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<span id="runtime">
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<h1 id="tutorials-runtime--page-root">
Deploying TRTorch Programs
<a class="headerlink" href="#tutorials-runtime--page-root" title="Permalink to this headline">
¶
</a>
</h1>
<p>
After compiling and saving TRTorch programs there is no longer a strict dependency on the full
TRTorch library. All that is required to run a compiled program is the runtime. There are therfore a couple
options to deploy your programs other than shipping the full trtorch compiler with your applications.
</p>
<h2 id="trtorch-package-libtrtorch-so">
TRTorch package / libtrtorch.so
<a class="headerlink" href="#trtorch-package-libtrtorch-so" title="Permalink to this headline">
¶
</a>
</h2>
<p>
Once a program is compiled, you run it using the standard PyTorch APIs. All that is required is that the package
must be imported in python or linked in C++.
</p>
<h2 id="runtime-library">
Runtime Library
<a class="headerlink" href="#runtime-library" title="Permalink to this headline">
¶
</a>
</h2>
<p>
Distributed with the C++ distribution is
<code class="docutils literal notranslate">
<span class="pre">
libtrtorchrt.so
</span>
</code>
. This library only contains the components
necessary to run TRTorch programs. Instead of linking
<code class="docutils literal notranslate">
<span class="pre">
libtrtorch.so
</span>
</code>
or importing
<code class="docutils literal notranslate">
<span class="pre">
trtorch
</span>
</code>
you can
link
<code class="docutils literal notranslate">
<span class="pre">
libtrtorchrt.so
</span>
</code>
in your deployment programs or use
<code class="docutils literal notranslate">
<span class="pre">
DL_OPEN
</span>
</code>
or
<code class="docutils literal notranslate">
<span class="pre">
LD_PRELOAD
</span>
</code>
. For python
you can load the runtime with
<code class="docutils literal notranslate">
<span class="pre">
torch.ops.load_library("libtrtorchrt.so")
</span>
</code>
. You can then continue to use
programs just as you would otherwise via PyTorch API.
</p>
<div class="admonition note">
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Note
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If you are using the standard distribution of PyTorch in Python on x86, likely you will need the pre-cxx11-abi variant of
<code class="docutils literal notranslate">
<span class="pre">
libtrtorchrt.so
</span>
</code>
, check
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