In the README file, it says that the framework has been tested on a computer without GPU so I thought I'd give it a try. Unfortunately, the installation instructions using nvidia-docker only seem to work for computers with GPU. I've tried to install and run using vanilla docker which seemed to work but when try to run ./cnn_use.py -l /tmp/path/to/log/ -p /tmp/path/to/pretrained -i /path/to/image for example, I get the following error:
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "/usr/local/lib/python3.5/dist-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/python3.5/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: libcuda.so.1: cannot open shared object file: No such file or directory
Could anybody help me out with the installation for a computer without GPU? I am using a MacBook Pro with Ubuntu 18.04.
In the README file, it says that the framework has been tested on a computer without GPU so I thought I'd give it a try. Unfortunately, the installation instructions using
nvidia-dockeronly seem to work for computers with GPU. I've tried to install and run using vanilla docker which seemed to work but when try to run./cnn_use.py -l /tmp/path/to/log/ -p /tmp/path/to/pretrained -i /path/to/imagefor example, I get the following error:Could anybody help me out with the installation for a computer without GPU? I am using a MacBook Pro with Ubuntu 18.04.