msys2-runtime | Our friendly fork of Cygwin 💖 https://cygwinorg 💖 see the wiki for details
kandi X-RAY | msys2-runtime Summary
kandi X-RAY | msys2-runtime Summary
This directory contains various GNU compilers, assemblers, linkers, debuggers, etc., plus their support routines, definitions, and documentation. If you are receiving this as part of a GDB release, see the file gdb/README. If with a binutils release, see binutils/README; if with a libg++ release, see libg++/README, etc. That'll give you info about this package -- supported targets, how to use it, how to report bugs, etc.
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QUESTION
I (think) that I have all the libraries installed that I need, e.g.,
...ANSWER
Answered 2021-Sep-08 at 01:11Curating HolyBlackCat's comments into an answer that worked for me:
- Use
mingw64
shell, notmsys*
. (Not sure what purpose the division into multiple binaries serves. Perhaps it matters for other windows versions.) - Search for the archive file under
/mingw64/lib
that matches what you wanted to compile against. So iffoobar
is name of the functionality you wanted look forlibfoobar.a
there. - compile with
g++ main.cpp -o main -lfoobar
QUESTION
(As a student I am kind of new to this but did quite a bit of research and I got pretty far, I'm super into learning something new through this!)
This issue is for the project pulse -> https://github.com/adamian98/pulse
the readme if you scroll down a bit on the page, gives a much better explanation than I could. It will also give a direct "correct" path to judge my actions against and make solving the problem a lot easier.
Objective: run program using the run.py file
Issue: I got a "RuntimeError: CUDA out of memory" despite having a compatible gpu and enough vram
Knowledge: when it comes to coding i just started a few days ago and have a dozen hours with anaconda now, comfterable creating environments.
What I did was... (the list below is a summary and the specific details are after it)
install anaconda
use this .yml file -> https://github.com/leihuayi/pulse/blob/feature/docker/pulse.yml (it changes dependencies to work for windows which is why I needed to grab a different one than the one supplied on the master github page) to create a new environment and install the required packages. It worked fantastically! I only got an error trying to install dlib, it didn't seem compatible with A LOT of the packages and my python version.
I installed the cuda toolkit 10.2 , cmake 3.17.2, and tried to install dlib into the environment directly. the errors spat out in a blaze of glory. The dlib package seems to be only needed for a different .py file and not run.py though so I think it may be unrelated to this error
logs are below and I explain my process in more detail
START DETAILS AND LOGS: from here until the "DETAILS 2" section should be enough information to solve, the rest past there is in case
error log for runing out of memory--> (after executing the "run.py" file)
...ANSWER
Answered 2021-Jan-15 at 02:58based on new log evidence using this script simultaneously alongside the run.py file
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