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  <section id="module-ot.gpu">
<span id="ot-gpu"></span><h1>ot.gpu<a class="headerlink" href="#module-ot.gpu" title="Permalink to this headline"></a></h1>
<p>GPU implementation for several OT solvers and utility
functions.</p>
<p>The GPU backend in handled by <a class="reference external" href="https://cupy.chainer.org/">cupy</a>.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>This module is now deprecated and will be removed in future releases. POT
now privides a backend mechanism that allows for solving prolem on GPU wth
the pytorch backend.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Note that by default the module is not imported in <a class="reference internal" href="../all.html#module-ot" title="ot"><code class="xref py py-mod docutils literal notranslate"><span class="pre">ot</span></code></a>. In order to
use it you need to explicitely import <a class="reference internal" href="#module-ot.gpu" title="ot.gpu"><code class="xref py py-mod docutils literal notranslate"><span class="pre">ot.gpu</span></code></a> .</p>
<p>By default, the functions in this module accept and return numpy arrays
in order to proide drop-in replacement for the other POT function but
the transfer between CPU en GPU comes with a significant overhead.</p>
<p>In order to get the best performances, we recommend to give only cupy
arrays to the functions and desactivate the conversion to numpy of the
result of the function with parameter <code class="docutils literal notranslate"><span class="pre">to_numpy=False</span></code>.</p>
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