Summary:
I cannot connect to Stan from R, and therefore I cannot use the packages rstan or brms, for instance. The message error is always:
Error in compileCode(f, code, language = language, verbose = verbose) :
Error in sink(type = “output”) : invalid connection
with not a single line afterwards [seems to differ from other reported issues].
Description:
I try to run brms as usual a few days ago and then realized it was not working. I already had some issues in the past, but I somehow managed to deal with it. It seems like updating R is always an issue for rstan. I do not really get why. Currently, I can run brms on my personal laptop and I have issues with my work laptop. I generally keep both of them as updated as possible with regards to R, RStudio or R packages.
I have no clue what is the problem this time. I spent days trying to understand that. I went through many pages on the web for help [for instance here, here, here, or even here].
The solutions often appear to be somehow similar, but none of them work in my case.
As I am afraid that brms also stops working on my personal PC, I do not dare to look into the installation configuration on my personal PC. But I typically have very similar configurations on both PCs.
Reproducible Steps:
So I tried to uninstall all installations of R, RStudio, RTools, as well as deleting all associated folders, clearing all associated paths in the
System environment variables of my PC, but nothing has helped: always the same issue.
Current Output:
library("rstan") # observe startup messages
Loading required package: StanHeaders
Loading required package: ggplot2
rstan (Version 2.21.8, GitRev: 2e1f913d3ca3)
For execution on a local, multicore CPU with excess RAM we recommend calling
options(mc.cores = parallel::detectCores()).
To avoid recompilation of unchanged Stan programs, we recommend calling
rstan_options(auto_write = TRUE)
Do not specify '-march=native' in 'LOCAL_CPPFLAGS' or a Makevars file
> example(stan_model, package = "rstan", run.dontrun = TRUE)
stn_md> stancode <- 'data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}'
stn_md> mod <- stan_model(model_code = stancode, verbose = TRUE)
TRANSLATING MODEL '73fc79f8b1915e8208c736914c86d1a1' FROM Stan CODE TO C++ CODE NOW.
successful in parsing the Stan model '73fc79f8b1915e8208c736914c86d1a1'.
COMPILING THE C++ CODE FOR MODEL '73fc79f8b1915e8208c736914c86d1a1' NOW.
OS: x86_64, mingw32; rstan: 2.21.8; Rcpp: 1.0.11; inline: 0.3.19
>> setting environment variables:
LOCAL_LIBS = "C:/Program Files/R/R-4.3.1/library/rstan/lib/x64/libStanServices.a" -L"C:/Program Files/R/R-4.3.1/library/StanHeaders/libs/x64" -lStanHeaders -L"C:/Program Files/R/R-4.3.1/library/RcppParallel/lib/x64" -ltbb
PKG_CPPFLAGS = -I"C:/Program Files/R/R-4.3.1/library/Rcpp/include/" -I"C:/Program Files/R/R-4.3.1/library/RcppEigen/include/" -I"C:/Program Files/R/R-4.3.1/library/RcppEigen/include/unsupported" -I"C:/Program Files/R/R-4.3.1/library/BH/include" -I"C:/Program Files/R/R-4.3.1/library/StanHeaders/include/src/" -I"C:/Program Files/R/R-4.3.1/library/StanHeaders/include/" -I"C:/Program Files/R/R-4.3.1/library/RcppParallel/include/" -I"C:/Program Files/R/R-4.3.1/library/rstan/include" -DEIGEN_NO_DEBUG -DBOOST_DISABLE_ASSERTS -DBOOST_PENDING_INTEGER_LOG2_HPP -DSTAN_THREADS -DBOOST_NO_AUTO_PTR -include "C:/Program Files/R/R-4.3.1/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp" -std=c++1y
>> Program source :
1 :
2 : // includes from the plugin
3 : // [[Rcpp::plugins(cpp14)]]
4 :
5 :
6 : // user includes
7 : #include <Rcpp.h>
8 : #include <rstan/io/rlist_ref_var_context.hpp>
9 : #include <rstan/io/r_ostream.hpp>
10 : #include <rstan/stan_args.hpp>
11 : #include <boost/integer/integer_log2.hpp>
12 : // Code generated by Stan version 2.21.0
13 :
14 : #include <stan/model/model_header.hpp>
15 :
16 : namespace model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1_namespace {
17 :
18 : using std::istream;
19 : using std::string;
20 : using std::stringstream;
21 : using std::vector;
22 : using stan::io::dump;
23 : using stan::math::lgamma;
24 : using stan::model::prob_grad;
25 : using namespace stan::math;
26 :
27 : static int current_statement_begin__;
28 :
29 : stan::io::program_reader prog_reader__() {
30 : stan::io::program_reader reader;
31 : reader.add_event(0, 0, "start", "model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1");
32 : reader.add_event(3, 1, "end", "model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1");
33 : return reader;
34 : }
35 :
36 : class model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1
37 : : public stan::model::model_base_crtp<model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1> {
38 : private:
39 : double y_mean;
40 : public:
41 : model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1(rstan::io::rlist_ref_var_context& context__,
42 : std::ostream* pstream__ = 0)
43 : : model_base_crtp(0) {
44 : ctor_body(context__, 0, pstream__);
45 : }
46 :
47 : model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1(stan::io::var_context& context__,
48 : unsigned int random_seed__,
49 : std::ostream* pstream__ = 0)
50 : : model_base_crtp(0) {
51 : ctor_body(context__, random_seed__, pstream__);
52 : }
53 :
54 : void ctor_body(stan::io::var_context& context__,
55 : unsigned int random_seed__,
56 : std::ostream* pstream__) {
57 : typedef double local_scalar_t__;
58 :
59 : boost::ecuyer1988 base_rng__ =
60 : stan::services::util::create_rng(random_seed__, 0);
61 : (void) base_rng__; // suppress unused var warning
62 :
63 : current_statement_begin__ = -1;
64 :
65 : static const char* function__ = "model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1_namespace::model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1";
66 : (void) function__; // dummy to suppress unused var warning
67 : size_t pos__;
68 : (void) pos__; // dummy to suppress unused var warning
69 : std::vector<int> vals_i__;
70 : std::vector<double> vals_r__;
71 : local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
72 : (void) DUMMY_VAR__; // suppress unused var warning
73 :
74 : try {
75 : // initialize data block variables from context__
76 : current_statement_begin__ = 1;
77 : context__.validate_dims("data initialization", "y_mean", "double", context__.to_vec());
78 : y_mean = double(0);
79 : vals_r__ = context__.vals_r("y_mean");
80 : pos__ = 0;
81 : y_mean = vals_r__[pos__++];
82 :
83 :
84 : // initialize transformed data variables
85 : // execute transformed data statements
86 :
87 : // validate transformed data
88 :
89 : // validate, set parameter ranges
90 : num_params_r__ = 0U;
91 : param_ranges_i__.clear();
92 : current_statement_begin__ = 1;
93 : num_params_r__ += 1;
94 : } catch (const std::exception& e) {
95 : stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
96 : // Next line prevents compiler griping about no return
97 : throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
98 : }
99 : }
100 :
101 : ~model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1() { }
102 :
103 :
104 : void transform_inits(const stan::io::var_context& context__,
105 : std::vector<int>& params_i__,
106 : std::vector<double>& params_r__,
107 : std::ostream* pstream__) const {
108 : typedef double local_scalar_t__;
109 : stan::io::writer<double> writer__(params_r__, params_i__);
110 : size_t pos__;
111 : (void) pos__; // dummy call to supress warning
112 : std::vector<double> vals_r__;
113 : std::vector<int> vals_i__;
114 :
115 : current_statement_begin__ = 1;
116 : if (!(context__.contains_r("y")))
117 : stan::lang::rethrow_located(std::runtime_error(std::string("Variable y missing")), current_statement_begin__, prog_reader__());
118 : vals_r__ = context__.vals_r("y");
119 : pos__ = 0U;
120 : context__.validate_dims("parameter initialization", "y", "double", context__.to_vec());
121 : double y(0);
122 : y = vals_r__[pos__++];
123 : try {
124 : writer__.scalar_unconstrain(y);
125 : } catch (const std::exception& e) {
126 : stan::lang::rethrow_located(std::runtime_error(std::string("Error transforming variable y: ") + e.what()), current_statement_begin__, prog_reader__());
127 : }
128 :
129 : params_r__ = writer__.data_r();
130 : params_i__ = writer__.data_i();
131 : }
132 :
133 : void transform_inits(const stan::io::var_context& context,
134 : Eigen::Matrix<double, Eigen::Dynamic, 1>& params_r,
135 : std::ostream* pstream__) const {
136 : std::vector<double> params_r_vec;
137 : std::vector<int> params_i_vec;
138 : transform_inits(context, params_i_vec, params_r_vec, pstream__);
139 : params_r.resize(params_r_vec.size());
140 : for (int i = 0; i < params_r.size(); ++i)
141 : params_r(i) = params_r_vec[i];
142 : }
143 :
144 :
145 : template <bool propto__, bool jacobian__, typename T__>
146 : T__ log_prob(std::vector<T__>& params_r__,
147 : std::vector<int>& params_i__,
148 : std::ostream* pstream__ = 0) const {
149 :
150 : typedef T__ local_scalar_t__;
151 :
152 : local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
153 : (void) DUMMY_VAR__; // dummy to suppress unused var warning
154 :
155 : T__ lp__(0.0);
156 : stan::math::accumulator<T__> lp_accum__;
157 : try {
158 : stan::io::reader<local_scalar_t__> in__(params_r__, params_i__);
159 :
160 : // model parameters
161 : current_statement_begin__ = 1;
162 : local_scalar_t__ y;
163 : (void) y; // dummy to suppress unused var warning
164 : if (jacobian__)
165 : y = in__.scalar_constrain(lp__);
166 : else
167 : y = in__.scalar_constrain();
168 :
169 : // model body
170 :
171 : current_statement_begin__ = 1;
172 : lp_accum__.add(normal_log<propto__>(y, y_mean, 1));
173 :
174 : } catch (const std::exception& e) {
175 : stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
176 : // Next line prevents compiler griping about no return
177 : throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
178 : }
179 :
180 : lp_accum__.add(lp__);
181 : return lp_accum__.sum();
182 :
183 : } // log_prob()
184 :
185 : template <bool propto, bool jacobian, typename T_>
186 : T_ log_prob(Eigen::Matrix<T_,Eigen::Dynamic,1>& params_r,
187 : std::ostream* pstream = 0) const {
188 : std::vector<T_> vec_params_r;
189 : vec_params_r.reserve(params_r.size());
190 : for (int i = 0; i < params_r.size(); ++i)
191 : vec_params_r.push_back(params_r(i));
192 : std::vector<int> vec_params_i;
193 : return log_prob<propto,jacobian,T_>(vec_params_r, vec_params_i, pstream);
194 : }
195 :
196 :
197 : void get_param_names(std::vector<std::string>& names__) const {
198 : names__.resize(0);
199 : names__.push_back("y");
200 : }
201 :
202 :
203 : void get_dims(std::vector<std::vector<size_t> >& dimss__) const {
204 : dimss__.resize(0);
205 : std::vector<size_t> dims__;
206 : dims__.resize(0);
207 : dimss__.push_back(dims__);
208 : }
209 :
210 : template <typename RNG>
211 : void write_array(RNG& base_rng__,
212 : std::vector<double>& params_r__,
213 : std::vector<int>& params_i__,
214 : std::vector<double>& vars__,
215 : bool include_tparams__ = true,
216 : bool include_gqs__ = true,
217 : std::ostream* pstream__ = 0) const {
218 : typedef double local_scalar_t__;
219 :
220 : vars__.resize(0);
221 : stan::io::reader<local_scalar_t__> in__(params_r__, params_i__);
222 : static const char* function__ = "model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1_namespace::write_array";
223 : (void) function__; // dummy to suppress unused var warning
224 :
225 : // read-transform, write parameters
226 : double y = in__.scalar_constrain();
227 : vars__.push_back(y);
228 :
229 : double lp__ = 0.0;
230 : (void) lp__; // dummy to suppress unused var warning
231 : stan::math::accumulator<double> lp_accum__;
232 :
233 : local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
234 : (void) DUMMY_VAR__; // suppress unused var warning
235 :
236 : if (!include_tparams__ && !include_gqs__) return;
237 :
238 : try {
239 : if (!include_gqs__ && !include_tparams__) return;
240 : if (!include_gqs__) return;
241 : } catch (const std::exception& e) {
242 : stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
243 : // Next line prevents compiler griping about no return
244 : throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
245 : }
246 : }
247 :
248 : template <typename RNG>
249 : void write_array(RNG& base_rng,
250 : Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
251 : Eigen::Matrix<double,Eigen::Dynamic,1>& vars,
252 : bool include_tparams = true,
253 : bool include_gqs = true,
254 : std::ostream* pstream = 0) const {
255 : std::vector<double> params_r_vec(params_r.size());
256 : for (int i = 0; i < params_r.size(); ++i)
257 : params_r_vec[i] = params_r(i);
258 : std::vector<double> vars_vec;
259 : std::vector<int> params_i_vec;
260 : write_array(base_rng, params_r_vec, params_i_vec, vars_vec, include_tparams, include_gqs, pstream);
261 : vars.resize(vars_vec.size());
262 : for (int i = 0; i < vars.size(); ++i)
263 : vars(i) = vars_vec[i];
264 : }
265 :
266 : std::string model_name() const {
267 : return "model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1";
268 : }
269 :
270 :
271 : void constrained_param_names(std::vector<std::string>& param_names__,
272 : bool include_tparams__ = true,
273 : bool include_gqs__ = true) const {
274 : std::stringstream param_name_stream__;
275 : param_name_stream__.str(std::string());
276 : param_name_stream__ << "y";
277 : param_names__.push_back(param_name_stream__.str());
278 :
279 : if (!include_gqs__ && !include_tparams__) return;
280 :
281 : if (include_tparams__) {
282 : }
283 :
284 : if (!include_gqs__) return;
285 : }
286 :
287 :
288 : void unconstrained_param_names(std::vector<std::string>& param_names__,
289 : bool include_tparams__ = true,
290 : bool include_gqs__ = true) const {
291 : std::stringstream param_name_stream__;
292 : param_name_stream__.str(std::string());
293 : param_name_stream__ << "y";
294 : param_names__.push_back(param_name_stream__.str());
295 :
296 : if (!include_gqs__ && !include_tparams__) return;
297 :
298 : if (include_tparams__) {
299 : }
300 :
301 : if (!include_gqs__) return;
302 : }
303 :
304 : }; // model
305 :
306 : } // namespace
307 :
308 : typedef model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1_namespace::model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1 stan_model;
309 :
310 : #ifndef USING_R
311 :
312 : stan::model::model_base& new_model(
313 : stan::io::var_context& data_context,
314 : unsigned int seed,
315 : std::ostream* msg_stream) {
316 : stan_model* m = new stan_model(data_context, seed, msg_stream);
317 : return *m;
318 : }
319 :
320 : #endif
321 :
322 :
323 :
324 : #include <rstan_next/stan_fit.hpp>
325 :
326 : struct stan_model_holder {
327 : stan_model_holder(rstan::io::rlist_ref_var_context rcontext,
328 : unsigned int random_seed)
329 : : rcontext_(rcontext), random_seed_(random_seed)
330 : {
331 : }
332 :
333 : //stan::math::ChainableStack ad_stack;
334 : rstan::io::rlist_ref_var_context rcontext_;
335 : unsigned int random_seed_;
336 : };
337 :
338 : Rcpp::XPtr<stan::model::model_base> model_ptr(stan_model_holder* smh) {
339 : Rcpp::XPtr<stan::model::model_base> model_instance(new stan_model(smh->rcontext_, smh->random_seed_), true);
340 : return model_instance;
341 : }
342 :
343 : Rcpp::XPtr<rstan::stan_fit_base> fit_ptr(stan_model_holder* smh) {
344 : return Rcpp::XPtr<rstan::stan_fit_base>(new rstan::stan_fit(model_ptr(smh), smh->random_seed_), true);
345 : }
346 :
347 : std::string model_name(stan_model_holder* smh) {
348 : return model_ptr(smh).get()->model_name();
349 : }
350 :
351 : RCPP_MODULE(stan_fit4model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1_mod){
352 : Rcpp::class_<stan_model_holder>("stan_fit4model16fc5fe3736f_73fc79f8b1915e8208c736914c86d1a1")
353 : .constructor<rstan::io::rlist_ref_var_context, unsigned int>()
354 : .method("model_ptr", &model_ptr)
355 : .method("fit_ptr", &fit_ptr)
356 : .method("model_name", &model_name)
357 : ;
358 : }
359 :
360 :
361 : // declarations
362 : extern "C" {
363 : SEXP file16fc31a21df9( ) ;
364 : }
365 :
366 : // definition
367 : SEXP file16fc31a21df9() {
368 : return Rcpp::wrap("73fc79f8b1915e8208c736914c86d1a1");
369 : }
ERROR(s) during compilation: source code errors or compiler configuration errors!
***[too long to be printed here]***
Compilation ERROR, function(s)/method(s) not created!
Error in compileCode(f, code, language = language, verbose = verbose) :
To be more specific with brms:
Compiling Stan program...
Error in compileCode(f, code, language = language, verbose = verbose) :
Error in sink(type = “output”) : invalid connection
Expected Output:
Compiling Stan program...
Start sampling
SAMPLING FOR MODEL...
brms Version:
brms_2.19.0
RStan Version:
rstan_2.21.8
StanHeaders Version:
StanHeaders_2.26.27
Rcpp Version:
Rcpp_1.0.11
R Version:
R version 4.3.1 (2023-06-16 ucrt)
Operating System:
Windows 10