I really appreciate if any of you can guide me to solve this issue.
I am trying to install additional solvers, I downloaded SCIP and install it, however, when I run it, it finishes without an OUTPUT.
If I run the code with the default solvers Gecode, Chuffed, it does shows me an output.
I am not sure what Minizinc library path to set up on my Preferences, I tired -Glienar, Ggecode. This might be the cause of the error
This is what shows me.
Compiling raid.mzn, with additional data raid_0.dzn
Running raid.mzn
Finished in 18msec
I am using Minizinc 2.1.6 in Linux-Ubuntu 16.04 SCIP 6.0.1, I tried with the latest version of Minizinc but none of the solvers worked.
Related
I started getting the following warning repeatedly when running my PyTorch Lightning deep learning scripts, at execution start and then all through the training:
"OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead."
I get them when executing the main.py script; my scripts are publicly available here.
Symptoms:
I don't think it has anything to do with PyTorch Lightning, maybe even PyTorch.
It appeared overnight, so I don't know what could cause it.
It runs fine without those warnings on my PC.
I get the warnings when I run from my M1 Mac.
I use VSCode for both, each up to date.
I use separate miniconda environments.
Thanks for taking the time to reply!
I managed to sort myself out in the end.
I spotted the numba package in my miniconda env, which is a Python compiler and that seemed to be the root of the problem.
It was version 0.55.2 but the last version to date is 0.56.0. Trying to upgrade it via conda or pip didn't work for some reason (the 0.55.2 version couldn't be replaced).
I recreated my env step by step, and noticed this package comes with torch-audiomentations, a package for audio data augmentation for deep learning, under torch, that I use.
Re-installing it had numba version 0.56.0 installed properly, and the warnings disappeared.
That routine is deprecated, meaning that newer standards want you to use another routine. If you can not edit the code, just ignore. For now it's only an info message. You got that message when you switched to a newer OS / compiler version / OpenMP version.
I´m trying to build paraview from source, therefore using:
Windows 7
Visual Studio 2010
Qt 4.8.7
Python 2.7.8
msmpi 7
paraview source, version 5.1.0
In CMake I can choose different options to specify what functionality to include into the build process. I tried different combinations, like setting BUILD_EXAMPLES or PARAVIEW_USE_MPI, respectively. Now I have got following questions:
When I set BUILD_SHARED_LIBS and PARAVIEW_ENABLE_PYTHON as well (besides others), configuring and generating the project with CMake is successful, but compiling in VS fails; it keeps freezing right after starting the compilation. Did anybody experience the same problem and how did you solve it? (By the way, if I unset BUILD_SHARED_LIBS it works, but I don´t want a static build of Paraview).
By using the combination BUILD_EXAMPLES, BUILD_TESTING, PARAVIEW_BUILD_QT_GUI, PARAVIEW_ENABLE_CATALYST, PARAVIEW_ENABLE_PYTHON and PARAVIEW_USE_MPI the same problem as described in 1.) occurs, but that is more or less what I need to use Catalyst to perform in-situ analysis of my FEM simulation. (Incidentally, if I unset BUILD_TESTING in the above combination it works, but I need CTest to test the Catalyst examples as described here. Does anybody now how to fix that problem?
As shown at GitHub, some examples have been updated to work properly in Paraview 4.4. Is my version of Paraview (5.1.0) unsuitable for the Catalyst examples? Is that the reason why VS is always hanging up for particular variable settings in CMake and which version of Paraview is most suitable to get the Catalyst examples going?
I'd appreciate any help!
That's odd! There's no known reason for this. Although I haven't used VS2010 explicitly, we do have dashboards testing with 2013 and I build with VS2015 with no issue.
I'd recommend using the Ninja as the builder rather than the IDE, however. Just run cmake-gui.exe from appropriate VS studio command prompt and pick Ninja as the build generator. Then, to build, just run ninja in the build directory.
I am new to python, hoping to use it for scientific computation, data acquisition, etc. My ignorance is near total.
I am using a macbook pro, running OSX 10.9.5.
I first installed python 2.7, numpy, and matplotlib; can't remember where they came from. They seem to sit in /Library/Frameworks/Python.framework....
All was OK, until I realized I need scipy also. So, I installed the entire scipy stack from scipy.org, using 'sudo port install py27-numpy py27-scipy py27-matplotlib py27-ipython +notebook py27-pandas py27-sympy py27-nose', after having first installed xcode and the developer tools.
This new installation is located in \opt\local\var\macports\software...
Here's the question: When I run python in a terminal, it always defaults to the original installation. scipy, in particular, cannot be found. I suppose this is a path problem, but I am out of my depth here. Can someone help?
I am trying to install the MATLAB Runtime (see www.mathworks.com/products/compiler/mcr) on Cent0S 7. I think I have installed MCR correctly because the install finishes through saying it completed after running
sudo ./install -mode silent -agreeToLicense yes
However, I am currently getting a error of:
Fatal error loading library /usr/local/MATLAB/MATLAB_Compiler_Runtime/v80/bin/glnxa64/libmwmclmcr.so Error: libXmu.so.6: cannot open shared object file
I have searched around on the forums and found a couple of post that indicate this may be an issue with either 32-bit vs. 64-bit libraries and/or X Windows. Also, I am pretty sure I am setting the following environment LD_LIBRARY_PATH and XAPPLRESDIR set variables correctly.
Has anyone out there successfully installed MATLAB Runtime on CentOS 7? Any help would be appreciated.
Thanks,
Derek
In case anyone else has this issue the following library install fixed the issue for me:
sudo yum install libXmu.x86_64
I have been using LIBSVM in Matlab on Windows and Linux, and get different results. The Linux version just keeps restarting instead of iterating and gets really bad results.
I tried to recompile and did everything that was on the README file, any ideas what could be the issue?