Guidelines for including TMB c++ code in an R package - c++

Question

I've recently discovered the wonders of TMB and I'm working on a package which would ideally include TMB c++ templates in it for rather computationally expensive models.
I'm assuming that there's a possibility of:
Automatically compiling the TMB source code on package install
but I can't find any clear guidelines in the TMB documentation regarding this. As of now, my alternative is to write functions that compile the TMB code upon the first call of a function which uses an uncompiled class... but I have a feeling there are nicer ways to do this.
Has anyone successfully included TMB functions within another package and could point me in the direction of relevant documentation or examples?

Answer 1

With a bit more searching i finally found my answer in this thread. I guess I missed it because the resolutions it details were moved to the wiki page titled development, where the content is specifically targeted for users wishing to contribute to the development of TMB, whereas I just want to distribute code which incorperates TMB.
To summarize, the thread suggests some changes which I adopted like this (myPkg should be the name of your package):
src/
Place your .cpp template in mypkg/src. This will then be automatically compiled by R when you build your package.
DESCRIPTION
Add these lines to your description file so R has all the tools necessary to compile the model template.
Depends: TMB, RcppEigen
LinkingTo: TMB, RcppEigen
R/roxygentags.r
Now we need to add our TMB template to the namespace file. We can do this easily through roxygen by making a dummy file like so:
#' Roxygen commands
#'
#' #useDynLib myPkg
#'
dummy <- function(){
return(NULL)
}
The dummy function is just an excuse to have the tag #useDynLib myPkg somewhere in my source code where I wont mess with it. This tag will populate your NAMESPACE with useDynLib(myPkg)... and as I understand, this loads the shared libraries upon loading the package for you.
Calling the function in your package:
Finally, when calling MakeADFun, set DLL="myPkg". With this setup, you can compile a single TMB model into your package. This is because the content compiled in your ./src/ folder will automatically be renamed according to your package name, thus you cannot create uniquely named models.
EDIT: Solution for distributing multiple DLLs
After some more searching (same thread as referenced above)... I realized that solution described in the official wiki (and detailed above) is only relevant for distributing a single dll (i.e. a single TMB model).
If you want to distribute multiple TMB models in a package, you'll have to use your own makefile. I've given a more detailed description in my blog, so I'll only briefly describe the steps here with regard to how they differ from the previous steps I described.
src/Makefile
You'll have to define your own Makefile (or Makefile.win for windows users) and drop it in your src/ directory. Here's an example that works for me:
all: template1.so template2.so
# Comment here preserves the prior tab
template1.so: template1.cpp
Rscript --vanilla -e "TMB::compile('template1.cpp','-O0 -g')"
template2.so: template2.cpp
Rscript --vanilla -e "TMB::compile('template2.cpp','-O0 -g')"
clean:
rm -rf *o
For windows, replace so, with dll, and use the relevant compiler flags (for debugging). See ?TMB::compile for info regarding compiler flags for debugging.
R/roxygentags.r
This is slightly different than above:
#' Roxygen commands
#'
#' This is a dummy function who's purpose is to hold the useDynLib roxygen tag.
#' This tag will populate the namespace with compiled c++ functions upon package install.
#'
#' #useDynLib template1
#' #useDynLib template2
#'
dummy <- function(){
return(NULL)
}
Using your models in the package
Finally, the above changes will compile multiple uniquely named TMB templates and load them into the namespace. To call these models in your package, here's an example:
obj <- MakeADFun(data = data,
parameters = params,
DLL="template1",
inner.control = list(maxit = 10000),
silent=F)
Tips...
I had issues when I tried compiling this on a windows machine... it turned out to be related to not properly cleaning the src folder and I had old linux compiled files stuck in there. If you have compilation issues, its worth manually cleaning out the residual files in your src/ directory from previous builds... or perhaps someone can give some good advice on writing a better make file!

Answer 2

If you want access to the CppAD library with the additional code from TMB (which is quite substantial!) then you can use the WITH_LIBTMB macro variable as I do in this header here. This will allow you to have multiple .cpp files which you can compile separately. Importantly, you only need to compile the code from the TMB header once using a file like this which #includes the TMB.hpp header without defining WITH_LIBTMB.
This reduces the compilation time substantively as you can compile each .cpp on its own without all the code which is declared in TMB.hpp. Moreover, you can also use the code with Rcpp if you undefine and define a few macros as I do in the link.
You can also have one file which can used by TMB::MakeADFun. It requires a bit of manual work but can be done whilst also using Rcpp by using Rcpp::compileAttributes and changing the created file called RcppExports.cpp to instead be named init.cpp and then include these additional lines in the CallEntries array and R_init_survTMB function:
CallEntries array.
R_init_survTMB function.
Note on using Rstudio
Rstudio calls Rcpp::compileAttributes (or something similar) each time you build. Hence, you cannot use this. One way around this is to create a custom build script similar to the one here. It essentially calls R CMD INSTALL after having removed the RcppExports.cpp file created by Rcpp::compileAttributes. I also like to run the tests by calling devtools::test() but you can remove this if you like.