Intel's Tensorflow optimizations are now available for Linux as a wheel installable through pip.
For more information on the optimizations as well as performance data, see this blog post.
To install the wheel into an existing Python installation, simply run
# Python 2.7
pip install https://anaconda.org/intel/tensorflow/1.3.0/download/tensorflow-1.3.0-cp27-cp27mu-linux_x86_64.whl
# Python 3.5
pip install https://anaconda.org/intel/tensorflow/1.3.0/download/tensorflow-1.3.0-cp35-cp35m-linux_x86_64.whl
# Python 3.6
pip install https://anaconda.org/intel/tensorflow/1.3.0/download/tensorflow-1.3.0-cp36-cp36m-linux_x86_64.whl
Edit 10/12/17: Wheel paths have been updated to 1.3.0
To create a conda environment with Intel Tensorflow that also takes advantage of the Intel Distribution for Python’s optimized numpy, run
conda create -n tf -c intel python=<2|3> pip numpy
. activate tf
# Python 3.5
pip install https://anaconda.org/intel/tensorflow/1.3.0/download/tensorflow-1.3.0-cp35-cp35m-linux_x86_64.whl
# Python 2.7
pip install https://anaconda.org/intel/tensorflow/1.3.0/download/tensorflow-1.3.0-cp27-cp27mu-linux_x86_64.whl
Conda Package Now Available in Intel Python 2018
A conda package of Intel's optimized Tensorflow comes with the new 2018 Intel Python distribution on Linux. You can also create a conda environment with Intel Optimized Tensorflow with the following commands:
conda create -n intel_tf -c intel –override-channels tensorflow
source activate intel_tf
For more such intel IoT resources and tools from Intel, please visit the Intel® Developer Zone
Source:https://software.intel.com/en-us/articles/intel-optimized-tensorflow-wheel-now-available