cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version

Question

I get the following error when l run tensorflow in GPU.

2018-09-15 18:56:51.011724: E tensorflow/core/common_runtime/direct_session.cc:158] Internal: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
Traceback (most recent call last):
  File "evaluate_sample.py", line 160, in <module>
    tf.app.run(main)
  File "/anaconda3/envs/tf/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 125, in run
    _sys.exit(main(argv))
  File "evaluate_sample.py", line 123, in main
    with tf.Session() as sess:
  File "/anaconda3/envs/tf/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1494, in __init__
    super(Session, self).__init__(target, graph, config=config)
  File "/anaconda3/envs/tf/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 626, in __init__
    self._session = tf_session.TF_NewSession(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: Failed to create session.

Where do the following errors come from ?

E tensorflow/core/common_runtime/direct_session.cc:158] Internal: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version

and tensorflow.python.framework.errors_impl.InternalError: Failed to create session.

Such tha my version of :

tensorflow is : 1.10

cat /proc/driver/nvidia/version

NVRM version: NVIDIA UNIX x86_64 Kernel Module 390.77 Tue Jul 10 18:28:52 PDT 2018

GCC version: gcc version 7.3.0 (Debian 7.3.0-28)

nvcc --version

nvcc: NVIDIA (R) Cuda compiler driver

Copyright (c) 2005-2016 NVIDIA Corporation

Built on Sun_Sep__4_22:14:01_CDT_2016

Cuda compilation tools, release 8.0, V8.0.44

Answer 1

Updating nvidia driver solved this issue.

You can check your cuda toolkit compatiblity here. Then update your nvidia driver by downloading it from here.

Answer 2

Just update your nvidia drivers and it will solve the issue

Answer 3

The reason for this error is the mismatch of your installed Cuda Toolkit version and the version of the python package cudatoolkit, which is usually installed as dependency of tensorflow-gpu.

In order to fix this you have to first match your tensorflow version with your installed Cuda Toolkit version like shown here

Then you have to check the version of your cudatoolkit package. This have to match major and minor version, so e.g. if you have Cuda Toolkit 9.0 installed and cudatoolkit9_1 is installed you need to downgrade to cudatoolkit9 via your python.