Stan Math Library  4.9.0 Automatic Differentiation
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normal_lpdf.hpp
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1#ifndef STAN_MATH_OPENCL_PRIM_NORMAL_LPDF_HPP
2#define STAN_MATH_OPENCL_PRIM_NORMAL_LPDF_HPP
3#ifdef STAN_OPENCL
4
11
12
13namespace stan {
14namespace math {
15
35template <
36 bool propto, typename T_y_cl, typename T_loc_cl, typename T_scale_cl,
38 T_scale_cl>* = nullptr,
39 require_any_not_stan_scalar_t<T_y_cl, T_loc_cl, T_scale_cl>* = nullptr>
41 const T_y_cl& y, const T_loc_cl& mu, const T_scale_cl& sigma) {
42 static constexpr const char* function = "normal_lpdf(OpenCL)";
44 using std::isfinite;
45 using std::isnan;
46
47 check_consistent_sizes(function, "Random variable", y, "Location parameter",
48 mu, "Scale parameter", sigma);
49 const size_t N = max_size(y, mu, sigma);
50 if (N == 0) {
51 return 0.0;
52 }
54 return 0.0;
55 }
56
57 const auto& y_col = as_column_vector_or_scalar(y);
58 const auto& mu_col = as_column_vector_or_scalar(mu);
59 const auto& sigma_col = as_column_vector_or_scalar(sigma);
60
61 const auto& y_val = value_of(y_col);
62 const auto& mu_val = value_of(mu_col);
63 const auto& sigma_val = value_of(sigma_col);
64
65 auto check_y_not_nan
66 = check_cl(function, "Random variable", y_val, "not NaN");
67 auto y_not_nan = !isnan(y_val);
68 auto check_mu_finite
69 = check_cl(function, "Location parameter", mu_val, "finite");
70 auto mu_finite = isfinite(mu_val);
71 auto check_sigma_positive
72 = check_cl(function, "Scale parameter", sigma_val, "positive");
73 auto sigma_positive = 0 < sigma_val;
74
75 auto inv_sigma = elt_divide(1., sigma_val);
76 auto y_scaled = elt_multiply((y_val - mu_val), inv_sigma);
77 auto y_scaled_sq = elt_multiply(y_scaled, y_scaled);
78
79 auto logp1 = -0.5 * y_scaled_sq;
80 auto logp_expr
82 logp1 - log(sigma_val), logp1));
83
84 auto scaled_diff = elt_multiply(inv_sigma, y_scaled);
85 auto sigma_deriv = elt_multiply(inv_sigma, y_scaled_sq) - inv_sigma;
86
87 matrix_cl<double> logp_cl;
88 matrix_cl<double> mu_deriv_cl;
89 matrix_cl<double> y_deriv_cl;
90 matrix_cl<double> sigma_deriv_cl;
91
92 results(check_y_not_nan, check_mu_finite, check_sigma_positive, logp_cl,
93 y_deriv_cl, mu_deriv_cl, sigma_deriv_cl)
94 = expressions(y_not_nan, mu_finite, sigma_positive, logp_expr,
95 calc_if<!is_constant<T_y_cl>::value>(-scaled_diff),
98
99 T_partials_return logp = sum(from_matrix_cl(logp_cl));
100
102 logp += NEG_LOG_SQRT_TWO_PI * N;
103 }
104
105 auto ops_partials = make_partials_propagator(y_col, mu_col, sigma_col);
106
108 partials<0>(ops_partials) = std::move(y_deriv_cl);
109 }
111 partials<1>(ops_partials) = std::move(mu_deriv_cl);
112 }
114 partials<2>(ops_partials) = std::move(sigma_deriv_cl);
115 }
116 return ops_partials.build(logp);
117}
118
119} // namespace math
120} // namespace stan
121#endif
122#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.
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_loc_cl, T_scale_cl > normal_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &sigma)
The log of the normal density for the specified scalar(s) given the specified mean(s) and deviation(s...
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.
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
const double NEG_LOG_SQRT_TWO_PI
The value of minus the natural logarithm of the square root of , .
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 > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:22
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 ...
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 ...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...