Re: [R-pkg-devel] Checking the number of cores used
Sorry, I missed the --as-cran option: you run R CMD check --as-cran Duncan Murdoch On 19/09/2023 5:59 a.m., Duncan Murdoch wrote: On 18/09/2023 10:10 a.m., Shu Fai Cheung wrote: Hi All, I know we should not use more than 2 cores in tests, vignettes, etc. I encountered and solved this issue before. However, I still committed this mistake in a new package and would like find out where the cause is. I have a package that already has parallel processing disabled by default and I did not enable parallel processing in the examples and tests (except for one test, which is always skipped by skip()). However, I was told that somewhere in the package more than 2 cores are used. I checked several times and even added a temporary 'stop()` to "trap" parallel processing but still could not find where the source of the problem is. I checked the timing in the log in R CMD check results from winbuilder but everything seems OK. The user time and elapsed time are similar for all the examples. Is there any quick way to check where things go wrong regarding the number of cores? It is not easy to find the source of the problems when there are many examples and tests. If you run R CMD check at the command line, it will produce a directory *.Rcheck containing a number of files. One of those files will be *-Ex.timings, which will give the individual timings of each of the examples in your package. Maybe you can recognize from those which of the examples are problematic ones, and add `proc.time()` calls to the example to figure out which line(s) cause the issue. I don't remember whether winbuilder keeps the timings file when it runs a check. Duncan Murdoch __ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel
Re: [R-pkg-devel] Checking the number of cores used
On 18/09/2023 10:10 a.m., Shu Fai Cheung wrote: Hi All, I know we should not use more than 2 cores in tests, vignettes, etc. I encountered and solved this issue before. However, I still committed this mistake in a new package and would like find out where the cause is. I have a package that already has parallel processing disabled by default and I did not enable parallel processing in the examples and tests (except for one test, which is always skipped by skip()). However, I was told that somewhere in the package more than 2 cores are used. I checked several times and even added a temporary 'stop()` to "trap" parallel processing but still could not find where the source of the problem is. I checked the timing in the log in R CMD check results from winbuilder but everything seems OK. The user time and elapsed time are similar for all the examples. Is there any quick way to check where things go wrong regarding the number of cores? It is not easy to find the source of the problems when there are many examples and tests. If you run R CMD check at the command line, it will produce a directory *.Rcheck containing a number of files. One of those files will be *-Ex.timings, which will give the individual timings of each of the examples in your package. Maybe you can recognize from those which of the examples are problematic ones, and add `proc.time()` calls to the example to figure out which line(s) cause the issue. I don't remember whether winbuilder keeps the timings file when it runs a check. Duncan Murdoch __ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel
Re: [R-pkg-devel] Checking the number of cores used
On 18.09.2023 16:10, Shu Fai Cheung wrote: Hi All, I know we should not use more than 2 cores in tests, vignettes, etc. I encountered and solved this issue before. However, I still committed this mistake in a new package and would like find out where the cause is. I have a package that already has parallel processing disabled by default and I did not enable parallel processing in the examples and tests (except for one test, which is always skipped by skip()). However, I was told that somewhere in the package more than 2 cores are used. I checked several times and even added a temporary 'stop()` to "trap" parallel processing but still could not find where the source of the problem is. I checked the timing in the log in R CMD check results from winbuilder but everything seems OK. The user time and elapsed time are similar for all the examples. Is there any quick way to check where things go wrong regarding the number of cores? It is not easy to find the source of the problems when there are many examples and tests. If it is OK on winbuilder but not on Linux, then likely something makes use of multithreading. Best, Uwe Ligges Regards, Shu Fai __ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel __ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel
