[Jenkins] auto-formatting by clang-format version 10.0.0-4ubuntu1

Author: stan-buildbot

stan/math/fwd/fun/hypergeometric_pFq.hpp

@@ -25,13 +25,11 @@ namespace math {
  * @param[in] z Scalar z argument
  * @return Generalized hypergeometric function
  */
-template <typename Ta, typename Tb, typename Tz,
-          typename FvarT = return_type_t<Ta, Tb, Tz>,
-          bool grad_a = is_autodiff_v<Ta>,
-          bool grad_b = is_autodiff_v<Tb>,
-          bool grad_z = is_autodiff_v<Tz>,
-          require_all_vector_t<Ta, Tb>* = nullptr,
-          require_fvar_t<FvarT>* = nullptr>
+template <
+    typename Ta, typename Tb, typename Tz,
+    typename FvarT = return_type_t<Ta, Tb, Tz>, bool grad_a = is_autodiff_v<Ta>,
+    bool grad_b = is_autodiff_v<Tb>, bool grad_z = is_autodiff_v<Tz>,
+    require_all_vector_t<Ta, Tb>* = nullptr, require_fvar_t<FvarT>* = nullptr>
 inline FvarT hypergeometric_pFq(Ta&& a, Tb&& b, Tz&& z) {
   auto&& a_ref = to_ref(as_column_vector_or_scalar(a));
   auto&& b_ref = to_ref(as_column_vector_or_scalar(b));

stan/math/opencl/kernel_generator/multi_result_kernel.hpp

@@ -77,13 +77,13 @@ struct multi_result_kernel_internal {
       int expression_rows = expression.rows();
       int expression_cols = expression.cols();
       if constexpr (is_colwise_reduction<T_current_expression>::value
-          && expression_cols == -1) {
+                    && expression_cols == -1) {
         expression_cols = n_cols;
         expression_rows = expression.thread_rows();
         expression_rows = internal::colwise_reduction_wgs_rows(
             expression_rows < 0 ? n_rows : expression_rows, expression_cols);
       } else if constexpr (is_reduction_2d<T_current_expression>::value
-                 && expression_cols == -1) {
+                           && expression_cols == -1) {
         expression_rows = internal::colwise_reduction_wgs_rows(n_rows, n_cols);
         if (expression_rows == 0) {
           expression_cols = 0;

stan/math/opencl/prim/bernoulli_logit_glm_lpmf.hpp

@@ -79,7 +79,8 @@ return_type_t<T_x_cl, T_alpha_cl, T_beta_cl> bernoulli_logit_glm_lpmf(
   if (N == 0) {
     return 0;
   }
-  if constexpr (!include_summand<propto, T_x_cl, T_alpha_cl, T_beta_cl>::value) {
+  if constexpr (!include_summand<propto, T_x_cl, T_alpha_cl,
+                                 T_beta_cl>::value) {
     return 0;
   }
 

stan/math/opencl/prim/bernoulli_logit_lpmf.hpp

@@ -72,8 +72,7 @@ return_type_t<T_prob_cl> bernoulli_logit_lpmf(const T_n_cl& n,
   matrix_cl<double> deriv_cl;
 
   results(logp_cl, deriv_cl, check_n_bounded, check_theta_not_nan)
-      = expressions(logp_expr,
-                    calc_if<is_autodiff_v<T_prob_cl>>(deriv_expr),
+      = expressions(logp_expr, calc_if<is_autodiff_v<T_prob_cl>>(deriv_expr),
                     n_bounded_expr, theta_not_nan_expr);
 
   T_partials_return logp = sum(from_matrix_cl(logp_cl));

stan/math/opencl/prim/bernoulli_lpmf.hpp

@@ -68,8 +68,7 @@ return_type_t<T_prob_cl> bernoulli_lpmf(const T_n_cl& n,
     matrix_cl<double> deriv_cl;
 
     results(logp_cl, deriv_cl, check_n_bounded, check_theta_bounded)
-        = expressions(logp_expr,
-                      calc_if<is_autodiff_v<T_prob_cl>>(deriv_expr),
+        = expressions(logp_expr, calc_if<is_autodiff_v<T_prob_cl>>(deriv_expr),
                       n_bounded_expr, theta_bounded_expr);
 
     logp = sum(from_matrix_cl(logp_cl));

stan/math/opencl/prim/beta_proportion_lpdf.hpp

@@ -103,8 +103,7 @@ return_type_t<T_y_cl, T_loc_cl, T_prec_cl> beta_proportion_lpdf(
   results(check_y_bounded, check_mu_bounded, check_kappa_positive_finite,
           logp_cl, y_deriv_cl, mu_deriv_cl, kappa_deriv_cl)
       = expressions(y_bounded_expr, mu_bounded_expr, kappa_positive_finite,
-                    logp_expr,
-                    calc_if<is_autodiff_v<T_y_cl>>(y_deriv_expr),
+                    logp_expr, calc_if<is_autodiff_v<T_y_cl>>(y_deriv_expr),
                     calc_if<is_autodiff_v<T_loc_cl>>(mu_deriv_expr),
                     calc_if<is_autodiff_v<T_prec_cl>>(kappa_deriv_expr));
 

stan/math/opencl/prim/binomial_logit_glm_lpmf.hpp

@@ -51,7 +51,8 @@ return_type_t<T_x_cl, T_alpha_cl, T_beta_cl> binomial_logit_glm_lpmf(
   if (N_instances == 0 || N_attributes == 0) {
     return 0;
   }
-  if constexpr (!include_summand<propto, T_x_cl, T_alpha_cl, T_beta_cl>::value) {
+  if constexpr (!include_summand<propto, T_x_cl, T_alpha_cl,
+                                 T_beta_cl>::value) {
     return 0;
   }
 

stan/math/opencl/prim/cauchy_cdf.hpp

@@ -83,11 +83,10 @@ return_type_t<T_y_cl, T_loc_cl, T_scale_cl> cauchy_cdf(
 
   results(check_y_not_nan, check_mu_finite, check_sigma_positive_finite,
           any_y_neg_inf_cl, P_cl, mu_deriv_cl, sigma_deriv_cl)
-      = expressions(
-          y_not_nan_expr, mu_finite_expr, sigma_positive_finite_expr,
-          any_y_neg_inf, P_expr,
-          calc_if<is_any_autodiff_v<T_y_cl, T_loc_cl>>(mu_deriv_tmp),
-          calc_if<is_autodiff_v<T_scale_cl>>(sigma_deriv_tmp));
+      = expressions(y_not_nan_expr, mu_finite_expr, sigma_positive_finite_expr,
+                    any_y_neg_inf, P_expr,
+                    calc_if<is_any_autodiff_v<T_y_cl, T_loc_cl>>(mu_deriv_tmp),
+                    calc_if<is_autodiff_v<T_scale_cl>>(sigma_deriv_tmp));
 
   if (from_matrix_cl(any_y_neg_inf_cl).maxCoeff()) {
     return 0.0;

stan/math/opencl/prim/cauchy_lccdf.hpp

@@ -80,8 +80,7 @@ return_type_t<T_y_cl, T_loc_cl, T_scale_cl> cauchy_lccdf(
   results(check_y_not_nan, check_mu_finite, check_sigma_positive_finite,
           ccdf_log_cl, y_deriv_cl, mu_deriv_cl, sigma_deriv_cl)
       = expressions(y_not_nan_expr, mu_finite_expr, sigma_positive_finite_expr,
-                    ccdf_log_expr,
-                    calc_if<is_autodiff_v<T_y_cl>>(-rep_deriv),
+                    ccdf_log_expr, calc_if<is_autodiff_v<T_y_cl>>(-rep_deriv),
                     calc_if<is_autodiff_v<T_loc_cl>>(rep_deriv),
                     calc_if<is_autodiff_v<T_scale_cl>>(sigma_deriv));
 

stan/math/opencl/prim/cauchy_lcdf.hpp

@@ -80,8 +80,7 @@ return_type_t<T_y_cl, T_loc_cl, T_scale_cl> cauchy_lcdf(
   results(check_y_not_nan, check_mu_finite, check_sigma_positive_finite,
           cdf_log_cl, mu_deriv_cl, sigma_deriv_cl)
       = expressions(y_not_nan_expr, mu_finite_expr, sigma_positive_finite_expr,
-                    cdf_log_expr,
-                    calc_if<is_autodiff_v<T_y_cl>>(rep_deriv),
+                    cdf_log_expr, calc_if<is_autodiff_v<T_y_cl>>(rep_deriv),
                     calc_if<is_autodiff_v<T_loc_cl>>(-rep_deriv),
                     calc_if<is_autodiff_v<T_scale_cl>>(sigma_deriv));