)";
34 using T_partials_return = partials_return_t<T_y_cl, T_scale_cl>;
35
36 check_consistent_sizes(function, "Random variable", y, "Scale parameter",
37 sigma);
38 const size_t N = max_size(y, sigma);
39 if (N == 0) {
40 return 0.0;
41 }
43 return 0.0;
44 }
45
46 const auto& y_col = as_column_vector_or_scalar(y);
47 const auto& sigma_col = as_column_vector_or_scalar(sigma);
48
49 const auto& y_val = value_of(y_col);
50 const auto& sigma_val = value_of(sigma_col);
51
52 auto ops_partials = make_partials_propagator(y_col, sigma_col);
53
54 auto check_y_positive
55 = check_cl(function, "Random variable", y_val, "positive");
56 auto y_positive = y_val > 0;
57 auto check_sigma_positive
58 = check_cl(function, "Scale parameter", sigma_val, "positive");
59 auto sigma_positive = sigma_val > 0;
60
61 auto inv_sigma = elt_divide(1.0, sigma_val);
62 auto y_over_sigma = elt_divide(y_val, sigma_val);
63
64 auto logp1 = -0.5 * elt_multiply(y_over_sigma, y_over_sigma);
65 auto logp2 = static_select<include_summand<propto, T_scale_cl>::value>(
66 logp1 - 2.0 * log(sigma_val), logp1);
67 auto logp_expr
69 logp2 + log(y_val), logp2));
70
71 auto scaled_diff = elt_multiply(inv_sigma, y_over_sigma);
72 auto y_deriv_expr = elt_divide(1.0, y_val) - scaled_diff;
73 auto sigma_deriv_expr
74 = elt_multiply(y_over_sigma, scaled_diff) - 2.0 * inv_sigma;
75
76 matrix_cl<double> logp_cl;
77 matrix_cl<double> y_deriv_cl;
78 matrix_cl<double> sigma_deriv_cl;
79
80 results(check_y_positive, check_sigma_positive, logp_cl, y_deriv_cl,
81 sigma_deriv_cl)
82 = expressions(y_positive, sigma_positive, logp_expr,
83 calc_if<!is_constant<T_y_cl>::value>(y_deriv_expr),
84 calc_if<!is_constant<T_scale_cl>::value>(sigma_deriv_expr));
85
86 T_partials_return logp = sum(from_matrix_cl(logp_cl));
87
89 partials<0>(ops_partials) = std::move(y_deriv_cl);
90 }
92 partials<1>(ops_partials) = std::move(sigma_deriv_cl);
93 }
94
95 return ops_partials.build(logp);
96}
97
98} // namespace math
99} // namespace stan
100#endif
101#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)
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.
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
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_y_cl, T_scale_cl > rayleigh_lpdf(const T_y_cl &y, const T_scale_cl &sigma)
The log of an Rayleigh density for y with the specified scale parameter.
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
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.
Definition value_of.hpp:18
fvar< T > log(const fvar< T > &x)
Definition log.hpp:15
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.
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:23
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
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 ...
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...