I tried to build from source by following the tutorial. When I do bazel build, it shows me a warning:

WARNING: Sandboxed execution is not supported on your system and thus hermeticity of actions cannot be guaranteed. See http://bazel.io/docs/bazel-user-manual.html#sandboxing for more information. You can turn off this warning via --ignore_unsupported_sandboxing.

I don't know whether this is going to be a problem.

I follow your step to install tensorflow on raspberry pi 2 - newest Raspbian I have a trouble when building Bazel ./compile.sh It shows that error

= new Signal("INT"); ^ src/main/java/com/google/devtools/build/lib/server/signal/InterruptSignalHandler.java:32: warning: Signal is internal proprietary API and may be removed in a future release private static final Signal SIGINT = new Signal("INT"); ^ src/main/java/com/google/devtools/build/lib/server/signal/InterruptSignalHandler.java:34: warning: SignalHandler is internal proprietary API and may be removed in a future release private SignalHandler oldHandler; ^ src/main/java/com/google/devtools/build/lib/server/signal/InterruptSignalHandler.java:42: warning: SignalHandler is internal proprietary API and may be removed in a future release this.oldHandler = Signal.handle(SIGINT, new SignalHandler() { ^ src/main/java/com/google/devtools/build/lib/server/signal/InterruptSignalHandler.java:44: warning: Signal is internal proprietary API and may be removed in a future release public void handle(Signal signal) { ^ src/main/java/com/google/devtools/build/lib/server/signal/InterruptSignalHandler.java:42: warning: Signal is internal proprietary API and may be removed in a future release this.oldHandler = Signal.handle(SIGINT, new SignalHandler() { ^ src/main/java/com/google/devtools/build/lib/server/signal/InterruptSignalHandler.java:55: warning: Signal is internal proprietary API and may be removed in a future release Signal.handle(SIGINT, oldHandler); ^ Exception in thread "main" java.lang.OutOfMemoryError: Java heap space at java.util.jar.Manifest$FastInputStream.(Manifest.java:332) at java.util.jar.Manifest$FastInputStream.(Manifest.java:327) at java.util.jar.Manifest.read(Manifest.java:195) at java.util.jar.Manifest.(Manifest.java:69) at java.util.jar.JarFile.getManifestFromReference(JarFile.java:199) at java.util.jar.JarFile.getManifest(JarFile.java:180) at sun.misc.URLClassPath$JarLoader$2.getManifest(URLClassPath.java:944) at java.net.URLClassLoader.defineClass(URLClassLoader.java:450) at java.net.URLClassLoader.access$100(URLClassLoader.java:73) at java.net.URLClassLoader$1.run(URLClassLoader.java:368) at java.net.URLClassLoader$1.run(URLClassLoader.java:362) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:361) at java.lang.ClassLoader.loadClass(ClassLoader.java:424) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:331) at java.lang.ClassLoader.loadClass(ClassLoader.java:357) at com.sun.tools.javac.main.Main.resourceMessage(Main.java:610) at com.sun.tools.javac.main.Main.compile(Main.java:543) at com.sun.tools.javac.main.Main.compile(Main.java:381) at com.sun.tools.javac.main.Main.compile(Main.java:370) at com.sun.tools.javac.main.Main.compile(Main.java:361) at com.sun.tools.javac.Main.compile(Main.java:56) at com.sun.tools.javac.Main.main(Main.java:42)

Do u have any idea to solve this problems. I guess it maybe OutOfMemoryError. Should I do the swap memory first before compile Bazel.

Thank you very much.

Hi, I want to install tensorflow package on raspberry pi. I was able to go through the first step: download of the package. But when trying to pip install it, I get the following error lines:

could not find any downloads that satisfy the requirements... cleaning up ... No distributions at all found for tensorflow-0.8.0rc0... I tried both install with pip and pip2 without success. Has anyone been facing that error, and was able to solve it? Thanks.

JM

Describe the Issue

[email protected]:~ $ sudo pip install tensorflow-0.11.0-cp27-none-linux_armv7l.whl Unpacking ./tensorflow-0.11.0-cp27-none-linux_armv7l.whl Cleaning up... Exception: Traceback (most recent call last): File "/usr/lib/python2.7/dist-packages/pip/basecommand.py", line 122, in main status = self.run(options, args) File "/usr/lib/python2.7/dist-packages/pip/commands/install.py", line 290, in run requirement_set.prepare_files(finder, force_root_egg_info=self.bundle, bundle=self.bundle) File "/usr/lib/python2.7/dist-packages/pip/req.py", line 1198, in prepare_files do_download, File "/usr/lib/python2.7/dist-packages/pip/req.py", line 1365, in unpack_url unpack_file_url(link, location, download_dir) File "/usr/lib/python2.7/dist-packages/pip/download.py", line 640, in unpack_file_url unpack_file(from_path, location, content_type, link) File "/usr/lib/python2.7/dist-packages/pip/util.py", line 640, in unpack_file unzip_file(filename, location, flatten=not filename.endswith(('.pybundle', '.whl'))) File "/usr/lib/python2.7/dist-packages/pip/util.py", line 510, in unzip_file zip = zipfile.ZipFile(zipfp) File "/usr/lib/python2.7/zipfile.py", line 770, in init self._RealGetContents() File "/usr/lib/python2.7/zipfile.py", line 811, in _RealGetContents raise BadZipfile, "File is not a zip file" BadZipfile: File is not a zip file

Storing debug log for failure in /root/.pip/pip.log

I dont know why it doesnt work.... plz help me

Steps to Reproduce

Hardware/Software Info

Please provide the following information about your Raspberry Pi setup:

• Raspberry Pi model: raspberry pi3 model b.
• Operating System used: mac
• Version of Python used: 2.7.9
• SD card memory size: 32GB
• Size of USB/other device used as swap (if building from source):
• TensorFlow git commit hash (if building from source):

Relevant Console Output/Logs

When I use python3.4, I get the following error:

import tensorflow as tf RuntimeError: module compiled against API version 0xa but this version of numpy is 0x9

I don't get the error using python2.7

Hi, Can I install TensorFlow on the Pi zero.?

I tried "sudo pip2 install tensorflow-0.9.0-cp27-none-linux_armv7l.whl" but it returned tensorflow-0.9.0-cp27-none-linux_armv7l.whl is not a supported wheel on this platform. Storing debug log for failure in /root/.pip/pip.log

Is it possible for Install tensorflow with Docker or C++?

thank you and regards, Khoa

Describe the Issue

After bazel installation, I proceeded to configure Tensorflow and build. Error occurs when building Tensorflow. I am new to Raspberry Pi as I just bought it to do a project, any help would be greatly appreciated.

Target //src:bazel up-to-date:
  bazel-bin/src/bazel
INFO: Elapsed time: 19448.170s, Critical Path: 18836.57s
WARNING: /tmp/bazel_7kFiSyEp/out/external/bazel_tools/WORKSPACE:1: Workspace name in /tmp/bazel_7kFiSyEp/out/external/bazel_tools/WORKSPACE (@io_bazel) does not match the name given in the repository's definition (@bazel_tools); this will cause a build error in future versions.

Build successful! Binary is here: /home/pi/tf/bazel/output/bazel
[email protected]:~/tf/bazel $ cd . .
[email protected]:~/tf/bazel $ cd ..
[email protected]:~/tf $ cd bazel
[email protected]:~/tf/bazel $ sudo cp output/bazel /usr/local/bin/bazel
[email protected]:~/tf/bazel $ bazel
Extracting Bazel installation...
..............................................................................................................................................................................................................................................................
                                               [bazel release 0.4.3- (@non-git)]
Usage: bazel <command> <options> ...

Available commands:
  analyze-profile     Analyzes build profile data.
  build               Builds the specified targets.
  canonicalize-flags  Canonicalizes a list of bazel options.
  clean               Removes output files and optionally stops the server.
  coverage            Generates code coverage report for specified test targets.
  dump                Dumps the internal state of the bazel server process.
  fetch               Fetches external repositories that are prerequisites to the targets.
  help                Prints help for commands, or the index.
  info                Displays runtime info about the bazel server.
  mobile-install      Installs targets to mobile devices.
  query               Executes a dependency graph query.
  run                 Runs the specified target.
  shutdown            Stops the bazel server.
  test                Builds and runs the specified test targets.
  version             Prints version information for bazel.

Getting more help:
  bazel help <command>
                   Prints help and options for <command>.
  bazel help startup_options
                   Options for the JVM hosting bazel.
  bazel help target-syntax
                   Explains the syntax for specifying targets.
  bazel help info-keys
                   Displays a list of keys used by the info command.
[email protected]:~/tf/bazel $ cd ..

[email protected]:~/tf $ git clone --recurse-submodules https://github.com/tensorflow/tensorflow
Cloning into 'tensorflow'...
remote: Counting objects: 170252, done.
remote: Total 170252 (delta 0), reused 0 (delta 0), pack-reused 170251
Receiving objects: 100% (170252/170252), 91.34 MiB | 1.42 MiB/s, done.
Resolving deltas: 100% (130884/130884), done.
Checking connectivity... done.
Checking out files: 100% (5894/5894), done.
[email protected]:~/tf $ cd tensorflow
[email protected]:~/tf/tensorflow $ grep -Rl 'lib64' | xargs sed -i 's/lib64/lib/g'
[email protected]:~/tf/tensorflow $ sudo nano tensorflow/core/platform/platform.h
[email protected]:~/tf/tensorflow $ sudo nano WORKSPACE

[email protected]:~/tf/tensorflow $ ./configure
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:
Do you wish to use jemalloc as the malloc implementation? [Y/n]
jemalloc enabled
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]
No Google Cloud Platform support will be enabled for TensorFlow
Do you wish to build TensorFlow with Hadoop File System support? [y/N]
No Hadoop File System support will be enabled for TensorFlow
Do you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N]
No XLA support will be enabled for TensorFlow
Found possible Python library paths:
  /usr/lib/python3/dist-packages
  /usr/local/lib/python3.4/dist-packages
Please input the desired Python library path to use.  Default is [/usr/lib/python3/dist-packages]
/usr/local/lib/python3.4/dist-packages
Do you wish to build TensorFlow with OpenCL support? [y/N]
No OpenCL support will be enabled for TensorFlow
Do you wish to build TensorFlow with CUDA support? [y/N]
No CUDA support will be enabled for TensorFlow
.............................................................................................................................................................................................................................................................
INFO: Starting clean (this may take a while). Consider using --expunge_async if the clean takes more than several minutes.
Configuration finished

[email protected]:~/tf/tensorflow $ bazel build -c opt --copt="-mfpu=neon-vfpv4" --copt="-funsafe-math-optimizations" --copt="-ftree-vectorize" --copt="-fomit-frame-pointer" --local_resources 1024,1.0,1.0 --verbose_failures tensorflow/tools/pip_package:build_pip_package
WARNING: Sandboxed execution is not supported on your system and thus hermeticity of actions cannot be guaranteed. See http://bazel.build/docs/bazel-user-manual.html#sandboxing for more information. You can turn off this warning via --ignore_unsupported_sandboxing.
ERROR: /home/pi/tf/tensorflow/third_party/gpus/cuda_configure.bzl:883:18: unexpected keyword 'environ' in call to repository_rule(implementation: function, *, attrs: dict or NoneType = None, local: bool = False).
ERROR: com.google.devtools.build.lib.packages.BuildFileContainsErrorsException: error loading package '': Extension file 'third_party/gpus/cuda_configure.bzl' has errors.
INFO: Elapsed time: 42.211s
[email protected]:~/tf/tensorflow $

Steps to Reproduce

Followed step by step installation by source

Hardware/Software Info

Please provide the following information about your Raspberry Pi setup:

• Raspberry Pi model: Raspberry Pi 3 Model B
• Operating System used: Raspian (jessie 8.0) - NOOBs installation
• Version of Python used: 3.4
• SD card memory size: 64gb
• Size of USB/other device used as swap (if building from source): 8gb
• TensorFlow git commit hash (if building from source):

Relevant Console Output/Logs

error tensorflow.txt

Getting a validation failure when attempting to build TensorFlow wheel from source using most recent from-sources guide.

ERROR: /home/pi/tf/tensorflow/tensorflow/tensorboard/bower/BUILD:5:1: no such package '@numericjs_numeric_min_js//file': Error downloading [https://cdnjs.cloudflare.com/ajax/libs/numeric/1.2.6/numeric.min.js] to /home/pi/.cache/bazel/_bazel_pi/4770c5ca1786316d370c900c0b614a6d/external/numericjs_numeric_min_js/numeric.min.js: sun.security.validator.ValidatorException: PKIX path validation failed: java.security.cert.CertPathValidatorException: signature check failed and referenced by '//tensorflow/tensorboard/bower:bower'.
ERROR: Analysis of target '//tensorflow/tools/pip_package:build_pip_package' failed; build aborted.

An issue on the official TensorFlow repo experienced this problem due to Docker getting out of sync with the root machine, but this doesn't help much here.

Wow terrific work, has anyone tried to get tensor flow running in a docker container on the RPI. It would give some nice isolation and in our work, we use docker on arm extensively. In addition, it makes cross compilation easy as you can today run arm containers on linux (by installing qemu-user-static) or Mac (with the new Docker for Mac) so you do not need to compile directly on the Pi. I can send you a link to a docker package and git repo that makes this a little easier, then people can do a docker pull and get tensor flow on their pi without a big compile

I'm finding that your .whl has the following issues and here are the steps:

1. Download Docker for the Mac (it's in private beta) or on your ubuntu/debian machine, run apt-get install docker qemu-user-static which will give you the ability to cross compile
2. Now I'm working on a Dockerfile that can encapsulate your wheel file. The main issue is that the resin/rpi-raspbian is a minimal build so doesn't include things that you need. Specifically here is what I have found so far:

• The toolchain is not all there, in looking at the http://www.scipy.org/scipylib/building/linux.html#installation-from-source instructions, looks like you just need to add to your readme the following prerequisites:

apt-get install gcc fortran 

At a minimum in the rpi-raspbian container. I'm not sure but it looks like you also need libatlas-base-dev as well, but I have not yet finished your .whl compilation. As a final note, instead of creating a swapfile on a device, you might want to use a file based swapfile, that makes things way easier, there is a package called dphys-swapfile, so then you can just mount your junk USB that you do not care about as a single file.

Describe the Issue

When I try to install the Tensorflow through the python-wheel provided by you, I got a error message said: tensorflow-1.0.0-cp27-none-linux_armv7l.whl is not a supported wheel on this platform

Steps to Reproduce

apt-get update
apt-get install python-pip python-dev
wget https://github.com/samjabrahams/tensorflow-on-raspberry-pi/releases/download/v1.0.0/tensorflow-1.0.0-cp27-none-linux_armv7l.whl

sudo pip install tensorflow-1.0.0-cp27-none-linux_armv7l.whl

Hardware/Software Info

Please provide the following information about your Raspberry Pi setup:

• Raspberry Pi model: Raspberry Pi 3
• Operating System used: Raspbian 8
• Version of Python used: 2.7.9
• SD card memory size: 16
• Size of USB/other device used as swap (if building from source):
• TensorFlow git commit hash (if building from source):

Relevant Console Output/Logs

sudo pip install tensorflow-1.0.0-cp27-none-linux_armv7l.whl
tensorflow-1.0.0-cp27-none-linux_armv7l.whl is not a supported wheel on this platform.

Describe the Issue

After installing by pip, bazel is not found when trying to run retrain.py Does bazel have to be installed in addition or is it a fault?

Steps to Reproduce

Install with pip and execute:

bazel build third_party/tensorflow/examples/image_retraining:retrain && \ bazel-bin/third_party/tensorflow/examples/image_retraining/retrain \ --image_dir ~/imagedir

Hardware/Software Info

Please provide the following information about your Raspberry Pi setup:

• Raspberry Pi model: 3
• Operating System used: Jessie
• Version of Python used: 2
• SD card memory size: 16gb
• Size of USB/other device used as swap (if building from source):
• TensorFlow git commit hash (if building from source):

Relevant Console Output/Logs

-bash: bazel: command not found

Describe the Issue

Followed all steps but ./compile.sh results in

[email protected]:~/tf/bazel $ sudo ./compile.sh INFO: You can skip this first step by providing a path to the bazel binary as second argument: INFO: ./compile.sh compile /path/to/bazel 🍃 Building Bazel from scratch ERROR: Cannot determine JDK version, please set $JAVA_HOME.\n $JAVAC_VERSION is "javac 11.0.15"

I tried setting it as follows [email protected]:~/tf/bazel $ JAVA_HOME="${JAVA_HOME:-$(readlink -f $(which javac) | sed 's_/bin/javac__')}" [email protected]:~/tf/bazel $ echo $JAVA_HOME /usr/lib/jvm/java-11-openjdk-armhf But the build still results in the exact same error. Any advice you can offer?

This is by the way on Pi 3B+.

Steps to Reproduce

Hardware/Software Info

Please provide the following information about your Raspberry Pi setup:

• Raspberry Pi model:
• Operating System used:
• Version of Python used:
• SD card memory size:
• Size of USB/other device used as swap (if building from source):
• TensorFlow git commit hash (if building from source):

Relevant Console Output/Logs

hey, thanks for you guys' donation.It's great. As raspberry pi 4B is already been come out. So I wonder if there is something for 4B. Thanks very much.BTW, I use the ubuntu server OS.

###pip install tensorflow...

It runs through the entire process and goes right up to almost 100% and then crashes with multiple red lines and the last line says "Memory Error" - tried different versions, reimaged SD card and same error message

Raspberry PI WH - 8 GB SD Card/Python 3.5

Please provide the following information about your Raspberry Pi setup:

• Raspberry Pi model: WH
• Operating System used: Linux
• Version of Python used: 3.5
• SD card memory size: 8 GB
• Size of USB/other device used as swap (if building from source):
• TensorFlow git commit hash (if building from source): just install so far pip install tensorflow

###Memory Error

Describe the Issue

I am following this guide (https://gist.github.com/EKami/9869ae6347f68c592c5b5cd181a3b205) to install tensorflow on a raspberry pi for c++. I attempt to build the tensorflow library with this command: bazel build -c opt --config=monolithic --local_resources 1024,1.0,1.0 --verbose_failures //tensorflow:libtensorflow_cc.so

Steps to Reproduce

Follow the guide above but skipping the portion where he says to replace: native.new_http_archive( name = "eigen_archive", urls = [ "http://mirror.bazel.build/bitbucket.org/eigen/eigen/get/f3a22f35b044.tar.gz", "https://bitbucket.org/eigen/eigen/get/f3a22f35b044.tar.gz", ], sha256 = "ca7beac153d4059c02c8fc59816c82d54ea47fe58365e8aded4082ded0b820c4", strip_prefix = "eigen-eigen-f3a22f35b044", build_file = str(Label("//third_party:eigen.BUILD")), ) as doing so caused me problems. I also used all of the newest versions of software the tutorial has you download

Hardware/Software Info

Please provide the following information about your Raspberry Pi setup:

• Raspberry Pi model: 3 B+
• Operating System used: Raspbian Stretch
• Version of Python used: 3.5.3
• SD card memory size: 32 GB
• Size of USB/other device used as swap (if building from source): 16 GB
• TensorFlow git commit hash (if building from source): I cloned the repository October 19 2018

Relevant Con/home/pi/tf/tensorflow/tensorflow/BUILD:558:1: Linking of rule '//tensorflow:libtensorflow_cc.so' failed (Exit 1): gcc failed: error executing command

(cd /home/pi/.cache/bazel/_bazel_pi/4770c5ca1786316d370c900c0b614a6d/execroot/org_tensorflow &&
exec env -
PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/games:/usr/games
PWD=/proc/self/cwd
PYTHON_BIN_PATH=/usr/bin/python
PYTHON_LIB_PATH=/usr/local/lib/python2.7/dist-packages
TF_DOWNLOAD_CLANG=0
TF_NEED_CUDA=0
TF_NEED_OPENCL_SYCL=0
/usr/bin/gcc -shared -o bazel-out/arm-opt/bin/tensorflow/libtensorflow_cc.so -z defs -Wl,--version-script tensorflow/tf_version_script.lds '-Wl,-rpath,$ORIGIN/' -Wl,-soname,libtensorflow_cc.so -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread -pthread '-fuse-ld=gold' -Wl,-no-as-needed -Wl,-z,relro,-z,now -B/usr/bin -B/usr/bin -pass-exit-codes -Wl,--gc-sections -Wl,@bazel-out/arm-opt/bin/tensorflow/libtensorflow_cc.so-2.params) bazel-out/arm-opt/bin/tensorflow/core/kernels/_objs/list_kernels/list_kernels.pic.o:list_kernels.cc:function tensorflow::TensorListStack<Eigen::ThreadPoolDevice, tensorflow::bfloat16>::Compute(tensorflow::OpKernelContext*): error: undefined reference to 'void tensorflow::ConcatCPUtensorflow::bfloat16(tensorflow::DeviceBase*, std::vector<std::unique_ptr<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix, std::default_delete<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix> >, std::allocator<std::unique_ptr<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix, std::default_delete<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix> > > > const&, tensorflow::TTypes<tensorflow::bfloat16, 2, int>::Matrix*)' bazel-out/arm-opt/bin/tensorflow/core/kernels/_objs/list_kernels/list_kernels.pic.o:list_kernels.cc:function tensorflow::TensorListGather<Eigen::ThreadPoolDevice, tensorflow::bfloat16>::Compute(tensorflow::OpKernelContext*): error: undefined reference to 'void tensorflow::ConcatCPUtensorflow::bfloat16(tensorflow::DeviceBase*, std::vector<std::unique_ptr<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix, std::default_delete<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix> >, std::allocator<std::unique_ptr<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix, std::default_delete<tensorflow::TTypes<tensorflow::bfloat16, 2, int>::ConstMatrix> > > > const&, tensorflow::TTypes<tensorflow::bfloat16, 2, int>::Matrix*)' collect2: error: ld returned 1 exit status Target //tensorflow:libtensorflow_cc.so failed to build INFO: Elapsed time: 21254.436s, Critical Path: 1956.26s INFO: 2708 processes: 2708 local. FAILED: Build did NOT complete successfully sole Output/Logs

Describe the Issue

build failed

Steps to Reproduce

download bazelv0.13.0 and edit files as in this git and perform bash ./compile.sh

Hardware/Software Info

RPi3B+, Raspbian OS

ERROR: