I want to downgrade my cuda 10.1 to cuda 10.0 in arch linux as tensorflow requires cuda 10.0 only.
I installed tensorflow on CUDA 10.1 in arch Linux but I didn't know tensorflow-gpu needs CUDA 10.0 or lesser.
I tried tried symlinking the required 10.0 libraries with new 10.1 libraries but it didn't work.
Whenever I try to import tensorflow in python console error shows up that 'libcublas.so.10.0' not found.
So I found out that I can only run tensorflow on CUDA 10.0 so now I want to downgrade my CUDA. But I have no Idea how to do that in arch Linux.
Every time I run import tensorflow
it gives this error.
Traceback (most recent call last):
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/usr/lib/python3.7/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/usr/lib/python3.7/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: /usr/lib/libcublas.so.10.0: version `libcublas.so.10.0' not found (required by /home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/__init__.py", line 24, in <module>
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/__init__.py", line 49, in <module>
from tensorflow.python import pywrap_tensorflow
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 74, in <module>
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/usr/lib/python3.7/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/usr/lib/python3.7/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: /usr/lib/libcublas.so.10.0: version `libcublas.so.10.0' not found (required by /home/techievin/.local/lib/python3.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so)
Failed to load the native TensorFlow runtime.
pacman -S cuda=="10.0"
is not working.
I searched everywhere but couldn't find any proper answer for arch Linux to downgrade to CUDA 10.0
sudo pacman -U cuda-10.0.130-2-x86_64.pkg.tar.xz
I've solved this issue by using yay
. With yay
you can install older versions of cuda
and cudnn
. In my experience this is faster than downloading from archive.org.
Install yay
on Arch:
pacman -S --needed git base-devel
git clone https://aur.archlinux.org/yay.git
cd yay
makepkg -si
Search for the version you need:
yay -Ss cuda
yay -Ss cudnn
At the moment of writing this answer I needed to downgrade from cuda
11.2 to 11.0. So I installed specific versions:
pacman -R cuda cudnn
yay -S cuda-11.0 cudnn8-cuda11.0
For me, Tensorflow worked smoothly after downgrading.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With