My Test
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
My Error
2019-12-27 10:51:17.887009: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/openmpi/lib:
2019-12-27 10:51:17.888489: E tensorflow/stream_executor/cuda/cuda_driver.cc:318] failed call to cuInit: UNKNOWN ERROR (303)
2019-12-27 10:51:17.888992: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (3e7d899714a9): /proc/driver/nvidia/version does not exist
2019-12-27 10:51:17.890608: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-12-27 10:51:17.915554: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2904000000 Hz
2019-12-27 10:51:17.918061: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x56101fca67e0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-27 10:51:17.918228: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
My Environment
Ubunutu 18
tensorflow 1.15.0/1.14.0
My Question
I have reviewed similar issues for example TensorFlow : failed call to cuInit: CUDA_ERROR_NO_DEVICE
The key difference is I do not have the tensorflow-gpu
package installed. How can this error be raised by normal TensorFlow?
Why can't Tensorflow detect my GPU ? Show activity on this post. The issue was solved on GitHub. This error message will be shown if you set an invalid value for the CUDA_VISIBLE_DEVICES environment variable, e.g. when you only have a single GPU (which has ID 0) and set CUDA_VISIBLE_DEVICES=1 or CUDA_VISIBLE_DEVICES=2.
This is most likely because the CUDA and CuDNN drivers are not being correctly detected in your system. I am assuming that you have already installed Tensorflow with GPU support.
Sign in to your account No custom code, Validate you installation test from tensorflow website: Validate your installation test code OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 16.04.4 TensorFlow installed from (source or binary): with pip install --upgrade tensorflow-gpu
any disadvantages to that ? @Jitin Hmmm, only the obvious disadvantage of not having consistent package requirements across machines if you are using some kind of automated deployment of your model across gpu and non-gpu machines. Otherwise, if you are not using the gpu features of tensorflow, there are no disadvantages AFAIK.
You can attempt to work around this problem on cpu-only machines by using the tensorflow-cpu
package instead of tensorflow
.
pip uninstall tensorflow
pip install tensorflow-cpu
Installing nvidia-modprobe can solve this issue.
sudo apt install nvidia-modprobe
Other solutions you can try are :
The problem also could be that only some /dev/nvidia*
files are present before running Python with sudo, check using $ ls /dev/nvidia*
, after running the Device Node verification script the /dev/nvidia-uvm
file gets added.
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