I don't want to install cuDNN on a computer for which I haven't sudo privileges. For my TensorFlow model I don't need cuDNN, therefore I use the environment variable TF_USE_CUDNN=0. However, I get:
ImportError: libcudnn.so.5: cannot open shared object file: No such file or directory
How I can use TensorFlow without cuDNN?
As far as I can tell from the code that reads the environment variable and its callers, the TF_USE_CUDNN environment variable only disables the use of cuDNN at runtime. Due to the way the standard TensorFlow-on-GPU distribution is linked, it still requires you to install the cuDNN library, because it will be loaded with the rest of the module. The easiest workaround would be to install cuDNN locally in your $HOME/lib directory, and set up LD_LIBRARY_PATH to look for the library there.
Related
While installing saleor, I have encountered with the below issue.
OSError: cannot load library 'gobject-2.0-0': error 0x7e. Additionally, ctypes.util.find_library() did not manage to locate a library called 'gobject-2.0-0'
I have tried all the solutions given in stack overflow as well as git. Nothing seems to be working.
Can someone please help me out.
Tools installed:
python: 3.8 / 3.9
GTK3
I have also updated the GTK3\bin in the top of the environment variables as said in the other solutions.
Download the https://www.msys2.org/ and install it.
a) install gtk package and python bundles from MSYS2 terminal. We can start this with command shell. and pacman -S mingw-w64-x86_64-gtk3
b) pacman -S mingw-w64-x86_64-python-gobject
Update your $XDG_DATA_HOME and XDG_DATA_DIRS to the installed path for example :
'C:/msys64/mingw64/share'
Reboot your system and check, it will work.
Another option that worked for me is :
Install MSYS2 from https://www.msys2.org.
Install GTK3 DLL Dependencies from here : https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer/releases
And then set environment path variables to your windows variable path file.
WEASYPRINT_DLL_DIRECTORIES=C:\GTK3\bin
I am using Conda on a shared compute cluster where numerical and io libraries have been tune for the system.
How can I tell Conda to use these and only worry about the libraries and packages which are not already there on path?
For example:
There is a openmpi library installed and the package which I would like to install and mange with Conda has it also as a dependency.
How can I tell Conda to just worry about what is not there?
One trick is to use a shell package - an empty package whose only purpose is to satisfy constraints for the solver. This is something that Conda Forge does with mpich, as mentioned in this section of the documentation. Namely, for every version, they include an external build variant, that one could install like
conda install mpich=3.4.2=external_*
signaling that it will be supplied by the host. One can consult the recipe's meta.yaml for a concrete example.
I don't think this is great (seems like a lot of work), but I also don't know of a better alternative.
I need libv8-3.14 to run some R packages on linux, but I don't have root access/sudo access on the linux computer I'm using so I'd like to install an external folder instance of libv8-3.14. I've seen R packages reference this as external as CDFLAG="folder/v8-3.14" so I know it is possible.
I'm new(ish) to linux but I've installed external libraries before with tar.gz files which then have a configure file in them, which I set the external folder with ./configure --prefix==/folder/loc, but the only downloads I can find of libv8 are .git (which I can't get to work either).
How can I install an libv8-3.14 to a folder and install so I can set:
export PATH=$PATH:/path/to/install/
and
export `LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/install/`
I had the exact same problem. In case somebody in the future comes across this post, I will leave my suggestions and how it worked out in the end. Also, all credits go to an experienced colleague of mine.
The most sure thing to do is to consult IT, or someone who has already had the same problem, there is usually a workaround these issues.
A way you can do it yourself:
Create an anaconda environment, you can name it 'V8' or something (make sure the environment is based on the latest python version, or recent enough for r-v8).
activate it
install the conda version of the V8 R interface with conda install -c conda-forge r-v8
That's it. Whenever you need V8, fire up your environment beforehand, and it should be A-OK.
Further advice: If you run into errors when installing r-v8, it may be a good idea to update your conda and all the packages. However, depending on your conda version conda update conda and conda upgrade --all MAY BREAK your conda installation, so be careful. (For further information on this problem, see the endless complaints of people in this issue: https://github.com/conda/conda/issues/8920).
V8 doesn't use autotools, so it has no ./configure. In fact, it provides no installation facilities at all, because it is meant for embedding, not installing.
What I would try is to download the Ubuntu package (guessing from your other question, you are on Ubuntu, right?) for the right architecture from https://packages.ubuntu.com/trusty/libv8-3.14.5, and extracting it manually. .deb files are just ZIP archives.
As a side note, there's no point in setting PATH, because libv8, being a library, provides no executables. LD_LIBRARY_PATH is all you need.
I've just started a PyQt5 project that is currently running in a virtualenv.
PyQt5 was installed using a classic pip install pyqt5.
I want to type check my application using mypy.
But when I run it, I get an error telling me that there are no stubs file for PyQt5.
myapp/__main__.py:3: error: No library stub file for module 'PyQt5.QtWidgets
I've checked the site-package of my virtualenv, and indeed, there aren't any .pyi file in it.
Checking the documentation, I see that if compiled, stub files can be generated (and could at least exists beginning with PyQt5.6, I'm using 5.10).
Is there a way to obtain those file without the need to manually compile the library ?
I had the same problem with PyQt5. So I decided to put up PyQt5-stubs which contains the stub files for the main PyQt5 modules.
You can install it with pip:
$ pip install pyqt5-stubs
Another solution for you would be to change to Qt for Python (PySide2). They provide proper type annotations.
Not currently.
PEP 561, which specifies how packages should indicate they supply type information, was recently accepted. (Full disclosure, I am the author).
PyQt5 will need to become compliant with the PEP, and then as long as you are using mypy >=0.600, everything should work as expected.
I used a virtualbox with ubuntu-16, to install caffe in python 2.6. As I wanted to use py2exe, I needed to change python version to 3.6. When this was done, caffe import code stopped working. Here is the error message:
ImportError: libcaffe.so.1.0.0-rc5: cannot open shared object file: No such file
or directory
Do I have to rebuild caffe? Or is something else that need to be changed?
Here is the full image of the error:
Yes, you need to rebuild Caffe. The Python 2 and Python 3 libraries are not compatible. Not all of the file names are the same (different / added software organization). This rebuild requires that you place a single version of Python first in all search paths: make, compile, load, ...
When I need to do this, I check with my SysOps: there's always something I forget.