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<p>Building TensorFlow from source can give better performance than the official standard build. This is because the
<blockquote cite="https://www.tensorflow.org/performance/performance_guide#building_and_installing_from_source">
<p>default TensorFlow binaries target the broadest range of hardware to make TensorFlow accessible to everyone. If using CPUs for training or inference, it is recommended to compile TensorFlow with all of the optimizations
available for the CPU in use.</p>
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<a href="https://www.tensorflow.org/performance/performance_guide#building_and_installing_from_source">Building
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<ul>
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</li>
<li>In collaboration with the different product, service, and operations teams, we advance the application of state-of-the-art AI</li>
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<a href="https://github.com/thoth-station" target="_blank">
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</a> or
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</a>.</p>
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<h1>How we build them</h1>
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details on the build process you may have a look at
<a href="https://github.com/thoth-station/tensorflow-build-s2i">our build tool chain</a>.
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<h1>Python Simple Index</h1>
<section><a href="index/">AICoE's TensorFlow</a>
</section>
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<h1>How to use it</h1>
<p>Using these wheels with your Python application is very simple, just use the directory we provide as a source in your Pipfile or requirements.txt.</p>
<h2>Pipenv</h2>
<p>Here is a simple example of a
<code>Pipfile</code>.
<pre>
[[source]]
url ="https://tensorflow.pypi.thoth-station.ninja/index/manylinux2010/AVX2/simple/"
verify_ssl = true
name = "redhat-aicoe-experiments"
[[source]]
url = "https://pypi.python.org/simple"
verify_ssl = true
name = "pypi"
[requires]
python_version = "3.6"
[packages]
tensorflow = {version="==1.13.2", index="redhat-aicoe-experiments"}
[pipenv]
allow_prereleases = true</pre>
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