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

Author: stan-buildbot

stan/math/opencl/prim/multinomial_logit_glm_lpmf.hpp

@@ -53,8 +53,8 @@ inline return_type_t<T_x, T_alpha, T_beta> multinomial_logit_glm_lpmf(
     return 0;
   }
   return multinomial_logit_glm_lpmf<propto>(
-      matrix_cl<int>(as_array_or_scalar(y)), std::forward<T_x>(x), std::forward<T_alpha>(alpha),
-      std::forward<T_beta>(beta));
+      matrix_cl<int>(as_array_or_scalar(y)), std::forward<T_x>(x),
+      std::forward<T_alpha>(alpha), std::forward<T_beta>(beta));
 }
 
 template <bool propto = false, typename T_y, typename T_x, typename T_alpha,

stan/math/prim/prob/multinomial_logit_glm_lpmf.hpp

@@ -82,7 +82,8 @@ template <bool propto, typename T_x, typename T_alpha, typename T_beta,
           require_matrix_t<T_x>* = nullptr,
           require_matrix_t<T_alpha>* = nullptr,
           require_matrix_t<T_beta>* = nullptr,
-          require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_x, T_alpha, T_beta>* = nullptr>
+          require_all_not_nonscalar_prim_or_rev_kernel_expression_t<
+              T_x, T_alpha, T_beta>* = nullptr>
 inline return_type_t<T_x, T_alpha, T_beta> multinomial_logit_glm_lpmf(
     const std::vector<std::vector<int>>& y, T_x&& x, T_alpha&& alpha,
     T_beta&& beta) {
@@ -138,8 +139,7 @@ inline return_type_t<T_x, T_alpha, T_beta> multinomial_logit_glm_lpmf(
   }
 
   // Row-max shift for numerical stability; cancels in log-softmax.
-  const auto exp_eta
-      = exp((eta.colwise() - eta.rowwise().maxCoeff()));
+  const auto exp_eta = exp((eta.colwise() - eta.rowwise().maxCoeff()));
   const Array<eta_ret_t, Dynamic, Dynamic> softmax_mat
       = exp_eta.colwise() / exp_eta.rowwise().sum();
 
@@ -167,7 +167,8 @@ inline return_type_t<T_x, T_alpha, T_beta> multinomial_logit_glm_lpmf(
               .eval();
 
     if constexpr (is_autodiff_v<T_x>) {
-      partials<0>(ops_partials) = multiply(delta.matrix(), beta_val.transpose());
+      partials<0>(ops_partials)
+          = multiply(delta.matrix(), beta_val.transpose());
     }
     if constexpr (is_autodiff_v<T_beta>) {
       partials<2>(ops_partials) = multiply(x_val.transpose(), delta.matrix());
@@ -184,7 +185,8 @@ inline return_type_t<T_x, T_alpha, T_beta> multinomial_logit_glm_lpmf(
 }
 
 template <typename T_x, typename T_alpha, typename T_beta,
-          require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_x, T_alpha, T_beta>* = nullptr>
+          require_all_not_nonscalar_prim_or_rev_kernel_expression_t<
+              T_x, T_alpha, T_beta>* = nullptr>
 inline return_type_t<T_x, T_alpha, T_beta> multinomial_logit_glm_lpmf(
     const std::vector<std::vector<int>>& y, T_x&& x, T_alpha&& alpha,
     T_beta&& beta) {

test/unit/math/opencl/rev/multinomial_logit_glm_lpmf_test.cpp

@@ -328,9 +328,8 @@ TEST(ProbDistributionsMultinomialLogitGLM, opencl_matrix_cl_y_broadcast_alpha) {
   };
   stan::math::test::compare_cpu_opencl_prim_rev_separate(f_cpu, f_cl, x, alpha,
                                                          beta);
-  stan::math::test::compare_cpu_opencl_prim_rev_separate(f_cpu_propto,
-                                                         f_cl_propto, x, alpha,
-                                                         beta);
+  stan::math::test::compare_cpu_opencl_prim_rev_separate(
+      f_cpu_propto, f_cl_propto, x, alpha, beta);
 }
 
 TEST(ProbDistributionsMultinomialLogitGLM, opencl_matrix_cl_y_matrix_alpha) {
@@ -358,9 +357,8 @@ TEST(ProbDistributionsMultinomialLogitGLM, opencl_matrix_cl_y_matrix_alpha) {
   };
   stan::math::test::compare_cpu_opencl_prim_rev_separate(f_cpu, f_cl, x, alpha,
                                                          beta);
-  stan::math::test::compare_cpu_opencl_prim_rev_separate(f_cpu_propto,
-                                                         f_cl_propto, x, alpha,
-                                                         beta);
+  stan::math::test::compare_cpu_opencl_prim_rev_separate(
+      f_cpu_propto, f_cl_propto, x, alpha, beta);
 }
 
 TEST(ProbDistributionsMultinomialLogitGLM, opencl_matrix_cl_y_large) {