Dear Jamie, Le 06/11/2019 à 19:15, Jameson Graef Rollins a écrit : > On Wed, Nov 06 2019, Thibaut Paumard <thib...@debian.org> wrote: >> I believe: >> - the issue is not very serious, as it will not prevent your code from >> running fine and efficiently (it's only an informative message). > > It's true that it does not make it completely unusable, but it's > certainly not usable in any command line application without hacking the > import to suppress this message, which is actually quite problematic. > So I don't think we can simply dismiss this issue...
The warning contains a hint how to suppress it: "NOTE: You can disable this warning by setting the MCA parameter btl_base_warn_component_unused to 0." There are various way to do it, such as setting the corresponding environment variable, e.g. in bash: OMPI_MCA_btl_base_warn_component_unused=0 That could be done from within Python as well. More options to set an MCA parameter here: https://www.open-mpi.org/faq/?category=tuning#setting-mca-params >> - it is not in python3-h5py but somewhere in the MPI stack (I have no >> time right now for investigating, but I have seen this recently in >> another MPI code: gyoto). > > It sounds like this issue should then be forwarded to whichever > underlying library is producing the message. It's not ok for libraries > to print warnings to stderr/out, unless they can be easily suppressed by > the caller. But this message can only be suppressed from python with > some very undstandard redirection of stderr at import time. As shown above, the message can be suppressed easily. >> - downgrading only solves your issue because version 2.8.0 was not >> linked with MPI (and therefore may be less efficient, depending on >> hardware). > > Well, in fact, importing the MPI version (2.10.0) is about x7 slower > than the non-MPI version (2.8.0), taking almost a full second for just > the import, so not really a clear performance improvement at all: I will let the h5py maintainer comment on that, but I assume there's a judgment call between enabling MPI parallelization for high performance computing and optimizing the serial user case. In any case, I'm just giving some information I know, I'm not an active developer of h5py, libhdf5 or openmpi. Regards, Thibaut.
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