We build TensorFlow 1.6 on the Jetson TX with some new scripts written by Jason Tichy over at NVIDIA. Looky here:
Background
TensorFlow is one of the major deep learning systems. Created at Google, it is an open-source software library for machine intelligence. The Jetson TX2 ships with TensorRT. TensorRT is what is called an “Inference Engine“, the idea being that large machine learning systems can train models which are then transferred over and “run” on the Jetson.
In the vast majority of cases, you will want to install the associated .whl files for TensorFlow and not build from source. You can find the latest set of .whl files in the NVIDIA Jetson Forums.
Note: We previously built TensorFlow for both the Jetson TX2 and Jetson TX1 for L4T 28.1. Because of changes to the Java environment, these have been deprecated.
Some people would like to use the entire TensorFlow system on a Jetson. In this article, we’ll go over the steps to build TensorFlow r1.6 on a Jetson TX Dev Kit from source. These scripts work on both the Jetson TX1 and Jetson TX2. This should take about three hours to build on a Jetson TX2, longer on a Jetson TX1.
You will need ~10GB of free space in your build area. Typically the smart move is to freshly flash your Jetson with L4T 28.2, CUDA 9.0 Toolkit and cuDNN 7.0.5 and then start your build.
Installation
The TensorFlow scripts are located in the JasonAtNvidia account on Github in the JetsonTFBuild repository. You can simply check out the entire repository:
$ git checkout https://github.com/JasonAtNvidia/JetsonTFBuild.git
which will clone the repository including the TensorFlow .whl files. The .whl files take up several hundred megabytes of space. You may want to delete the .whl files.
As an alternative, here’s a script which will download the repository without the wheels directory:
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| #!/bin/bash | |
| cd $HOME | |
| # Get TensorFlow build scripts from JasonAtNvidia JetsonTFBuild repository | |
| git clone –no-checkout https://github.com/JasonAtNvidia/JetsonTFBuild.git | |
| cd JetsonTFBuild | |
| # Sparse checkout tells git not to checkout the wheels directory | |
| # where all of the .whl files are kept | |
| git config core.sparsecheckout true | |
| # Do not checkout the wheels directory | |
| echo '!wheels/*' >> .git/info/sparse-checkout | |
| # But checkout everything else | |
| echo "/*" >> .git/info/sparse-checkout | |
| git checkout | |
| echo "JetsonTFBuild checked out" |
Save the gist to a file (for example getJetsonTFBuild.sh), save the file and then execute it. For example:
$ bash getJetsonTFBuild.sh
This will download everything except the wheel directory.
Next, switch over to the repository directory:
$ cd JetsonTFBuild
Building
To execute the build file:
$ sudo bash BuildTensorFlow.sh
There are three parameters which you may pass to the script:
- -b | --branch <branchname> Github branch to clone, i.e r1.6 (default: master)
- -s | --swapsize <size> Size of swap file to create to assist building process in GB, i.e. 8
- -d | --dir <directory> Directory to download files and use for build process, default: pwd/TensorFlow_install
Because the Jetson TX1 and Jetson TX2 do not have enough physical memory to build TensorFlow, a swap file is used.
Note: On a Jetson TX1, make sure that you set the directory to point to a device which has enough space for the build. The TX1 does not have enough eMMC memory to hold the swap file. The faster the external memory the better. The Jetson TX2 eMMC does have enough extra room for the build.
For example, to compile TensorFlow release 1.6 on a Jetson TX2 (as shown in the video):
$ sudo bash BuildTensorFlow.sh -b r1.6
After the TensorFlow build (which will take between 3 to 6 hours), you should do a validation check.
Validation
You can go through the procedure on the TensorFlow installation page: Tensorflow: Validate your installation
Validate your TensorFlow installation by doing the following:
Start a Terminal.
Change directory (cd) to any directory on your system other than the tensorflow subdirectory from which you invoked the configure command.
Invoke python or python3 accordingly, for python 2.X for example:
$ python
Enter the following short program inside the python interactive shell:
>>> import tensorflow as tf
>>> hello = tf.constant(‘Hello, TensorFlow!’)
>>> sess = tf.Session()
>>> print(sess.run(hello))
If the Python program outputs the following, then the installation is successful and you can begin writing TensorFlow programs.
Hello, TensorFlow!”
This is not very thorough, of course. However it does show that what you have built is installed.
Conclusion
This is a pretty straight forward process to build TensorFlow. At the same time, you should spend the time in reading through the scripts to get an understanding of how they operate.
Make sure to report any issues on the JasonAtNvidia account in the JetsonTFBuild repository.
Special thanks again to Jason Tichy over at NVIDIA for the repository!
Notes
- The install in the video was performed directly after flashing the Jetson TX2 with JetPack 3.2
- The install is lengthy, however it certainly should take much less than 4 hours on a TX2 and less than 6 hours on a TX1 once all the files are downloaded. If it takes longer, something is wrong.
- In the video, TensorFlow 1.6.0 is installed
20 Responses
Just woke up so my brain isn’t working yet. Would it be terribly difficult to build on a desktop then transfer to the TX1 or -2?
David – you would need to cross compile them for the aarch64 architecture on your desktop for that to work… otherwise building them on your desktop would build x86-64 wheels that wont run on the arm processor on the jetsons.
I think it depends on your definition of “terribly difficult”. There are several parts. You have to set up a cross compilation environment. You need to have a version of Bazel, the Google build tool, that runs using Java. The scripts here build a version of Bazel for this version of TensorFlow, as Bazel is still in development. Of course you then have the cross compilation issue with the version of Python that you’re using if you are building the .whl files (this is easier if you’re just building C/C++ libraries). Me, I’m not smart enough to figure all that stuff out so I just compile on the device.
In any case, there’s really no need to compile TensorFlow. Enough people have done it, including people at NVIDIA, that you can just download the .whl files and install.
Faced problems with tensorrt. Had to put TF_NEED_TENSORRT=1 in helperscript and build against master using. Everything went well.
Thanks for the information, and thanks for reading!
Can this information install TensorFlow 1.7 on JetsonTX2?
Where should I change install TensorFlow 1.6?
Please visit the Github repository: https://github.com/JasonAtNvidia/JetsonTFBuild
You can also find older versions here: https://github.com/peterlee0127/tensorflow-nvJetson
Thanks for reading!
admin problem, not topic specific. Only way to get you guys the message is this way. Sorry. I tried to get a new password sent to my email box but it has been several hours now and it still hasn’t shown up. Is this normal?
Hi, I’m using this tutorial to Install TF on my Jetson TX2. I have just received this error.
ERROR: Skipping ‘//tensorflow/tools/pip_package:build_pip_package’: error loading package ‘tensorflow/tools/pip_package’: Encountered error while reading extension file ‘build_defs.bzl’: no such package ‘@local_config_tensorrt//’: Traceback (most recent call last):
File “/home/nvidia/JetsonTFBuild/TensorFlow_Install/tensorflow/third_party/tensorrt/tensorrt_configure.bzl”, line 160
auto_configure_fail(“TensorRT library (libnvinfer) v…”)
File “/home/nvidia/JetsonTFBuild/TensorFlow_Install/tensorflow/third_party/gpus/cuda_configure.bzl”, line 210, in auto_configure_fail
fail((“\n%sCuda Configuration Error:%…)))
Cuda Configuration Error: TensorRT library (libnvinfer) version is not set.
WARNING: Target pattern parsing failed.
ERROR: error loading package ‘tensorflow/tools/pip_package’: Encountered error while reading extension file ‘build_defs.bzl’: no such package ‘@local_config_tensorrt//’: Traceback (most recent call last):
File “/home/nvidia/JetsonTFBuild/TensorFlow_Install/tensorflow/third_party/tensorrt/tensorrt_configure.bzl”, line 160
auto_configure_fail(“TensorRT library (libnvinfer) v…”)
File “/home/nvidia/JetsonTFBuild/TensorFlow_Install/tensorflow/third_party/gpus/cuda_configure.bzl”, line 210, in auto_configure_fail
fail((“\n%sCuda Configuration Error:%…)))
Cuda Configuration Error: TensorRT library (libnvinfer) version is not set.
INFO: Elapsed time: 2.895s
FAILED: Build did NOT complete successfully (0 packages loaded)
currently loading: tensorflow/tools/pip_package
Can anyone give me some advice on how to resolve this problem please? Thanks.
What version of L4T are you running? Do you have TensorRT installed?
Hi, I am using Jetpack 3.2. I think TensorRT is pre-installed on Jetpack 3.2. Thanks for the reply.
You should file an issue with: https://github.com/JasonAtNvidia/JetsonTFBuild
same problem with Jetpack3.2 on TX1
You should file an issue with: https://github.com/JasonAtNvidia/JetsonTFBuild
You can download the wheel file,then use “sudo -H pip3 install tensorflow-1.6.0rc1-cp35-cp35m-linux_aarch64.whl” to install tensorflow.This method can skip the build process.The flow link can help you download the whl file.Thank furkankalinsaz’s help.
https://devtalk.nvidia.com/default/topic/1030603/tensorflow-1-6-for-jetson-tx2/
Hello,
I have errors, and I think it is due to my “sources.list” file. Could someone who succeeded to install tensorflow 1.6 copy-paste the content of this file?
I freshly flashed my Jetson TX2 with L4T 28.2, CUDA 9.0 Toolkit and cuDNN 7.0.5
Thank you very much in advance!
I flashed my Jetson TX2 with Tegra186_Linux_R28.2.1_aarch64.
Then I followed to install JetPack 3.3.
There are lots of compatibility problems during TensorFlow installation, so I searched the best wheel for it: TensorFlow 1.10-rc1.
I choose to install this wheel because it is the only one that seems to work with CUDA 9.0 and CUDNN v7.1.5.
For more info, I suggest you follow the designs from the link: https://github.com/peterlee0127/tensorflow-nvJetson
I had an error when loading Tensor flow. I am running a TX2, it was freshly flashed with Jetpack 3.2.1.Here are the errors I am seeing after following the instructions this occurred after executing ‘sudo bash BuildTensorflow.sh’ :
……………………………
WARNING: Config value opt is not defined in any .rc file
ERROR: /home/nvidia/JetsonTFBuild/TensorFlow_Install/tensorflow/WORKSPACE:21:1: Traceback (most recent call last):
File “/home/nvidia/JetsonTFBuild/TensorFlow_Install/tensorflow/WORKSPACE”, line 21
check_bazel_version_at_least(“0.15.0”)
File “/home/nvidia/JetsonTFBuild/TensorFlow_Install/tensorflow/tensorflow/version_check.bzl”, line 47, in check_bazel_version_at_least
fail(“\nCurrent Bazel version is {}, …))
Current Bazel version is 0.13.0- (@non-git), expected at least 0.15.0
ERROR: Error evaluating WORKSPACE file
ERROR: error loading package ”: Encountered error while reading extension file ‘android.bzl’: no such package ‘@local_config_android//’: error loading package ‘external’: Could not load //external package
ERROR: error loading package ”: Encountered error while reading extension file ‘android.bzl’: no such package ‘@local_config_android//’: error loading package ‘external’: Could not load //external package
INFO: Elapsed time: 3.549s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (0 packages loaded)
@AdamAmp
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Hi. I’m trying this tutorial but I had some compile error.
Would you give me some advice?
I’ve installed following libraries and packages.
JetPack3.2
CUDA9.0
cuDNN7.0.5
————————————–
nvidia@tegra-ubuntu:~/JetsonTFBuild$ sudo -H bash BuildTensorflow.sh -b r1.6
Reading package lists… Done
Building dependency tree
Reading state information… Done
build-essential is already the newest version (12.1ubuntu2).
unzip is already the newest version (6.0-20ubuntu1).
zip is already the newest version (3.0-11).
openjdk-8-jdk is already the newest version (8u181-b13-0ubuntu0.16.04.1).
python-dev is already the newest version (2.7.12-1~16.04).
The following packages were automatically installed and are no longer required:
apt-clone archdetect-deb dmeventd dmraid dpkg-repack gir1.2-timezonemap-1.0
gir1.2-xkl-1.0 grub-common gstreamer1.0-plugins-bad-videoparsers kpartx
kpartx-boot libappstream3 libass5 libavresample-ffmpeg2 libbs2b0
libdebian-installer4 libdevmapper-event1.02.1 libdmraid1.0.0.rc16 libflite1
libgstreamer-plugins-bad1.0-0 libllvm5.0 liblockfile-bin liblockfile1
liblvm2app2.2 liblvm2cmd2.02 libmircommon5 libparted-fs-resize0 libqmi-glib1
libqpdf17 libreadline5 libsodium18 libzmq5 lockfile-progs lvm2 os-prober
pmount python3-icu python3-pam rdate ubiquity-casper ubiquity-ubuntu-artwork
ubuntu-core-launcher
Use ‘sudo apt autoremove’ to remove them.
0 upgraded, 0 newly installed, 0 to remove and 254 not upgraded.
Reading package lists… Done
Building dependency tree
Reading state information… Done
python-numpy is already the newest version (1:1.11.0-1ubuntu1).
python-scipy is already the newest version (0.17.0-1).
python-wheel is already the newest version (0.29.0-1).
python-pip is already the newest version (8.1.1-2ubuntu0.4).
The following packages were automatically installed and are no longer required:
apt-clone archdetect-deb dmeventd dmraid dpkg-repack gir1.2-timezonemap-1.0
gir1.2-xkl-1.0 grub-common gstreamer1.0-plugins-bad-videoparsers kpartx
kpartx-boot libappstream3 libass5 libavresample-ffmpeg2 libbs2b0
libdebian-installer4 libdevmapper-event1.02.1 libdmraid1.0.0.rc16 libflite1
libgstreamer-plugins-bad1.0-0 libllvm5.0 liblockfile-bin liblockfile1
liblvm2app2.2 liblvm2cmd2.02 libmircommon5 libparted-fs-resize0 libqmi-glib1
libqpdf17 libreadline5 libsodium18 libzmq5 lockfile-progs lvm2 os-prober
pmount python3-icu python3-pam rdate ubiquity-casper ubiquity-ubuntu-artwork
ubuntu-core-launcher
Use ‘sudo apt autoremove’ to remove them.
0 upgraded, 0 newly installed, 0 to remove and 254 not upgraded.
Reading package lists… Done
Building dependency tree
Reading state information… Done
E: Unable to locate package python-enum32
Reading package lists… Done
Building dependency tree
Reading state information… Done
python3-dev is already the newest version (3.5.1-3).
python3-numpy is already the newest version (1:1.11.0-1ubuntu1).
python3-scipy is already the newest version (0.17.0-1).
python3-wheel is already the newest version (0.29.0-1).
python3-pip is already the newest version (8.1.1-2ubuntu0.4).
The following packages were automatically installed and are no longer required:
apt-clone archdetect-deb dmeventd dmraid dpkg-repack gir1.2-timezonemap-1.0
gir1.2-xkl-1.0 grub-common gstreamer1.0-plugins-bad-videoparsers kpartx
kpartx-boot libappstream3 libass5 libavresample-ffmpeg2 libbs2b0
libdebian-installer4 libdevmapper-event1.02.1 libdmraid1.0.0.rc16 libflite1
libgstreamer-plugins-bad1.0-0 libllvm5.0 liblockfile-bin liblockfile1
liblvm2app2.2 liblvm2cmd2.02 libmircommon5 libparted-fs-resize0 libqmi-glib1
libqpdf17 libreadline5 libsodium18 libzmq5 lockfile-progs lvm2 os-prober
pmount python3-icu python3-pam rdate ubiquity-casper ubiquity-ubuntu-artwork
ubuntu-core-launcher
Use ‘sudo apt autoremove’ to remove them.
0 upgraded, 0 newly installed, 0 to remove and 254 not upgraded.
Reading package lists… Done
Building dependency tree
Reading state information… Done
python3-h5py is already the newest version (2.6.0-1).
python3-mock is already the newest version (1.3.0-2.1ubuntu1).
The following packages were automatically installed and are no longer required:
apt-clone archdetect-deb dmeventd dmraid dpkg-repack gir1.2-timezonemap-1.0
gir1.2-xkl-1.0 grub-common gstreamer1.0-plugins-bad-videoparsers kpartx
kpartx-boot libappstream3 libass5 libavresample-ffmpeg2 libbs2b0
libdebian-installer4 libdevmapper-event1.02.1 libdmraid1.0.0.rc16 libflite1
libgstreamer-plugins-bad1.0-0 libllvm5.0 liblockfile-bin liblockfile1
liblvm2app2.2 liblvm2cmd2.02 libmircommon5 libparted-fs-resize0 libqmi-glib1
libqpdf17 libreadline5 libsodium18 libzmq5 lockfile-progs lvm2 os-prober
pmount python3-icu python3-pam rdate ubiquity-casper ubiquity-ubuntu-artwork
ubuntu-core-launcher
Use ‘sudo apt autoremove’ to remove them.
0 upgraded, 0 newly installed, 0 to remove and 254 not upgraded.
Reading package lists… Done
Building dependency tree
Reading state information… Done
mlocate is already the newest version (0.26-1ubuntu2).
The following packages were automatically installed and are no longer required:
apt-clone archdetect-deb dmeventd dmraid dpkg-repack gir1.2-timezonemap-1.0
gir1.2-xkl-1.0 grub-common gstreamer1.0-plugins-bad-videoparsers kpartx
kpartx-boot libappstream3 libass5 libavresample-ffmpeg2 libbs2b0
libdebian-installer4 libdevmapper-event1.02.1 libdmraid1.0.0.rc16 libflite1
libgstreamer-plugins-bad1.0-0 libllvm5.0 liblockfile-bin liblockfile1
liblvm2app2.2 liblvm2cmd2.02 libmircommon5 libparted-fs-resize0 libqmi-glib1
libqpdf17 libreadline5 libsodium18 libzmq5 lockfile-progs lvm2 os-prober
pmount python3-icu python3-pam rdate ubiquity-casper ubiquity-ubuntu-artwork
ubuntu-core-launcher
Use ‘sudo apt autoremove’ to remove them.
0 upgraded, 0 newly installed, 0 to remove and 254 not upgraded.
Requirement already satisfied: keras_applications==1.0.4 in /usr/local/lib/python3.5/dist-packages (1.0.4)
Requirement already satisfied: keras_preprocessing==1.0.2 in /usr/local/lib/python3.5/dist-packages (1.0.2)
Requirement already satisfied: keras_applications==1.0.4 in /usr/local/lib/python3.5/dist-packages (1.0.4)
Requirement already satisfied: keras_preprocessing==1.0.2 in /usr/local/lib/python3.5/dist-packages (1.0.2)
Requirement already satisfied: enum34 in /usr/local/lib/python3.5/dist-packages (1.1.6)
swapon: /home/nvidia/JetsonTFBuild/swapfile.swap: swapon failed: Device or resource busy
Looks like Swap not desired or is already in use
dirname: missing operand
Try ‘dirname –help’ for more information.
dirname: missing operand
Try ‘dirname –help’ for more information.
PYTHON_BIN_PATH=/usr/bin/python2
GCC_HOST_COMPILER_PATH=/usr/bin/gcc
CUDA_TOOLKIT_PATH=
TF_CUDA_VERSION=9.0
TF_CUDA_COMPUTE_CAPABILITIES=5.3,6.2
CUDNN_INSTALL_PATH=/usr/lib/aarch64-linux-gnu
TF_CUDNN_VERSION=7.0.5
./tf_build.sh: line 20: /home/nvidia/JetsonTFBuild: Is a directory
/usr/bin/python2: can’t open file ‘configure.py’: [Errno 2] No such file or directory
error: patch failed: tensorflow/contrib/lite/kernels/internal/BUILD:21
error: tensorflow/contrib/lite/kernels/internal/BUILD: patch does not apply
INFO: Options provided by the client:
Inherited ‘common’ options: –isatty=1 –terminal_columns=80
INFO: Reading rc options for ‘build’ from /home/nvidia/JetsonTFBuild/tensorflow/tools/bazel.rc:
‘build’ options: –define framework_shared_object=true –define=use_fast_cpp_protos=true –define=allow_oversize_protos=true –define=grpc_no_ares=true –spawn_strategy=standalone –genrule_strategy=standalone -c opt
ERROR: Config value opt is not defined in any .rc file
Tue Oct 9 20:34:03 JST 2018 : === Using tmpdir: /tmp/tmp.swhwrsSoaA
cp: cannot stat ‘bazel-bin/tensorflow/tools/pip_package/build_pip_package.runfiles/org_tensorflow/tensorflow’: No such file or directory
———————————-
It’s not clear which Jetson you are running this on. Is it a TX1?
There appear to be many updates to the repository mentioned. If you *really* need version 1.6, you should revert to a Github commit that targeted that version.
The swap file does not appear to be accessible.
I do not know what command line sequence you called, it’s hard to guess the issue.