TBB_INTERFACE_NEW flag is not working

Interfaces CmdStan
1

Hello,

I am running into the same issue as this thread

I can compile the model, but running expose_functions will result the same error. What could be the reason for stan not use TBB_INTERFACE_NEW=true flag, FWIW, the init_threadpool_tbb.hpp has these two lines in line 8-9 that should not include tbb_stddef.h if TBB_INTERFACE_NEW is defined:

#ifndef TBB_INTERFACE_NEW
#include <tbb/tbb_stddef.h>

library(brms)
library(data.table)
library(ChainLadder)
data(GenIns)

loss_data <- data.table(
  accident_year = rep(1991:2000, 10),
  dev = sort(rep(1:10, 10)),
  premium = rep(10000000+400000*0:9, 10),
  cum_loss = as.vector(GenIns),
  incr_loss = as.vector(cum2incr(GenIns))
)[order(accident_year, dev),
  `:=`(cum_lr = cum_loss/premium,
       incr_lr = incr_loss/premium)]

myFuns <- '
vector compartmentmodel(real t, vector y, vector theta) {
  vector[3] dydt;
  real ke = theta[1];
  real dr = theta[2];
  real kp1 = theta[3];
  real kp2 = theta[4];
  
  dydt[1] = pow(ke, dr) * pow(t, dr - 1) * exp(-t * ke)/tgamma(dr)
          - (kp1 + kp2) * y[1]; // Exposure
  dydt[2] = kp2 * (y[1] - y[2]); // Outstanding
  dydt[3] = (kp1 *  y[1] + kp2 * y[2]); // Paid
 
  return dydt;
}
real lossemergence(real t, real devfreq, real ke, real dr, 
                   real kp1, real kp2){
    vector[3] y0;
    array[1] vector[3] y;
    vector[4] theta;
    theta[1] = ke;
    theta[2] = dr;
    theta[3] = kp1;
    theta[4] = kp2;
    real out; 
    // Set initial values
    y0[1] = 0; // Exposure
    y0[2] = 0; // Outstanding
    y0[3] = 0; // Paid
    
    y = ode_rk45(compartmentmodel, y0, 0, rep_array(t, 1), theta);
    out = y[1, 3];
    
    if(t > devfreq){ // paid greater dev period 1
    y = ode_rk45(compartmentmodel, y0, 0, rep_array(t - devfreq, 1), theta);
    // incremental paid
     out = out - y[1, 3];
    }
    
    return(out);
}
'

frml <- bf(
  incr_lr ~ eta,
  nlf(eta ~ log(ELR * lossemergence(dev, 1.0, ke, dr, kp1, kp2))),
  nlf(ke ~ exp(oke * 0.5)),
  nlf(dr ~ 1 + 0.1 * exp(odr * 0.5)),
  nlf(kp1 ~ 0.5 * exp(okp1 * 0.5)),
  nlf(kp2 ~ 0.1 * exp(okp2 * 0.5)),
  ELR ~ 1 + (1 | accident_year), 
  oke  ~ 1 + (1 | accident_year), odr ~ 1 + (1 | accident_year), 
  okp1 ~ 1 + (1 | accident_year), okp2 ~ 1 + (1 | accident_year),
  nl = TRUE
)

mypriors <- c(
  prior(inv_gamma(4, 2), nlpar = 'ELR', lb = 0),
  prior(normal(0, 1), nlpar = 'oke'),
  prior(normal(0, 1), nlpar = 'odr'),
  prior(normal(0, 1), nlpar = 'okp1'),
  prior(normal(0, 1), nlpar = 'okp2'),
  prior(student_t(10, 0, 1), class = 'sd', nlpar = 'ELR'),
  prior(student_t(10, 0, 1), class = 'sd', nlpar = 'oke'),
  prior(student_t(10, 0, 1), class = 'sd', nlpar = 'odr'),
  prior(student_t(10, 0, 1), class = 'sd', nlpar = 'okp1'),
  prior(student_t(10, 0, 1), class = 'sd', nlpar = 'okp2'),
  #class = sigma for lognormal family to account for residual sd
  prior(student_t(10, 0, 1), class = 'sigma') 
)

fit <- brm(
  frml,
  data = loss_data, family = lognormal(), 
  prior = mypriors,
  stanvars = stanvar(scode = myFuns, block = 'functions'),
  backend = 'cmdstan',
  file = 'hierarchical-compartmental-model-wide-prior',
  file_refit = 'on_change',
  control = list(adapt_delta = 0.99)
)

fit

x <- summarize_draws(
  as_draws_array(fit, variable = '^b', regex = TRUE),
  mean, sd, ~quantile2(.x, probs = c(0.025, 0.975)))

expose_functions(fit, vectorize = TRUE)

expose_functions(fit, vectorize = TRUE)
using C++ compiler: ‘x86_64-conda-linux-gnu-c++ (conda-forge gcc 12.3.0-13) 12.3.0’
x86_64-conda-linux-gnu-c++ -std=gnu++17 -I"/opt/conda/envs/reserve/lib/R/include" -DNDEBUG   -I"/workspaces/reserve/.cache/R/renv/v5/R-4.3/x86_64-conda-linux-gnu/Rcpp/1.0.12/5ea2700d21e038ace58269ecdbeb9ec0/Rcpp/include" -I"/tmp/RtmpPvsatH/sourceCpp-x86_64-conda-linux-gnu-1.0.12" -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /opt/conda/envs/reserve/include -I/opt/conda/envs/reserve/include -Wl,-rpath-link,/opt/conda/envs/reserve/lib   -std=c++17 -D_REENTRANT -Wno-sign-compare -Wno-ignored-attributes -I'/opt/conda/envs/reserve/bin/cmdstan//opt/conda/envs/reserve/include/' -O3 -I'/opt/conda/envs/reserve/bin/cmdstan/src' -I'/opt/conda/envs/reserve/bin/cmdstan/stan/src' -I'/opt/conda/envs/reserve/bin/cmdstan/stan/lib/rapidjson_1.1.0/' -I'/opt/conda/envs/reserve/bin/cmdstan/lib/CLI11-1.9.1/' -I'/opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/' -I'/opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/lib/eigen_3.4.0' -I'/opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/lib/boost_1.84.0' -I'/opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/lib/sundials_6.1.1/include' -I'/opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/lib/sundials_6.1.1/src/sundials' -I"/workspaces/reserve/.cache/R/renv/v5/R-4.3/x86_64-conda-linux-gnu/cmdstanr/0.8.1/e3409949f3437c53affcf4447c9aaace/cmdstanr/include" -fpic  -fvisibility-inlines-hidden  -fmessage-length=0 -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /opt/conda/envs/reserve/include -fdebug-prefix-map=/home/conda/feedstock_root/build_artifacts/r-base-split_1718533472036/work=/usr/local/src/conda/r-base-4.3.3 -fdebug-prefix-map=/opt/conda/envs/reserve=/usr/local/src/conda-prefix  -c file16d712924aa12.cpp -o file16d712924aa12.o
In file included from /opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math/prim/core.hpp:4,
                 from /opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math/rev/core/Eigen_NumTraits.hpp:5,
                 from /opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math/rev/core/typedefs.hpp:7,
                 from /opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math/rev/core/chainable_object.hpp:6,
                 from /opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math/rev/core.hpp:10,
                 from /opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math/rev.hpp:10,
                 from /opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math.hpp:19,
                 from /opt/conda/envs/reserve/bin/cmdstan/stan/src/stan/model/model_header.hpp:4,
                 from file16d712924aa12.cpp:2:
/opt/conda/envs/reserve/bin/cmdstan/stan/lib/stan_math/stan/math/prim/core/init_threadpool_tbb.hpp:9:10: fatal error: tbb/tbb_stddef.h: No such file or directory
    9 | #include <tbb/tbb_stddef.h>
      |          ^~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [/opt/conda/envs/reserve/lib/R/etc/Makeconf:200: file16d712924aa12.o] Error 1
Error in Rcpp::sourceCpp(code = code, env = env, verbose = verbose, ...) : 
  Error 1 occurred building shared library.

I also see the output of cmdstan_make_local()

r$> cmdstan_make_local()
[1] "TBB_CXX_TYPE=gcc"                        
[2] "TBB_INTERFACE_NEW=true"                  
[3] "TBB_INC=/opt/conda/envs/reserve/include/"
[4] "TBB_LIB=/opt/conda/envs/reserve/lib/"    
[5] "PRECOMPILED_HEADERS=false"               
[6] "STAN_HAS_CXX17=true"                     
[7] "CPPFLAGS_SUNDIALS += -fPIC"              

r$> cmdstan_path()
[1] "/opt/conda/envs/reserve/bin/cmdstan"

r$> check_cmdstan_toolchain()
The C++ toolchain required for CmdStan is setup properly!
2

Looking at the message from exposure_functions output

I think there may be something wrong with this line, seems like there are two directories concatenated together. But I am not sure if this is the issue, or how to fix it if it’s the issue.

-D_REENTRANT -Wno-sign-compare -Wno-ignored-attributes -I'/opt/conda/envs/reserve/bin/cmdstan//opt/conda/envs/reserve/include/'
3

I believe cmdstanr’s expose function does not use the cmdstan build system, which would lead to this @andrjohns

4

Ah interesting! We use make print-CXXFLAGS to get the flags to pass to Rcpp when exposing functions, is there a different/better make target which would capture the additional flags here?

5

Defines are technically “supposed” to go in CPPFLAGS not CXXFLAGS, but I’m not sure if Stan actually does this in practice or not.

Edit: yes, they’re in the pre processor flags. You will probably want both CPPFLAGS and CXXFLAGS, as well as possibly LDLIBS and LDFLAGS if you’re not already using those for linking

6

Edit: yes, they’re in the pre processor flags. You will probably want both CPPFLAGS and CXXFLAGS

Perfect, will do. Thanks!

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7

Sorry I am not very familiar with how stan works behind the scene. It sounds like there is a solution for this issue? Is there a short term fix on user’s end before it’s actually fixed in cmdstanr/cmdstan?

8

I’ve got a PR for the fix now, once the CI passes and I merge it in you can just install cmdstanr from Github and all should work

I’ll ping you here once it’s ready

EDIT: @EKtheSage You can now install the github version:

remotes::install_github("stan-dev/cmdstanr")

And re-run your model

9

@andrjohns Thanks for the update. I re-compiled my model and now exposure_functions have another error:

r$> expose_functions(fit, vectorize = TRUE)

 *** caught segfault ***
address 0x7f8091aed008, cause 'invalid permissions'

Traceback:
 1: dyn.load("/tmp/RtmpXJ3uw2/sourceCpp-x86_64-conda-linux-gnu-1.0.12/sourcecpp_4cdd7639b3d0/sourceCpp_2.so")
 2: eval(ei, envir)
 3: eval(ei, envir)
 4: withVisible(eval(ei, envir))
 5: source(scriptPath, local = env)
 6: Rcpp::sourceCpp(code = code, env = env, verbose = verbose, ...)
 7: force(code)
 8: force(code)
 9: with_envvar(c(R_MAKEVARS_USER = makevars_file), {    set_makevars(new, path, makevars_file, assignment = assignment)    force(code)})
10: withr::with_makevars(c(USE_CXX14 = 1, PKG_CPPFLAGS = cppflags,     PKG_CXXFLAGS = paste0(cxxflags, cmdstanr_includes, collapse = " "),     PKG_LIBS = libs), Rcpp::sourceCpp(code = code, env = env,     verbose = verbose, ...))
11: force(code)
12: withr::with_path(repair_path(file.path(cmdstan_path(), "stan/lib/stan_math/lib/tbb")),     withr::with_makevars(c(USE_CXX14 = 1, PKG_CPPFLAGS = cppflags,         PKG_CXXFLAGS = paste0(cxxflags, cmdstanr_includes, collapse = " "),         PKG_LIBS = libs), Rcpp::sourceCpp(code = code, env = env,         verbose = verbose, ...)))
13: rcpp_source_stan(mod_stan_funs, env, verbose)
14: compile_functions(function_env, verbose, global)
15: expose_stan_functions(self$functions, global, verbose)
16: stanmodel$expose_functions()
17: withCallingHandlers(expr, message = function(c) if (inherits(c,     classes)) tryInvokeRestart("muffleMessage"))
18: suppressMessages(stanmodel$expose_functions())
19: .expose_functions_cmdstanr(stanmodel, vectorize = vectorize,     env = env, ...)
20: expose_functions.brmsfit(fit, vectorize = TRUE)
21: expose_functions(fit, vectorize = TRUE)

Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
10

I was able to solve it by using the information on this thread

Basically need to set STAN_THREADS=TRUE in make/local and rebuild cmdstan.

cmdstan_make_local(
  cpp_options = list(
    'STAN_THREADS' = TRUE
  )
)

rebuild_cmdstan()
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