[Jetson TX2 ] cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime
version
Any pointers on how to solve the following problem:
I am trying to execute tensorflow with GPU support on my Jetson TX2. The code is shown below:
python3
import tensorflow as tf
hello = tf.constant(‘Hello, TensorFlow!’)
sess = tf.Session()
print(sess.run(hello))
An attempt to execute this code generates the following error:
2018-11-16 12:13:43.983272: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:864] ARM64
does not support NUMA - returning NUMA node zero
2018-11-16 12:13:43.983397: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1392] Found
device 0 with properties:
name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate(GHz): 1.3005
pciBusID: 0000:00:00.0
totalMemory: 7.67GiB freeMemory: 5.32GiB
2018-11-16 12:13:43.983517: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1471] Adding
visible gpu devices: 0
2018-11-16 12:13:43.983919: 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 “”, line 1, in
File “/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py”, line 1563, in init
super(Session, self).init(target, graph, config=config)
File “/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py”, line 633, in init
self._session = tf_session.TF_NewSession(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: Failed to create session.
Compiler driver version:
nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Sun_Nov_19_03:16:56_CST_2017
Cuda compilation tools, release 9.0, V9.0.252
nvidia@tegra-ubuntu:~/DeepLearning/rnn-based-af-detection$