ImportError: (How to success install Tensorflow on Xavier ?)

I already flash JetPack4.1.1 DP and nstall HDF5 as required by TensorFlow:
apt-get install libhdf5-serial-dev hdf5-tools

and i set
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64
export PATH=$PATH:/usr/local/cuda-10.0/bin
export CUDA_HOME=$CUDA_HOME:/usr/local/cuda-10.0

But it still has error message.

nvidia@jetson-0423618000766:~$ python
Python 2.7.15rc1 (default, Nov 12 2018, 14:31:15)
[GCC 7.3.0] on linux2
Type “help”, “copyright”, “credits” or “license” for more information.

import tensorflow
Traceback (most recent call last):
File “”, line 1, in
File “/home/nvidia/.local/lib/python2.7/site-packages/tensorflow/”, line 24, in
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File “/home/nvidia/.local/lib/python2.7/site-packages/tensorflow/python/”, line 49, in
from tensorflow.python import pywrap_tensorflow
File “/home/nvidia/.local/lib/python2.7/site-packages/tensorflow/python/”, line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File “/home/nvidia/.local/lib/python2.7/site-packages/tensorflow/python/”, line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File “/home/nvidia/.local/lib/python2.7/site-packages/tensorflow/python/”, line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File “/home/nvidia/.local/lib/python2.7/site-packages/tensorflow/python/”, line 24, in swig_import_helper
_mod = imp.load_module(’_pywrap_tensorflow_internal’, fp, pathname, description)
ImportError: cannot open shared object file: No such file or directory

Failed to load the native TensorFlow runtime.


for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.


One common issue is that the TensorFlow package is built from different environment.

Could you share how do you install the package?
If you are using JetPack4.1.1, it’s recommended to install our official one:

If you already use the package above, please re-flash your device with JetPack again.
Sometimes, it may caused by incomplete CUDA installation.