Unfortunately TensorFlow—or rather: its build system—hasn’t yet been ported to Windows (but the guys are working on it). Until then, one can get by using Docker containers or running full-blown Linux VMs. With the introduction of the WSL (Windows Subsystem for Linux) as a part of Windows 10 Anniversary Update, however, it has become possible to run the Linux-version of TensorFlow on Windows in its Ubuntu user space (CPU only, sadly). WSL is still in beta, so there are some quirks to be expected. Follow the instructions below to set up a working IPython-TensorFlow environment on Windows 10 Pro:
Step 1: Activate WSL and “Bash on Ubuntu on Windows”First you need to activate the Linux Subsystem and install the Ubuntu user land. First, open Windows Settings (Windows + I) and click on “Windows Update, recovery, backup” (Fig. 1).
|Figure 1: Click on “Update” ...|
|Figure 2: ... to enable developer mode.|
Step 2 (optional): Install mintty for WSLWhen you use the aforementioned short cut, a bash shell starts in a conventional cmd.exe console host. While that is perfectly useable, I personally much prefer mintty (Cygwin's default terminal emulator). Luckily, there's already a version for WSL available: Just download the installer, run it, et voilà, ready to go. The installer also configures the explorer context menu to contain a handy "WSL in Mintty Here" shortcut, which opens a bash session in the current path.
|Figure 7: mintty hosting a bash shell|
Step 3: Install AnacondaAnaconda from Continuum Analytics is the computational science Python distribution. While we could also simply use the default Python distribution from the Ubuntu repositories, Anaconda comes with Intel's MKL and thus a substantial performance boost (not to mention its potent conda package manager). Start a bash shell and download the Anaconda installer by running the following commands
$ cd ~
$ wget https://repo.continuum.io/archive/Anaconda3-4.2.0-Linux-x86_64.sh
$ chmod +x Anaconda3-4.2.0-Linux-x86_64.sh
Note that this installs Anaconda into your WSL home directory. You could install it "system-wide" using sudo, but as WSL environments are per-Windows-user anyway, there isn't much point in doing so. At some point the installer will ask you, whether it should add Anaconda to your Linux PATH, effectively making it the default Python. Confirm by entering "yes" (Fig. 8).
|Figure 8: YES!!!|
. Alternatively you can "source" (reload/re-execute) .bashrc via
$ . ~/.bashrc
Now you should be able to run
And see a message like this:
Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 2 2016, 17:53:06)
Type "copyright", "credits" or "license" for more information.
IPython 5.1.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
Yet, when you enter the command (IPython magic)
In : %pylab
Python will throw some PyQt4 error at us:
---> 31 from .qt_compat import QtCore, QtGui, QtWidgets, _getSaveFileName, __version__
32 from matplotlib.backends.qt_editor.formsubplottool import UiSubplotTool
135 # have been changed in the above if block
136 if QT_API in [QT_API_PYQT, QT_API_PYQTv2]: # PyQt4 API
--> 137 from PyQt4 import QtCore, QtGui
ImportError: No module named 'PyQt4'
Step 4: Fix Matplotlib PyQt4 ErrorThe above error is already known by the Anaconda developers. Sadly, the proposed solutions like explicitly selecting the Qt5Agg backend or downgrading to Qt4 didn't work for me. What did work was switchting to the TkAgg. For that you need to create a new text file
$ vi ~/.config/matplotlib/matplotlibrc
(use nano, if you can't handle vi...) and add the following line
backend : TkAgg
When you now start IPython again, executing %pylab should work fine ...
In : %pylab
Using matplotlib backend: TkAgg
Populating the interactive namespace from numpy and matplotlib
... only to run into the next error when trying to create a little test plot:
In : x = linspace(0, 10, 1000)
In : plot(x, x**2)
OMP: Error #100: Fatal system error detected.
OMP: System error #22: Invalid argument
Step 5: Work Around OpenMP ErrorThe previous error also is already known, though not yet fixed. To work around this bug(?), edit your .bashrc
$ vi ~/.bashrc
and add the line
to the end of the file. Run
$ . ~/.bashrc
again and re-try %pylab and plotting. This time, IPython will reward us with a new error message:
-> 1868 self.tk = _tkinter.create(screenName, baseName, className, interactive, wantobjects, useTk, sync, use)
1869 if useTk:
TclError: no display name and no $DISPLAY environment variable
Step 6: Install X11 Server and set $DISPLAYMatplotlib needs an X server to draw its plot windows. Nowadays I recommend VcXsrv, which is easy to install and just works out of the box. You could use Cygwin/X or Xming, but at least the former requires some fiddeling with its setting for it to work with WSL.
After having installed and started your X server of choice, edit your .bashrc again to add the following line
$ . ~/.bashrc
Now, IPython/matplotlib should finally work.
Step 7: Install TensorFlowThe TensorFlow installation itself is pretty straight-forward: Execute
$ conda install -c conda-forge tensorflow
Alongside of raw TensorFlow, you may also want to install a deep learning library like Keras, which is easily installed via PIP
$ pip install keras
When you now start again IPython and enter
you should get a little "using TensorFlow backend" message, indicating your successful installation of TensorFlow on Windows!
|Figure 9: When installed correctly, Keras defaults to TensorFlow as its backend|
|Figure 10: Training a (small) CNN using TensorFlow on WSL|