Dear all,
I’m trying to install Rstan on Rstudio workbench built on top of a GCP GKE cluster. The error I’m getting is
stn_md> fit <- sampling(mod, data = list(y_mean = 0))
Error: cannot allocate vector of size 699575.6 Gb
after running the following the example:
example(stan_model, package = "rstan", run.dontrun = TRUE)
Full output
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)
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 '16a540c6086086816528e4524def24d9' FROM Stan CODE TO C++ CODE NOW.
successful in parsing the Stan model '16a540c6086086816528e4524def24d9'.
COMPILING THE C++ CODE FOR MODEL '16a540c6086086816528e4524def24d9' NOW.
OS: x86_64, linux-gnu; rstan: 2.21.8; Rcpp: 1.0.11; inline: 0.3.19
>> setting environment variables:
PKG_LIBS = '/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/rstan/lib//libStanServices.a' -L'/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/lib/' -lStanHeaders -L'/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppParallel/lib/' -ltbb
PKG_CPPFLAGS = -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/Rcpp/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppEigen/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppEigen/include/unsupported" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/BH/include" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/include/src/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppParallel/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/rstan/include" -DEIGEN_NO_DEBUG -DBOOST_DISABLE_ASSERTS -DBOOST_PENDING_INTEGER_LOG2_HPP -DSTAN_THREADS -DBOOST_NO_AUTO_PTR -include '/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/include/stan/math/prim/fun/Eigen.hpp' -D_REENTRANT -DRCPP_PARALLEL_USE_TBB=1
>> 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 model1a719e4677_16a540c6086086816528e4524def24d9_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", "model1a719e4677_16a540c6086086816528e4524def24d9");
32 : reader.add_event(3, 1, "end", "model1a719e4677_16a540c6086086816528e4524def24d9");
33 : return reader;
34 : }
35 :
36 : class model1a719e4677_16a540c6086086816528e4524def24d9
37 : : public stan::model::model_base_crtp<model1a719e4677_16a540c6086086816528e4524def24d9> {
38 : private:
39 : double y_mean;
40 : public:
41 : model1a719e4677_16a540c6086086816528e4524def24d9(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 : model1a719e4677_16a540c6086086816528e4524def24d9(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__ = "model1a719e4677_16a540c6086086816528e4524def24d9_namespace::model1a719e4677_16a540c6086086816528e4524def24d9";
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 : ~model1a719e4677_16a540c6086086816528e4524def24d9() { }
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__ = "model1a719e4677_16a540c6086086816528e4524def24d9_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 "model1a719e4677_16a540c6086086816528e4524def24d9";
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 model1a719e4677_16a540c6086086816528e4524def24d9_namespace::model1a719e4677_16a540c6086086816528e4524def24d9 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_fit4model1a719e4677_16a540c6086086816528e4524def24d9_mod){
352 : Rcpp::class_<stan_model_holder>("stan_fit4model1a719e4677_16a540c6086086816528e4524def24d9")
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 file1a30f68b06( ) ;
364 : }
365 :
366 : // definition
367 : SEXP file1a30f68b06() {
368 : return Rcpp::wrap("16a540c6086086816528e4524def24d9");
369 : }
make cmd is
make -f '/opt/R/4.1.0/lib/R/etc/Makeconf' -f '/opt/R/4.1.0/lib/R/share/make/shlib.mk' -f '/home/A549936/.R/Makevars' CXX='$(CXX14) $(CXX14STD)' CXXFLAGS='$(CXX14FLAGS)' CXXPICFLAGS='$(CXX14PICFLAGS)' SHLIB_LDFLAGS='$(SHLIB_CXX14LDFLAGS)' SHLIB_LD='$(SHLIB_CXX14LD)' SHLIB='file1a30f68b06.so' OBJECTS='file1a30f68b06.o'
make would use
/usr/bin/x86_64-linux-gnu-g++ -std=gnu++14 -I"/opt/R/4.1.0/lib/R/include" -DNDEBUG -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/Rcpp/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppEigen/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppEigen/include/unsupported" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/BH/include" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/include/src/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppParallel/include/" -I"/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/rstan/include" -DEIGEN_NO_DEBUG -DBOOST_DISABLE_ASSERTS -DBOOST_PENDING_INTEGER_LOG2_HPP -DSTAN_THREADS -DBOOST_NO_AUTO_PTR -include '/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/include/stan/math/prim/fun/Eigen.hpp' -D_REENTRANT -DRCPP_PARALLEL_USE_TBB=1 -I/usr/local/include -fpic -O3 -march=native -mtune=native -fPIC -c file1a30f68b06.cpp -o file1a30f68b06.o
if test "zfile1a30f68b06.o" != "z"; then \
echo /usr/bin/x86_64-linux-gnu-g++ -std=gnu++14 -shared -L"/opt/R/4.1.0/lib/R/lib" -L/usr/local/lib -o file1a30f68b06.so file1a30f68b06.o '/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/rstan/lib//libStanServices.a' -L'/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/lib/' -lStanHeaders -L'/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppParallel/lib/' -ltbb -L"/opt/R/4.1.0/lib/R/lib" -lR; \
/usr/bin/x86_64-linux-gnu-g++ -std=gnu++14 -shared -L"/opt/R/4.1.0/lib/R/lib" -L/usr/local/lib -o file1a30f68b06.so file1a30f68b06.o '/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/rstan/lib//libStanServices.a' -L'/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/StanHeaders/lib/' -lStanHeaders -L'/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/RcppParallel/lib/' -ltbb -L"/opt/R/4.1.0/lib/R/lib" -lR; \
fi
Running
example(stan_model, run.dontrun=TRUE, verbose = TRUE)
gives the error :
stn_md> fit <- sampling(mod, data = list(y_mean = 0))
Error in get("storage", envir = as.environment(x)) :
object 'storage' not found
Full output
Found file = ‘/home/A549936/R/x86_64-pc-linux-gnu-library/4.1/rstan/help/stan_model’
'envir' chosen:<environment: R_GlobalEnv>
encoding = "UTF-8" chosen
--> parsed 4 expressions; now eval(.)ing them:
has srcrefs:
List of 4
$ : 'srcref' int [1:8] 8 1 8 84 1 84 8 8
..- attr(*, "srcfile")=Classes 'srcfilecopy', 'srcfile' <environment: 0x7f4b90880b80>
$ : 'srcref' int [1:8] 9 1 9 56 1 56 9 9
..- attr(*, "srcfile")=Classes 'srcfilecopy', 'srcfile' <environment: 0x7f4b90880b80>
$ : 'srcref' int [1:8] 10 1 10 45 1 45 10 10
..- attr(*, "srcfile")=Classes 'srcfilecopy', 'srcfile' <environment: 0x7f4b90880b80>
$ : 'srcref' int [1:8] 11 1 11 46 1 46 11 11
..- attr(*, "srcfile")=Classes 'srcfilecopy', 'srcfile' <environment: 0x7f4b90880b80>
>>>> eval(expression_nr. 1 )
=================
stn_md> stancode <- 'data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}'
curr.fun: symbol <-
.. after ‘expression(stancode <- 'data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}')’
>>>> eval(expression_nr. 2 )
=================
stn_md> mod <- stan_model(model_code = stancode, verbose = TRUE)
TRANSLATING MODEL '16a540c6086086816528e4524def24d9' FROM Stan CODE TO C++ CODE NOW.
successful in parsing the Stan model '16a540c6086086816528e4524def24d9'.
curr.fun: symbol <-
.. after ‘expression(mod <- stan_model(model_code = stancode, verbose = TRUE))’
>>>> eval(expression_nr. 3 )
=================
stn_md> fit <- sampling(mod, data = list(y_mean = 0))
Error in get("storage", envir = as.environment(x)) :
object 'storage' not found
utils::sessionInfo()
Full session info
R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.6 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
[6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] rstan_2.21.8 ggplot2_3.4.2 StanHeaders_2.26.27
loaded via a namespace (and not attached):
[1] Rcpp_1.0.11 pillar_1.9.0 compiler_4.1.0 prettyunits_1.1.1 tools_4.1.0 pkgbuild_1.4.2 lifecycle_1.0.3 tibble_3.2.1
[9] gtable_0.3.3 pkgconfig_2.0.3 rlang_1.1.1 cli_3.6.1 rstudioapi_0.14 parallel_4.1.0 loo_2.6.0 gridExtra_2.3
[17] withr_2.5.0 dplyr_1.1.2 generics_0.1.3 vctrs_0.6.3 stats4_4.1.0 grid_4.1.0 tidyselect_1.2.0 glue_1.6.2
[25] inline_0.3.19 R6_2.5.1 processx_3.8.2 fansi_1.0.4 callr_3.7.3 magrittr_2.0.3 codetools_0.2-18 scales_1.2.1
[33] ps_1.7.5 matrixStats_1.0.0 colorspace_2.1-0 utf8_1.2.3 RcppParallel_5.1.7 munsell_0.5.0 crayon_1.5.2
Operating System: x86_64, linux-gnu
Interface Version: stan: 2.21.8; Rcpp: 1.0.11; inline: 0.3.19
RStudio 2021.09.0+351.pro6 "Ghost Orchid" Release (50423e45af21f7b8d57c1937d66cceade58de01a, 2021-09-23) for Ubuntu Bionic
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36
Compiler/Toolkit:
which gcc
/usr/bin/gcc
cd /usr/bin/gcc
ls | grep "gcc"
gives:
c89-gcc
c99-gcc
gcc
gcc-7
gcc-ar
gcc-ar-7
gcc-nm
gcc-nm-7
gcc-ranlib
gcc-ranlib-7
x86_64-linux-gnu-gcc
x86_64-linux-gnu-gcc-7
x86_64-linux-gnu-gcc-ar
x86_64-linux-gnu-gcc-ar-7
x86_64-linux-gnu-gcc-nm
x86_64-linux-gnu-gcc-nm-7
x86_64-linux-gnu-gcc-ranlib
x86_64-linux-gnu-gcc-ranlib-7
gcc --version
gives
gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Copyright (C) 2017 Free Software Foundation, Inc.
My Makevars:
CXX14FLAGS=-O3 -march=native -mtune=native -fPIC
CXX14=/usr/bin/x86_64-linux-gnu-g++
I’ve tried changing my CXX14= to gcc, gcc-7 and x86_64-linux-gnu-gcc-7 and they gave the same error as above.
I’ve also read all the related threads on the forum and tried removing pakcages
"StanHeaders", "RcppParallel", "RcppEigen", "BH", "Rcpp", "RcppEigen" and reinstalling from source multiple times.
At this point I think I’ve exhuasted the list of options to try. Any help or suggestions is greatly appreciated! Thank you very much in advance.
