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diff --git a/tensorflow/docs_src/install/install_raspbian.md b/tensorflow/docs_src/install/install_raspbian.md deleted file mode 100644 index cf6b6b4f79..0000000000 --- a/tensorflow/docs_src/install/install_raspbian.md +++ /dev/null @@ -1,313 +0,0 @@ -# Install TensorFlow on Raspbian - -This guide explains how to install TensorFlow on a Raspberry Pi running -Raspbian. Although these instructions might also work on other Pi variants, we -have only tested (and we only support) these instructions on machines meeting -the following requirements: - -* Raspberry Pi devices running Raspbian 9.0 or higher - -## Determine how to install TensorFlow - -You must pick the mechanism by which you install TensorFlow. The supported -choices are as follows: - -* "Native" pip. -* Cross-compiling from sources. - -**We recommend pip installation.** - -## Installing with native pip - -We have uploaded the TensorFlow binaries to piwheels.org. Therefore, you can -install TensorFlow through pip. - -The [REQUIRED_PACKAGES section of -setup.py](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/setup.py) -lists the packages that pip will install or upgrade. - -### Prerequisite: Python - -In order to install TensorFlow, your system must contain one of the following -Python versions: - -* Python 2.7 -* Python 3.4+ - -If your system does not already have one of the preceding Python versions, -[install](https://wiki.python.org/moin/BeginnersGuide/Download) it now. It -should already be included when Raspbian was installed though, so no extra steps -should be needed. - -### Prerequisite: pip - -[Pip](https://en.wikipedia.org/wiki/Pip_\(package_manager\)) installs and -manages software packages written in Python. If you intend to install with -native pip, then one of the following flavors of pip must be installed on your -system: - -* `pip3`, for Python 3.n (preferred). -* `pip`, for Python 2.7. - -`pip` or `pip3` was probably installed on your system when you installed Python. -To determine whether pip or pip3 is actually installed on your system, issue one -of the following commands: - -<pre>$ <b>pip3 -V</b> # for Python 3.n -$ <b>pip -V</b> # for Python 2.7</pre> - -If it gives the error "Command not found", then the package has not been -installed yet. To install if for the first time, run: - -<pre>$ sudo apt-get install python3-pip # for Python 3.n -$ sudo apt-get install python-pip # for Python 2.7</pre> - -You can find more help on installing and upgrading pip in -[the Raspberry Pi documentation](https://www.raspberrypi.org/documentation/linux/software/python.md). - -### Prerequisite: Atlas - -[Atlas](http://math-atlas.sourceforge.net/) is a linear algebra library that -numpy depends on, and so needs to be installed before TensorFlow. To add it to -your system, run the following command: - -<pre>$ sudo apt install libatlas-base-dev</pre> - -### Install TensorFlow - -Assuming the prerequisite software is installed on your Pi, install TensorFlow -by invoking **one** of the following commands: - -<pre>$ <b>pip3 install tensorflow</b> # Python 3.n -$ <b>pip install tensorflow</b> # Python 2.7</pre> - -This can take some time on certain platforms like the Pi Zero, where some Python -packages like scipy that TensorFlow depends on need to be compiled before the -installation can complete. The Python 3 version will typically be faster to -install because piwheels.org has pre-built versions of the dependencies -available, so this is our recommended option. - -### Next Steps - -After installing TensorFlow, [validate your -installation](#ValidateYourInstallation) to confirm that the installation worked -properly. - -### Uninstalling TensorFlow - -To uninstall TensorFlow, issue one of following commands: - -<pre>$ <b>pip uninstall tensorflow</b> -$ <b>pip3 uninstall tensorflow</b> </pre> - -## Cross-compiling from sources - -Cross-compilation means building on a different machine than than you'll be -deploying on. Since Raspberry Pi's only have limited RAM and comparatively slow -processors, and TensorFlow has a large amount of source code to compile, it's -easier to use a MacOS or Linux desktop or laptop to handle the build process. -Because it can take over 24 hours to build on a Pi, and requires external swap -space to cope with the memory shortage, we recommend using cross-compilation if -you do need to compile TensorFlow from source. To make the dependency management -process easier, we also recommend using Docker to help simplify building. - -Note that we provide well-tested, pre-built TensorFlow binaries for Raspbian -systems. So, don't build a TensorFlow binary yourself unless you are very -comfortable building complex packages from source and dealing with the -inevitable aftermath should things not go exactly as documented - -### Prerequisite: Docker - -Install Docker on your machine as described in the [Docker -documentation](https://docs.docker.com/engine/installation/#/on-macos-and-windows). - -### Clone the TensorFlow repository - -Start the process of building TensorFlow by cloning a TensorFlow repository. - -To clone **the latest** TensorFlow repository, issue the following command: - -<pre>$ <b>git clone https://github.com/tensorflow/tensorflow</b> </pre> - -The preceding <code>git clone</code> command creates a subdirectory named -`tensorflow`. After cloning, you may optionally build a **specific branch** -(such as a release branch) by invoking the following commands: - -<pre> -$ <b>cd tensorflow</b> -$ <b>git checkout</b> <i>Branch</i> # where <i>Branch</i> is the desired branch -</pre> - -For example, to work with the `r1.0` release instead of the master release, -issue the following command: - -<pre>$ <b>git checkout r1.0</b></pre> - -### Build from source - -To compile TensorFlow and produce a binary pip can install, do the following: - -1. Start a terminal. -2. Navigate to the directory containing the tensorflow source code. -3. Run a command to cross-compile the library, for example: - -<pre>$ CI_DOCKER_EXTRA_PARAMS="-e CI_BUILD_PYTHON=python3 -e CROSSTOOL_PYTHON_INCLUDE_PATH=/usr/include/python3.4" \ -tensorflow/tools/ci_build/ci_build.sh PI-PYTHON3 tensorflow/tools/ci_build/pi/build_raspberry_pi.sh - </pre> - -This will build a pip .whl file for Python 3.4, with Arm v7 instructions that -will only work on the Pi models 2 or 3. These NEON instructions are required for -the fastest operation on those devices, but you can build a library that will -run across all Pi devices by passing `PI_ONE` at the end of the command line. -You can also target Python 2.7 by omitting the initial docker parameters. Here's -an example of building for Python 2.7 and Raspberry Pi model Zero or One -devices: - -<pre>$ tensorflow/tools/ci_build/ci_build.sh PI tensorflow/tools/ci_build/pi/build_raspberry_pi.sh PI_ONE</pre> - -This will take some time to complete, typically twenty or thirty minutes, and -should produce a .whl file in an output-artifacts sub-folder inside your source -tree at the end. This wheel file can be installed through pip or pip3 (depending -on your Python version) by copying it to a Raspberry Pi and running a terminal -command like this (with the name of your actual file substituted): - -<pre>$ pip3 install tensorflow-1.9.0-cp34-none-linux_armv7l.whl</pre> - -### Troubleshooting the build - -The build script uses Docker internally to create a Linux virtual machine to -handle the compilation. If you do have problems running the script, first check -that you're able to run Docker tests like `docker run hello-world` on your -system. - -If you're building from the latest development branch, try syncing to an older -version that's known to work, for example release 1.9, with a command like this: - -<pre>$ <b>git checkout r1.0</b></pre> - -<a name="ValidateYourInstallation"></a> - -## Validate your installation - -To validate your TensorFlow installation, do the following: - -1. Ensure that your environment is prepared to run TensorFlow programs. -2. Run a short TensorFlow program. - -### Prepare your environment - -If you installed on native pip, Virtualenv, or Anaconda, then do the following: - -1. Start a terminal. -2. If you installed TensorFlow source code, navigate to any directory *except* - one containing TensorFlow source code. - -### Run a short TensorFlow program - -Invoke python from your shell as follows: - -<pre>$ <b>python</b></pre> - -Enter the following short program inside the python interactive shell: - -```python -# Python -import tensorflow as tf -hello = tf.constant('Hello, TensorFlow!') -sess = tf.Session() -print(sess.run(hello)) -``` - -If the system outputs the following, then you are ready to begin writing -TensorFlow programs: - -<pre>Hello, TensorFlow!</pre> - -If you're running with Python 3.5, you may see a warning when you first import -TensorFlow. This is not an error, and TensorFlow should continue to run with no -problems, despite the log message. - -If the system outputs an error message instead of a greeting, see [Common -installation problems](#common_installation_problems). - -To learn more, see the [TensorFlow tutorials](../tutorials/). - -## Common installation problems - -We are relying on Stack Overflow to document TensorFlow installation problems -and their remedies. The following table contains links to Stack Overflow answers -for some common installation problems. If you encounter an error message or -other installation problem not listed in the following table, search for it on -Stack Overflow. If Stack Overflow doesn't show the error message, ask a new -question about it on Stack Overflow and specify the `tensorflow` tag. - -<table> -<tr> <th>Stack Overflow Link</th> <th>Error Message</th> </tr> - - -<tr> - <td><a href="http://stackoverflow.com/q/42006320">42006320</a></td> - <td><pre>ImportError: Traceback (most recent call last): -File ".../tensorflow/core/framework/graph_pb2.py", line 6, in <module> -from google.protobuf import descriptor as _descriptor -ImportError: cannot import name 'descriptor'</pre> - </td> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/q/33623453">33623453</a></td> - <td><pre>IOError: [Errno 2] No such file or directory: - '/tmp/pip-o6Tpui-build/setup.py'</tt></pre> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/questions/35190574">35190574</a> </td> - <td><pre>SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify - failed</pre></td> -</tr> - -<tr> - <td><a href="http://stackoverflow.com/q/42009190">42009190</a></td> - <td><pre> - Installing collected packages: setuptools, protobuf, wheel, numpy, tensorflow - Found existing installation: setuptools 1.1.6 - Uninstalling setuptools-1.1.6: - Exception: - ... - [Errno 1] Operation not permitted: - '/tmp/pip-a1DXRT-uninstall/.../lib/python/_markerlib' </pre></td> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/q/33622019">33622019</a></td> - <td><pre>ImportError: No module named copyreg</pre></td> -</tr> - -<tr> - <td><a href="http://stackoverflow.com/q/37810228">37810228</a></td> - <td>During a <tt>pip install</tt> operation, the system returns: - <pre>OSError: [Errno 1] Operation not permitted</pre> - </td> -</tr> - -<tr> - <td><a href="http://stackoverflow.com/q/33622842">33622842</a></td> - <td>An <tt>import tensorflow</tt> statement triggers an error such as the - following:<pre>Traceback (most recent call last): - File "<stdin>", line 1, in <module> - File "/usr/local/lib/python2.7/site-packages/tensorflow/__init__.py", - line 4, in <module> - from tensorflow.python import * - ... - File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/tensor_shape_pb2.py", - line 22, in <module> - serialized_pb=_b('\n,tensorflow/core/framework/tensor_shape.proto\x12\ntensorflow\"d\n\x10TensorShapeProto\x12-\n\x03\x64im\x18\x02 - \x03(\x0b\x32 - .tensorflow.TensorShapeProto.Dim\x1a!\n\x03\x44im\x12\x0c\n\x04size\x18\x01 - \x01(\x03\x12\x0c\n\x04name\x18\x02 \x01(\tb\x06proto3') - TypeError: __init__() got an unexpected keyword argument 'syntax'</pre> - </td> -</tr> - - -</table> |